| 1. |
- Ahmadi, Alireza, et al.
(författare)
-
Optimum Failure Finding Inspection During Extended Operation Life
- 2013
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Konferensbidrag (refereegranskat)abstract
- In a complex system such as railway and aviation equipment’s, it may be necessary to employ a combination of Failure Finding Inspection (FFI) and a scheduled discard task, as suggested by Reliability-Centered Maintenance (RCM). This strategy ensures an adequate level of availability of hidden functions, as well as the reduction of the risk of multiple failures to an acceptable level. However, in some situations, operators prefer to extend the discard life of components beyond their recommended life limit, due to the operational restrictions. This necessitates the definition of an optimal Failure Finding Inspection interval for the extended life period. This paper aims to provide a mathematical model for defining optimal FFI interval, during the extended period of the replacement life. A cost function (CF) is developed to identify the cost per unit of time associated with different FFI intervals, for the proposed extended period of life, i.e. postponement period. The proposed method concerns as-bad-as-old (ABAO) inspection and repairs (due to failures found by inspection). It considers inspection and repair times, and takes into account the costs associated with inspection and repair, the opportunity cost of lost production due to maintenance downtime created by inspection and repair actions, and also the cost of accidents due to the occurrence of multiple failure
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| 2. |
- Asplund, Matthias, et al.
(författare)
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A study of railway wheel profile parameters used as indicators of an increased risk of wheel defects
- 2016
-
Ingår i: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit. - : SAGE Publications. - 0954-4097 .- 2041-3017. ; 230:2, s. 323-334
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Tidskriftsartikel (refereegranskat)abstract
- The capacity demands on the railways will increase in the future, as well as the demands for a robust and available system. The availability of the railway system is dependent on the condition of the infrastructure and the rolling stock. To inspect the rolling stock and to prevent damage to the track due to faulty wheels, infrastructure managers normally install wayside monitoring systems along the track. Such systems indicate, for example, wheels that fall outside the defined safety limits and have to be removed from service to prevent further damage to the track. Due to the nature of many wayside monitoring systems, which only monitor vehicles at definite points along the track, damage may be induced on the track prior to fault detection at the location of the system. Such damage can entail capacity-consuming speed reductions and manual track inspections before the track can be opened for traffic again. The number of wheel defects must therefore be kept to a minimum. In this paper wheel profile parameters measured by a wayside wheel profile measurement system, installed along the Swedish Iron Ore Line, are examined and related to warning and alarm indications from a wheel defect detector installed on the same line. The study shows that an increased wheel wear, detectable by changes in the wheel profile parameters could be used to reduce the risk of capacity-consuming wheel defect failure events and its reactive measures.
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| 3. |
- Asplund, Matthias, et al.
(författare)
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Assessment of the data quality of wayside wheel profile measurements
- 2016
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Ingår i: International Journal of COMADEM. - 1363-7681. ; 19:3, s. 19-25
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Tidskriftsartikel (refereegranskat)abstract
- To evaluate the behaviour and the condition of a railway wheel in relation to performance and safety criteria, the wheel profile can be measured. This can be achieved using manual methods or automatic systems mounted along the railway track. Such systems have the advantage that they can measure a vast number of profiles, enabling new possibilities of performing statistical analyses of the results and pinpointing bad wheels at an early stage. These wayside measurement systems are, however, subjected to different environmental conditions that can affect the data quality of the measurement. If one is to be able to use automatic wheel profile measurements, the data quality has to be controlled in order to facilitate maintenance decisions. This paper proposes a method for the data quality assessment of an automatic wayside condition monitoring system measuring railway rolling stock wheels. The purpose of the assessment method proposed in this paper is to validate individual wheel profile measurements to ensure the accuracy of the wheel profile measurement data and hence the following data analysis. The method consists of a check routine based on the paired t-test, which uses a hypothesis test to verify if the null hypotheses are true. The check routine compares measurements of passing wheels rolling to a certain destination with measurements of the same wheels returning from that destination. The routine of comparing measurements of the same wheel, which is performed by four sensors (one on each side of each rail), will ensure that the sensors generate the same data for the same sample. A case study is presented which shows how the method can detect a faulty setup of the measurement system and prevent incorrect interpretations of the data from different measurement units in the same system. The paper ends with a discussion and conclusions concerning the improvements that are presented.
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| 4. |
- Asplund, Matthias, et al.
(författare)
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Automatic laser scanning of wheel profiles: condition monitoring to achieve greater capacity for existing infrastructure in an extreme climate
- 2013
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Ingår i: Automatic laser scanning of wheel profiles. - India : Indian Railways, the host of 10th IHHA Conferance. - 9788192651910 ; , s. 445-451
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Konferensbidrag (refereegranskat)abstract
- The Iron Ore Line (Malmbanan) is a 473 km long track section located in northern Sweden and has been in operation since 1903. It is mainly used to transport iron ore and pellets from the mines in Kiruna and Malmberget to Narvik Harbour (Norway) in the northwest and Luleå Harbour (Sweden) in the southeast. The track section on the Swedish side is owned by the Swedish Government and managed by Trafikverket (the Swedish Transport Administration), while the ore wagons are owned and managed by the freight operator (LKAB). Due to the high axle load exerted by the iron ore transports, 30 tonnes, and the high demand for a constant ore/pellets flow, the track and wagons must be monitored and maintained on a regular basis. The condition of the wagon wheel profile is one of the most important aspects in this procedure. For this reason an automatic laser-based wheel profile monitoring system has been installed on this line. This system can automatically measure and monitor the wagon wheel profiles at speeds up to 130 km/h. The system was installed and is being operated in a collaboration project between the freight operator and infrastructure manager. The information generated is collected by the e-maintenance personnel at Luleå Railway Research Center (JVTC). The measurements will be used to diagnose the condition of the wheel and rail, and to optimize their maintenance further. This paper presents a study of the selection and the installation of the equipment. Some results from the measurements are shown. The system’s availability during performance in extreme climate conditions, with severe cold and large quantities of snow, is presented. Then the benefits and perceived challenges of the system are discussed. Some potential improvements in rail and wheel maintenance, to achieve more capacity, are analysed.
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| 5. |
- Asplund, Matthias, et al.
(författare)
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Combating curve squeal noise
- 2016
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Ingår i: Combating curve squeal noise.
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Konferensbidrag (refereegranskat)abstract
- Society demand for more sustainable transports is increasing, starting a modal shift from road to railway. The resulting increase in railway traffic intensity is leading to more activities on the track, even during the night time. For many years continuous urbanization has been resulting in a higher density of residents in areas close to railway tracks. The combination of these factors is raising the issue of noise disturbances from railway transports, which is forcing infrastructure managers to take action to combat noise from railway traffic systematically. There are different types of noise emanating from railways and one of the most annoying is curve squeal noise. This paper deals with the curve squeal phenomenon, the places where it occurs, and different methods for reducing it. The curving behaviour of a vehicle plays an important role in the generation of curve squeals, and therefore the way in which different rail profiles affect the capability to steer in a sharp curve is dealt within this paper. The paper is based on two case studies with investigated curves in urban regions that suffer from squeal noise, and in which comparisons between measurements and simulations were performed. The outcome of these studies is a workflow for combating squeal noise, results concerning the effects of a top-of-rail friction modifier on noise mitigation, and a proposed rail profiles for improving the steering capability of vehicles.
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| 6. |
- Asplund, Matthias, et al.
(författare)
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Condition monitoring and e-maintenance solution of railway wheels
- 2014
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Ingår i: Journal of Quality in Maintenance Engineering. - 1355-2511 .- 1758-7832. ; 20:3, s. 216-232
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Tidskriftsartikel (refereegranskat)abstract
- Purpose – The purpose of this paper is to investigate the failure-driven capacity consumption of wheels on the track, to determine whether there are some relations to vehicle wheel configurations that show a larger amount of failures, and to ascertain the influence of the temperature and the travelling direction of the train on the number of events. This information can be used to develop prognostic health management (PHM) so that more track capacity can be gained without modifications, re-building or re-investments. Design/methodology/approach – This paper presents a study of 1,509 warning and alarm events concerning train wheels. The data come from the infrastructure manager’s wheel defect detectors and wheel profile measurement system. These data have been analysed and processed to find patterns and connections to different vehicles, travelling directions and temperatures. Findings – Lower temperatures increase the probability of wheels having high vertical forces. Trains with different wheel configurations show different results. With high vertical forces, the probability of wheel failures at axle 6 and 7 is high for locomotives with two bogies and three axles in each bogie (2x3). All these findings can be used to develop the maintenance, monitoring and inspection principles for wheels. Practical implications – The inspection of wheels to detect failures needs to be more frequent on days and in seasons with lower temperatures. The wheel inspection should be performed more frequently at axle 6 and 7 for locomotives with a 2x3 wheel configuration. The inspection and monitoring of wheels need to be carried out more carefully for trains travelling south, to avoid a large amount of wheels with high force levels rolling in the southern direction. Originality/value – The analysis carried out in this paper identifies important factors that correlate with the high occurrence of wheel defects. It also proposes a conceptual e-maintenance model for the combination of wheel condition monitoring data from different system. The value of this study is the provision of information to support prognostic and health management system to support proactive maintenance.
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| 7. |
- Asplund, Matthias, et al.
(författare)
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Condition monitoring of rolling stock wheels : approach towards maintenance decision making
- 2014
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Ingår i: 27th International Congress on Condition Monitoring and Diagnostic Engineering (COMADEM 2014). - : COMADEM International.
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Konferensbidrag (refereegranskat)abstract
- Due to the more or less fixed inherent capacity of a railway system, capacity consuming events like failures within a railway network should be kept to a minimum. This could be achieved by the use of existing and new condition monitoring systems which can detect, report and predict failure events in an early stage. Demands for higher service quality, higher capacity, network availability and track quality together with less human intervention on tracks, drive the development of railway condition monitoring systems.Failure driven capacity consumption due to worn or defected rolling stock wheels have a big impact on the capacity and the infrastructure condition. Wheel defects such as out-of-round wheels, generates high forces, and could result in large capacity consumption especially for areas with cold climate conditions. Bad wheels cause even higher track wear that reduce the life length of the track. Wheels with fatigue defects could also influence the track safety issues. This paper presents how different wheel defects can be monitored; together with a review of the most common wayside condition monitoring systems on the Swedish railway network. The study also describes how the decision making process could take advantage of the condition monitoring data in order to increase the achieved network capacity.
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| 8. |
- Asplund, Matthias, et al.
(författare)
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Data quality assessment of automatic wheel profile measurement systems
- 2016
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Ingår i: Current Trends in Reliability, Availability, Maintainability and Safety. - Cham : Encyclopedia of Global Archaeology/Springer Verlag. - 9783319235967 - 9783319235974 ; , s. 717-738
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Konferensbidrag (refereegranskat)abstract
- The aim of this paper is to present a method for the quality assessment of data from a condition monitoring system for rolling stock wheels to ascertain if the data have the right quality to be used for further analyses. This quality assessment will also show if there are variations between different measurement units for the same system, and if there are relations between different wheel parameter measurements, speed and time. The assessment of data is accomplished using the quality dimension freedom of error. There are two different data sources, namely an automatic wheel profile measurement system and a manual wheel profile measurement device. The manual measurements of wheel profiles are used for verifying the accuracy of the automatic wheel profile measurements, which constitute the larger data set. The proposed method for evaluating the data quality is demonstrated using the data from a specific condition monitoring system. The results show some inconsistencies indicating that this system lacks quality in the dimension of freedom of error and that there is need for internal calibration or self-adjustment of the studied system for quality reasons.
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| 9. |
- Asplund, Matthias, et al.
(författare)
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Enhancing the quality of data from a wheel profile measurement system : a proposed approach
- 2015
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Konferensbidrag (refereegranskat)abstract
- This investigation proposes a method for increasing the quality of data from an automatic condition monitoring system for railway rolling stock wheels, in order to assure the right data quality for further use of the data. The data quality improvement is used to ensure a higher reliability of the data analysis and to propose a new check routine to ensure that the sensors generate the same data for the same sample. A case study on field data shows how the data from different measurement setups differ for three of four measurements and why this check routine is needed. The paper ends with a discussion and conclusions concerning the improvements that are presented.
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| 10. |
- Asplund, Matthias, et al.
(författare)
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Evaluation of wheel profile measurements by means of the contact-point function for the wheel-rail interface
- 2018
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Ingår i: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit. - : Sage Publications. - 0954-4097 .- 2041-3017. ; 232:4, s. 1225-1239
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Tidskriftsartikel (refereegranskat)abstract
- This study examines the accuracy of a wayside train wheel profile measurement system. This was accomplished by an evaluation of the contact-point function for the wheel–rail interface. The wheel profile measurement system in question generates data about the wheel profiles of passing trains. These data are used for improving the wheel maintenance procedures for the rolling stock operator. Recent work shows that there are differences between the data from the two different units in the system, but how this influences further use of the data, e.g. in wheel–rail contact analysis, has not been investigated so far. Accordingly, this article shows how two key wheel measures (the wheel flange thickness and the wheel profile) impact on the contact-point function and which of these measures has the largest impact on the contact-point function. The data used in this study were generated by two different measurement units for the same wheel and with the same wheel status. The results show that the different units produce different results and that these differences are more prominent when a difference in the flange thickness is detected, with a resulting shift of the front side of the flange and of the tread. With no difference in the flange thickness, i.e. no shift of the front side of the flange and of the tread, a difference was still detected in the contact conditions. Furthermore, this investigation shows that the shape of the tread has a greater impact on the contact-point conditions compared to a change in the flange thickness of up to 2.5 mm. This difference in the tread shape could have originated in measurement noise or different wheel measurement positions. The results of the study also show the importance of managing the measurement quality before using the data, for example for maintenance decisions.
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| 11. |
- Asplund, Matthias, et al.
(författare)
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Inspection of railway turnouts using camera
- 2013
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Konferensbidrag (refereegranskat)abstract
- The railway turnout is an essential component in a railway system, used to divert traffic along different tracks. A turnout includes a number of different parts, including the switch blade, frog, point machine, switch roller, soleplate, check rail, wing rail, drive rods, control rods and other bars. These parts must be kept in good condition, meeting functional and safety requirements. Failing to comply will result in a reduction of the network’s capacity with economic consequences. Not honouring the safety limits could result in severe accidents, including derailment, causing human casualties. By performing the right type of inspection and/or maintenance at the right time, these unwanted events can be reduced. To determine if and when a maintenance action should be performed, the condition of the turnout must be established, usually by manual inspections or with measurement vehicles. The drawback is the discrete nature of these inspection events. Failure modes with development times shorter than the inspection interval could result in a malfunction of the unit. An on-line measurement system would be able to deal with these failure events and initiate correct maintenance actions at an earlier stage. With an on-line system, remotely located turnouts could be inspected without on-site personnel. Capacity consuming failures of turnouts with a strategic location or with bottleneck characteristics could also be corrected before they affect traffic. This paper describes a feasibility study of a camera based inspection system for turnouts and discusses the effect the method could have on system reliability and capacity.
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| 12. |
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| 13. |
- Asplund, Matthias, et al.
(författare)
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Reliability and measurement accuracy of a condition monitoring system in an extreme climate : a case study of automatic laser scanning of wheel profiles
- 2014
-
Ingår i: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit. - : SAGE Publications. - 0954-4097 .- 2041-3017. ; 228:6, s. 695-704
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Tidskriftsartikel (refereegranskat)abstract
- The Iron Ore Line (Malmbanan) is a 473 km long track section located in northern Sweden and has been in operation since 1903. This track section stretches through two countries, namely Sweden and Norway, and the main part of the track runs on the Swedish side, where the owner is the Swedish Government and the infrastructure manager is Trafikverket (the Swedish Transport Administration). The ore trains are owned and managed by the freight operator and mining company LKAB. Due to the high axle load exerted by transportation of the iron ore, 30 tonnes, and the high demand for a constant flow of ore and pellets, the track and wagons must be monitored and maintained on a regular basis. The condition of the wagon wheel is one of the most important aspects in this connection, and here the wheel profile plays an important role. For this reason an automatic laser-based wheel profile monitoring system (WPMS) has been installed on this line using a system lifecycle approach that is based on the reliability, availability, maintainability and safety (RAMS) approach for railways. The system was prepared and installed and is being operated in a collaborative project between the freight operator and infrastructure manager. The measurements are used to diagnose the condition of the wheels, and to further optimize their maintenance. This paper presents a study of the concepts and ideas of the WPMS, and the selection, installation and validation of the equipment using a system lifecycle approach that is based on RAMS for railways. Results from the profile measurements and validation are shown. The system’s reliability during performance in extreme climate conditions, with severe cold and large quantities of snow, is presented. Then the benefits, perceived challenges and acquired knowledge of the system are discussed, and an improved V-model for the lifecycle approach is presented.
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| 14. |
- Blidberg, Karin, et al.
(författare)
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LOWNOISEPAD : Low cost noise control by optimised rail pad
- 2024
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Ingår i: Sammanställning av referat från Transportforum 2024. - Linköping : Statens väg- och transportforskningsinstitut. ; , s. 324-324
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Trafikverket har i samarbete med UIC (Internatinella järnvägsunionen) och Luleå Tekniska Universitet medverkat i projektet LOWNOISEPAD. Syftet är att utveckla mellanlägg (pads) som är optimerade ur bullersynpunkt, utan att andra tekniskt viktiga egenskaper försämras. Slutrapport från UIC och mätrapporter från LTU förväntas bli klara under hösten 2023. Projektet har bestått av sex arbetspaketWP1: Preparation of proceduresWP2: Analysis of the current situationWP3: Selection of the rail pads to be testedWP4: Test site selection and rail pad installationWP5: MeasurementsWP6: Data processing and dissemination och genomförts parallellt med samma metod på järnvägen i tolv Europeiska länder.I projektet påvisas möjliga källbullerreduktioner på 1-5 dBA. De dynamiska egenskaperna på mellanlägg (gummiplattor mellan betongslipers och räl) påverkar bulleremissionerna från järnväg och det är tekniskt möjligt att minska bullret från järnvägen genom att förändra dessa egenskapskrav.
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| 15. |
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| 16. |
- Castaño, Miguel, et al.
(författare)
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3D Synthetic Aperture Imaging Using a Water-Jet Coupled Large Aperture Single Transducer
- 2014
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Ingår i: 2014 IEEE International Ultrasonics Symposium (IUS 2014). - Piscataway, NJ : IEEE Communications Society. - 9781479970490 ; , s. 1372-1375
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Konferensbidrag (refereegranskat)abstract
- This paper presents a technique for in-situ non-destructive testing of materials with applications in railway crossings. The novelty is in successfully applying the Virtual Source (VS) concept using water jet coupling for a large transducer. By focusing the sound field at the surface of the sample, the water jet probe can be built with a small nozzle opening, limiting the water consumption and making it viable for field applications. The annular geometry of the large transducer ensures the spherical wavefront assumed in the application of the SAFT algorithm, which usually limits the size of the transducer
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| 17. |
- Chandran, Praneeth, et al.
(författare)
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An Investigation of Railway Fastener Detection Using Image Processing and Augmented Deep Learning
- 2021
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Ingår i: Sustainability. - : MDPI. - 2071-1050. ; 13:21
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Tidskriftsartikel (refereegranskat)abstract
- The rail fastening system forms an indispensable part of the rail tracks and needs to be periodically inspected to ensure safe, reliable and sustainable rail operations. Automated visual inspection has gained significant importance for fastener inspection in recent years. Position accuracy, robustness, and practical limitations due to the complex environment are some of the major concerns associated with this method. This study investigates the combined use of image processing and deep learning algorithms for detecting missing clamps within a rail fastening system. The images used for this study was acquired during field inspections carried out along the Borlänge-Avesta line in Sweden. The image processing techniques proposed in this study enabled the improvement of the fastener position and removal of redundant information from the fastener images. In addition, image augmentation was carried out to enhance the data set, ensure experimental reliability and replicate practical challenges associated with such visual inspection. Convolutional neural network and ResNet-50 algorithms are used for classification purposes, and both the algorithms achieved over 98% accuracy during training and validation and over 94% accuracy during the test stage. Both the algorithms also maintained a good balance between the precision and recall scores during the test stage. CNN and ResNet-50 algorithms were also tested to analyse their performances when the clamp areas were covered. CNN was able to accurately predict the fastener state up to 70% of clamp area occlusion, and ResNet-50 was able to achieve accurate predictions up to 75% of clamp area occlusion.
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| 18. |
- Chandran, Praneeth, et al.
(författare)
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Supervised Machine Learning Approach for Detecting Missing Clamps in Rail Fastening System from Differential Eddy Current Measurements
- 2021
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Ingår i: Applied Sciences. - : MDPI. - 2076-3417. ; 11:9
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Tidskriftsartikel (refereegranskat)abstract
- The rail fastening system forms an integral part of rail tracks, as it maintains the rail in a fixed position, upholding the track stability and track gauge. Hence, it becomes necessary to monitor their conditions periodically to ensure safe and reliable operation of the railway. Inspection is normally carried out manually by trained operators or by employing 2-D visual inspection methods. However, these methods have drawbacks when visibility is minimal and are found to be expensive and time consuming. In the previous study, the authors proposed a train-based differential eddy current sensor system that uses the principle of electromagnetic induction for inspecting the railway fastening system that can overcome the above-mentioned challenges. The sensor system includes two individual differential eddy current sensors with a driving field frequency of 18 kHz and 27 kHz respectively. This study analyses the performance of a machine learning algorithm for detecting and analysing missing clamps within the fastening system, measured using a train-based differential eddy current sensor. The data required for the study was collected from field measurements carried out along a heavy haul railway line in the north of Sweden, using the train-based differential eddy current sensor system. Six classification algorithms are tested in this study and the best performing model achieved a precision and recall of 96.64% and 95.52% respectively. The results from the study shows that the performance of the machine learning algorithms improved when features from both the driving channels were used simultaneously to represent the fasteners. The best performing algorithm also maintained a good balance between the precision and recall scores during the test stage.
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| 19. |
- Chandran, Praneeth
(författare)
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Train Based Automated Inspection for Railway Fastening System
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Rail transportation is a sustainable mode of transportation and is a key enabler of the socio-economic development of modern society through passenger and freight services. Growth in overall transport demand has led to railways experiencing higher demand on operational capacity, service quality, and safety. However, an increase in traffic and load can lead to an increase in degradation of the components and thus cause a reduction in the infrastructure quality. Such degradation leads to failures of components, consequently resulting in a higher frequency of interventions for maintenance and renewal activities. The downtime arising from such maintenance and renewal of networks is a significant contributor to the delays incurred to the passengers. A plausible solution to attain higher operational capacity and quality of service with the existing infrastructure and minimise delays due to failure would be to inspect the track and its components frequently using in-service trains, operating in regular traffic. One of the crucial components in rail tracks is the rail fastening system, which acts as a means to fix the rails onto the sleeper, upholding the track stability and track gauge. Failures of fasteners can increase wheel flange wear, reduce the safety of train operations, and may lead to derailment due to gage widening or wheel climb. In Sweden, the inspection of track fasteners is mainly carried out either manually by trained inspectors or by using measurement cars. Manual inspections are slow, cost-intensive, labour-intensive, pose safety issues for maintenance personal involved, and are prone to human errors. Inspections based on measurement cars are cost intensive and requires track possession and thus cannot be utilised frequently without compromising the operational capacity. Further, the adverse weather condition, especially in the north of Sweden for the majority of the year, limit regular fastener inspection that depends on such traditional inspection methods. The research presented in this thesis has aimed to find an automated method for fastener inspection that can be carried out using vehicle-mounted measuring equipment operating in regular traffic. Firstly, a study was carried out to determine the effectiveness of automated visual-based solutions for fastener state detection. An anomaly detection model combining image processing techniques and deep learning algorithms was developed to detect the fastener state from rail images captured during the vision-based inspection. The model had a high capability of detecting the fastener state from the rail images. However, the model had difficulties detecting the fastener when there were instances of occlusions of fasteners due to the presence of snow and ballast stones and when the image brightness was low. In Sweden, specifically the northern part of it, the fastening systems are covered under snow for up to six months and thus can inhibit regular fastener inspections that rely on such automated visual inspection methods. To overcome the challenges associated with automated visual inspection systems for fastener state detection, an alternative inspection method using a differential eddy current measurement system was investigated. Controlled field measurements were carried out along a heavy haul railway line in the north of Sweden to determine the effectiveness of the proposed measurement system. An anomaly detection model based on a supervised machine learning algorithm was developed to detect the fastener state from the controlled eddy current measurements. Further, to test the effectiveness of the eddy current sensor during real-time measurements, the proposed sensor system was mounted on an in-service freight train, and measurements were carried out along the iron ore line of Sweden. An anomaly detection model using unsupervised machine learning algorithms was developed to facilitate fastener state detection and detect other anomalies from the real-time measurement data.
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| 20. |
- Chandran, Praneeth, et al.
(författare)
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Train-based differential eddy current sensor system for rail fastener detection
- 2019
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Ingår i: Measurement science and technology. - : Institute of Physics (IOP). - 0957-0233 .- 1361-6501. ; 30:12
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Tidskriftsartikel (refereegranskat)abstract
- One of the crucial components in rail tracks is the rail fastening system, which acts as a means of fixing rails to the sleepers to maintain the track gauge and stability. Manual inspection and 2D visual inspection of fastening systems have predominated over the past two decades. However, both methods have drawbacks when visibility is obscured and are found to be relatively expensive in terms of cost and track possession. The present article presents the concept of a train-based differential eddy current (EC) sensor system for fastener detection. The sensor uses the principle of electromagnetic induction, where an alternating-current-carrying coil is used to create an EC on the rail and other electrically conductive material in the vicinity and a pick-up coil is used to measure the returning field. This paper gives an insight into the theoretical background and application of the proposed differential EC sensor system for the condition monitoring system of rail fasteners and shows experimental results from both laboratory and field measurements. The field measurements were carried out along a heavy-haul railway line in the north of Sweden. Results obtained from both the field measurements and from the lab tests reveal that that the proposed method was able to detect an individual fastening system from a height of 65 mm above the rail. Furthermore, missing clamps within a fastening system are detected by analysing a time domain feature of the measurement signal.
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| 21. |
- Chandran, Praneeth, et al.
(författare)
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Unsupervised Machine Learning for Missing Clamp Detection from an In-Service Train Using Differential Eddy Current Sensor
- 2022
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Ingår i: Sustainability. - : MDPI. - 2071-1050. ; 14:2, s. 1035-1035
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Tidskriftsartikel (refereegranskat)abstract
- The rail fastening system plays a crucial role in railway tracks as it ensures operational safety by fixing the rail on to the sleeper. Early detection of rail fastener system defects is crucial to ensure track safety and to enable maintenance optimization. Fastener inspections are normally conducted either manually by trained maintenance personnel or by using automated 2-D visual inspection methods. Such methods have drawbacks when visibility is limited, and they are also found to be expensive in terms of system maintenance cost and track possession time. In a previous study, the authors proposed a train-based differential eddy current sensor system based on the principle of electromagnetic induction for fastener inspection that could overcome the challenges mentioned above. The detection in the previous study was carried out with the aid of a supervised machine learning algorithm. This study reports the finding of a case study, along a heavy haul line in the north of Sweden, using the same eddy current sensor system mounted on an in-service freight train. In this study, unsupervised machine learning models for detecting and analyzing missing clamps in a fastener system were developed. The differential eddy current measurement system was set to use a driving field frequency of 27 kHz. An anomaly detection model combining isolation forest (IF) and connectivity-based outlier factor (COF) was implemented to detect anomalies from fastener inspection measurements. To group the anomalies into meaningful clusters and to detect missing clamps within the fastening system, an unsupervised clustering based on the DBSCAN algorithm was also implemented. The models were verified by measuring a section of the track for which the track conditions were known. The proposed anomaly detection model had a detection accuracy of 96.79% and also exhibited a high score of sensitivity and specificity. The DBSCAN model was successful in clustering missing clamps, both one and two missing clamps, from a fastening system separately.
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| 22. |
- Famurewa, Stephen Mayowa, et al.
(författare)
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Comparative study of track geometry quality prediction models
- 2013
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Ingår i: 10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013. - 9781629939926 ; , s. 1057-1068
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Konferensbidrag (refereegranskat)abstract
- Track geometry quality is an important aspect in railway engineering as it reflects the actual condition of a track giving account of track geometry deviations. Monitoring and prediction of a relevant geometry quality parameter over time provides opportunity for effective maintenance with advantage of extending the life of the asset, reducing maintenance cost and minimizing possession time requirements. Two important aspects of good maintenance practice relating to track geometry quality are quality assessment of every measurement run for special and common cause of variations and also understanding the progression of the deterioration process. This gives engineering insight into temporal failure phenomena including the behaviour of track structure over time that can facilitate condition forecasting and consequent maintenance planning. This paper presents an approach for assessing track geometry data and also compares three track quality prediction models- linear, exponential and suggested GM(1,1) models. A series of inspection data from a selected line section of Trafikverket (Swedish transport administration) is used in the study. The contribution of this paper is the improvement of prediction accuracy of track geometry model, which is an essential consideration in failure prediction technique.
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| 23. |
- Famurewa, Stephen Mayowa, et al.
(författare)
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Maintenance analysis for continuous improvement of railway infrastructure performance
- 2015
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Ingår i: Structure and Infrastructure Engineering. - : Informa UK Limited. - 1573-2479 .- 1744-8980. ; 11:7, s. 957-969
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Tidskriftsartikel (refereegranskat)abstract
- Railway transport system is massive and complex, and as such it requires effective maintenance to achieve the business goal of safe, economic and sustainable transportation of passengers and goods. The growing demand for improved service quality and capacity target by railway infrastructure managers requires appropriate maintenance analysis to facilitate continuous improvement of infrastructure performance. This paper presents the application of risk matrix as a maintenance analysis method for the identification of track zones that are bottlenecks that limit operational capacity and quality. Furthermore, an adapted analysis method is proposed to create a hierarchical improvement list for addressing the problem of train mission interruption and reduced operational capacity. A case study of a line section of the Swedish network is presented. The result classifies the zones on the line section into different risk categories based on their contribution to loss of capacity and punctuality. In addition, an improvement list for the lower-level system is presented to facilitate maintenance decisions and continuous improvement at both operational and strategic levels.
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| 24. |
- Famurewa, Stephen Mayowa, et al.
(författare)
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Maintenance improvement: an opportunity for railway infrastructure capacity enhancement
- 2013
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Konferensbidrag (refereegranskat)abstract
- The continually increasing demand on railway service in terms of the quantity and quality of both passenger and freight train operations is the core of the general railway capacity challenge. Moreover, this challenge has been the driver for some improvements in the technical system, traffic operation & management as well as maintenance process, although the room for improvement in the maintenance function is still large. An effective capacity management entails critical study of the three essential capacity parameters: infrastructure, traffic and operating parameters. To further explore the fundamentals of capacity management, this paper investigates some essential issues on railway infrastructure capacity. A review of the general railway infrastructure capacity challenge and management is presented, including some strategic measures to enhance capacity and quality of service of existing infrastructure. We have proposed maintenance improvement framework to explore the opportunity of improving the capacity situation on a network. This framework will facilitate the identification of both critical systems and activities with the largest impact on the capacity and also some root causes for critical system. The framework has suggested methodology to improve allocation and utilisation of track possession time, giving room for capacity expansion of existing railway infrastructure.
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| 25. |
- Famurewa, Stephen Mayowa, et al.
(författare)
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Optimisation of maintenance track possession time : A tamping case study
- 2015
-
Ingår i: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit. - : SAGE Publications. - 0954-4097 .- 2041-3017. ; 229:1, s. 42726-
-
Tidskriftsartikel (refereegranskat)abstract
- Optimum allocation and efficient utilisation of track possession time are becoming important topics in railway infrastructure management due to increasing capacity demands. This development and other requirements of modern infrastructure management necessitate the improvement of planning and scheduling of large-scale maintenance activities such as tamping. It is therefore necessary to develop short-, medium- and long-term plans for performing tamping on a network or track section within a definite time horizon. To this end, two key aspects of infrastructure maintenance planning are considered in this paper, deterioration modelling and scheduling optimisation. An exponential deterioration function is applied to model the geometry quality of a series of 200 m segments of a 130 km line section, and an empirical model for recovery after tamping intervention is developed. These two models are subsequently used to generate a methodology to optimise a schedule for tamping intervention by minimising the total cost of intervention including the cost of track possession while geometry quality is ascertained to be within a desirable limit. The modelling considers two types of tamping interventions, preventive and corrective, with different intervention limits and tamping machines. The result of this paper suggests a tamping plan which will lead to optimum allocation of track possession time while maintaining the track geometry quality within specified limits.
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| 26. |
- Famurewa, Stephen Mayowa, et al.
(författare)
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RAM Modelling of Railway Operational Sections : A Case Study from the Iron Ore Line
- 2014
-
Ingår i: Proceedings of the Second International Conference on Railway Technology. - Kippen : Civil-Comp Press. - 9781905088591
-
Konferensbidrag (refereegranskat)abstract
- Railway infrastructure is a linearly distributed asset which has different hierarchical levels such as lines, operational sections, assemblies, modules and maintainable components. The management and performance evaluation of the entire system is done at suitable hierarchical level for efficiency and practicality. It is ideal to assess the integrity as well as the reliability, availability and maintainability (RAM) of the infrastructure on the level of operational sections which are established technical divisions used for traffic operational management by infrastructure administrations. There are several approaches that are used to evaluate the RAM characteristics of a system. This paper presents an approach for RAM simulation of railway operational sections using an event based simulation tool with the Monte Carlo technique. Theinput data used in the RAM modelling includes: historical maintenance and failure data between 2010 and 2012, planned train mission and possible preventive maintenance plans. The outcome of the simulation is the estimation of different RAM parameters over a period of one year. Amongst the parameters are: the expected number of failures and the downtime per operational section, states of each operational section and the overall dependability measure of the line in terms of the success of the planned traffic. These parameters are integrity measures of the asset which can be used for traffic simulation for effective management of traffic. They are also useful for logistic support planning that is required for cost effective and highly dependable infrastructure management.
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| 27. |
- Garmabaki, Amir H. Soleimani, et al.
(författare)
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A Survey on Underground Pipelines and Railway Infrastructure at Cross-Sections
- 2019
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Ingår i: Proceedings of the 29th European Safety and Reliability Conference (ESREL 2019). - Singapore : Research Publishing Services. ; , s. 1094-1101
-
Konferensbidrag (refereegranskat)abstract
- Underground pipelines are an essential part of the transportation infrastructure. The structural deterioration of pipelines crossing railways and their subsequent failures are critical for society and industry resulting in direct and indirect costs for all the related stakeholders. Pipeline failures are complex processes, which are affected by many factors, both static (e.g., pipe material, size, age, and soil type) and dynamic (e.g., traffic load, pressure zone changes, and environmental impacts). These failures have serious impacts on public due to safety, disruption of traffic, inconvenience to society, environmental impacts and shortage of resources. Therefore, continuous and accurate condition assessment is critical for the effective management and maintenance of pipeline networks within transportation infrastructure. The aim of this study is to identify failure modes and consequences related to the crossing of pipelines in railway corridors. Expert opinion have been collected through two set of questionnaires which have been distributed to the 291 municipalities in the whole Sweden. The failure analysis revealed that pipe deformation has higher impact followed by pipe rupture at cross-section with railway infrastructure. For underground pipeline under railway infrastructure, aging and external load gets higher ranks among different potential failure causes to the pipeline.
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| 28. |
- Hossein Nia, Saeed, 1983-
(författare)
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An Investigation of the Iron-Ore Wheel Damages using Vehicle Dynamics Simulation
- 2014
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Maintenance cost is one of the important issues in railway heavy haul operations. For the iron-ore company LKAB, these costs are mainly associated with the reprofiling and changing of the wheels of the locomotives and wagons. The main reason for the wheel damages is usually surface initiated rolling contact fatigue (RCF) on the wheels.The present work tries to enhance and improve the knowledge of the vehicle-track interaction of the Swedish iron-ore freight wagons and locomotives used at Malmbanan. The study is divided into two parts. Firstly, it is tried to get into the roots of RCF using the simulation model of the iron ore wagon (Paper A). Secondly, the study is focused on predicting wear and RCF on the locomotive wheels also via a dynamic simulation model (Paper B).In the first paper, some key issues of the dynamic modelling of the wagons with three piece bogies are first discussed and then parameter studies are carried out to find the most important reasons of wheel damages. These parameter studies include track design geometry, track irregularities, wheel-rail friction level, cant deficiency and track stiffness. The results show a significant effect of the friction level on the amount of RCF risk.As the locomotive wheel life is much shorter than that of the wagons, LKAB has decided to change the locomotive wheel profile. Two final wheel profiles are proposed; however, one had to be approved for the field tests. In the second paper, the long term evolution of the two profiles is compared via wear simulation analysis. Also, the RCF evolution on the wheel profiles as a function of running distance is discussed. The process is first carried out for the current locomotive wheel profiles and the results are compared with the measurements. Good agreement is achieved. Finally, one of the proposed profiles is suggested for the field test because of the mild wear and RCF propagation.
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| 29. |
- Håkansson, Anders, et al.
(författare)
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Patient specific biomodel of the whole aorta - the importance of calcified plaque removal
- 2011
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Ingår i: VASA. - : Hogrefe Publishing Group. - 0301-1526 .- 1664-2872. ; 40:6, s. 453-459
-
Tidskriftsartikel (refereegranskat)abstract
- Background: The use of anatomical models produced by 3D printing technique (rapid prototyping, RP) is gaining increased acceptance as a complementary tool for planning complex surgical interventions. This paper describes a method for creating a patient specific replica of the whole aorta. Methods: Computed tomography angiography (CTA) DICOM-data was converted to a three-dimensional computer aided design-model (CAD) of the inner wall of the aorta representing the lumen where the calcified plaque contribution was removed in a multi-step editing-manoeuvre. The edited CAD-model was used for creating a physical plaster model of the true lumen in a 3D-printer. Elastic and transparent silicon was applied onto the plaster model, which was then removed leaving a silicon replica of the aorta. Results: The median (interquartile range) difference between diameters obtained from CTA- and RP plaster-model at 19 predefined locations was 0.5 mm (1 mm) which corresponds to a relative median difference of 4.6% (7.0%). The average wall thickness of the silicone model was 3.5 mm. The elasticity property and performance during intervention was good with an acceptable transparency. Conclusions: The integration of RP-techniques with CAD based reconstruction of 3D-medical imaging data provides the needed tools for making a truly patient specific replica of the whole aorta with high accuracy. Plaque removal postprocessing is necessary to obtain a true inner wall configuration.
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| 30. |
- Johnsson, Roger, et al.
(författare)
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A new test track for automotive squeak and rattle (S&R) detection
- 2014
-
Ingår i: Applied Acoustics. - : Elsevier BV. - 0003-682X .- 1872-910X. ; 80, s. 79-85
-
Tidskriftsartikel (refereegranskat)abstract
- The perceived quality of interior sounds is of increasing importance in the automotive industry since it is important for the customer perception of vehicle quality. Squeak and rattle (S&R) is a group of intermittent interior noise that reduce the sense of quality dramatically. To identify and solve S&R problems the car manufacturers do both simulations and tests in laboratory of complete vehicles as well as subsystems. As a complement, to laboratory testing and for verification, complete vehicle tests at proving grounds are done. In order to systematically test for vehicle S&R noise at proving grounds there is a need for a new type of test track that in a controlled and repetitive ways excite vehicles at different frequencies. This paper describes such a new test track, called the Frequency Sweep Test Track (FSTT). The test track is based on sweep excitation and improves the precision when detecting and solving S&R issues. Different design considerations such as sweep waveform, frequency range and sweep rate are discussed. The track design is evaluated using a quarter-car model including a tandem ellipsoid tyre model. In a case study a FSTT was built and the excitation of a car was measured. The track excited the expected frequency range and the track operated well in detecting a rattle in the dashboard of an executive production car and at which frequency the rattle occurred.
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| 31. |
- Jönsson, Jens, et al.
(författare)
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Measurement of vertical geometry variations in railway turnouts exposed to different operating conditions
- 2016
-
Ingår i: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit. - : SAGE Publications. - 0954-4097 .- 2041-3017. ; 230:2, s. 486-501
-
Tidskriftsartikel (refereegranskat)abstract
- Turnouts are critical units in a railway system; they perform the switching procedure that allows trains to change between routes. Monitoring the track geometry of a turnout is necessary for maintenance planning and design optimisation. Monitoring is usually done by track recording cars, however, to isolate the ageing and dynamic behaviour of the track it is also necessary to study the unstressed track geometry of the turnouts. Such measurements can be used to develop degradation models to optimise maintenance and design, thereby increasing availability and reducing life cycle cost. This paper introduces a new method to measure the vertical position of the track geometry over time during non-operational conditions (unstressed) to show track degradation. The new method includes a smart system that uses relative measurement reference points to create a better accuracy and lower costs compared with fixed reference points. It evaluates various types of measurement equipment and uses levelling equipment to measure the unstressed vertical geometry of 13 turnouts located on Swedish railway lines, with three follow-up measurements over a year and a half. The turnouts were categorised into four groups: based on their accumulated capacity in million gross tonnes (MGT) and whether they were on a straight or curved main track. Surprisingly, the first three measurements showed the geometry of turnouts on the straight main track to have a vertical elevation tendency towards the mid-section, whereas the turnouts on the curved main track had a general vertical downwards bend tendency towards the mid-section. The results also showed that a higher capacity in MGT has a greater influence on track geometry changes over time.
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| 32. |
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| 33. |
- Lemma, Yonas, et al.
(författare)
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Investigation of the Top-of-Rail Friction by Field Measurements on Swedish Iron Ore Line
- 2015
-
Ingår i: International Journal of COMADEM. - 1363-7681. ; 18:2, s. 17-20
-
Tidskriftsartikel (refereegranskat)abstract
- Friction management in the railway industry is a well-established technology with the aim of optimizing the friction between the wheel and rail. Determining the friction coefficient (μ) at the wheel-rail interface is therefore important especially for heavy haul lines with higher axle loads. This paper presents an initial study of the top-of-rail friction condition of a line with 30 ton axle load, the Iron Ore Line in the northern part of Sweden. The friction coefficient between the rail and the metal wheel of a portable tribometer was measured at different geographical locations and in different environmental conditions. The effects of precipitation are studied and compared with the effects of top-of-rail friction modifiers.The measurements of non-lubricated line sections showed values of μ≈0.6, compared to μ≈0.3 for areas with, for example, top-of- rail lubrication. In snowy conditions a decrease in friction could also be detected.
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| 34. |
- Lemma, Yonas, et al.
(författare)
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Top-of-Rail Friction Measurements of the Swedish Iron Ore Line
- 2014
-
Ingår i: Proceedings of the 3rd international workshop and congress on eMaintenance. - Luleå : Luleå tekniska universitet. - 9789174399721 - 9789174399738 ; , s. 3-7
-
Konferensbidrag (refereegranskat)abstract
- Friction management in the railway industry is a well-establishedtechnology with the aim of optimizing the friction between wheeland rail. Determining the friction coefficient (Q) at the wheel-railinterface is therefore important especially for heavy haul lineswith higher axel loads. This paper presents an initial study of thetop-of-rail friction condition of a 30 ton axel load, Iron Ore line inthe northern part of Sweden. The friction coefficient between therail and a metal wheel of a portable Tribometer was measured atdifferent geographical locations and during differentenvironmental conditions. The effects of precipitation are studiedand compared with the effects of top of rail friction modifiers. Themeasurements of not lubricated line sections showed valuesaround Q 0.6 compared to Q 0.3 for areas with e.g. top-of- raillubrication. During snowy conditions a decrease in friction couldalso be detected.
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| 35. |
- Lundberg, Jan, et al.
(författare)
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Measurements of friction coefficients between rails lubricated with a friction modifier and the wheels of an IORE locomotive during real working conditions
- 2015
-
Ingår i: Wear. - : Elsevier BV. - 0043-1648 .- 1873-2577. ; 324-325, s. 109-117
-
Tidskriftsartikel (refereegranskat)abstract
- The real friction coefficients between the rails and the wheels on a 360. t and 10,800. kW IORE locomotive were measured using the locomotive׳s in-built traction force measurement system. The locomotive consisted of two pair-connected locomotives had a CoCo+CoCo bogie configuration, and hauled a fully loaded set of 68 ore wagons (120. t/wagon). The measurements were performed both on rails in a dry condition and on rails lubricated with a water-based top-of-rail (ToR) friction modifier on the Iron Ore Line between the cities of Kiruna and Narvik in Northern Sweden and Norway, respectively. Since full-scale measurements like these are costly, the friction coefficients were also measured at the same time and place using a conventional hand-operated tribometer, with and without the ToR friction modifier. The most important results are that the real friction coefficient is definitely not constant and is surprisingly low (0.10-0.25) when the ToR friction modifier is used, and that it is also significantly dependent on the amount of ToR friction modifier. A large amount will reduce the friction coefficient. Furthermore, it is concluded that the real friction coefficients are in general lower than the friction coefficients measured with the hand-operated tribometer. A final remark is thus that the use of a water-based ToR friction modifier can give excessively low friction, which can result in unacceptably long braking distances.
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| 36. |
- Main, Kevin, et al.
(författare)
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Aortic rupture after spinal correction for scoliosis in the presence of a thoracic stent graft
- 2010
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Ingår i: Journal of Vascular Surgery. - : Elsevier BV. - 0741-5214 .- 1097-6809. ; 52:6, s. 1653-1657
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Tidskriftsartikel (refereegranskat)abstract
- Corrective surgery for scoliosis often results in a lengthening of the spinal column and relative change of the position of the adjacent anatomical structures such as the aorta. The extent of these anatomical changes could be affected by the presence of a rigid aortic stent graft in the descending thoracic aorta. We present a case of aortic rupture after spinal correction for scoliosis in a 56-year-old female with a thoracic aortic stent graft. Extensive elongation of the aorta with concentration of the stress forces at the lower margin of the stent graft resulted in a weakening of the aortic wall and subsequent rupture.
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| 37. |
- Mishra, Madhav, 1980-, et al.
(författare)
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A Model-based Prognostic Approach to Predict Remaining Useful Life of Components
- 2016
-
Ingår i: Proceedings of 1st International Conference on Maintenance Engineering, IncoME-I, 2016.
-
Konferensbidrag (refereegranskat)abstract
- One of the major problems in the industry is the extension of the useful life of high-performance systems. Proper maintenance plays an important role by extending the useful life, reducing the lifecycle costs and improving the reliability and availability. Health management using a proper condition-based maintenance (CBM) deployment is a worldwide accepted strategy and has grown very popular in many industries over the past decades. A case of CBM is when the maintenance decision is taken based on a forecast of the asset state. This strategy is called predictive maintenance or prognostic health management (PHM). PHM is an engineering discipline that aims to maintain the system behaviour and function, and assure the mission success, safety and effectiveness. This strategy is relevant in environments where the prediction of a failure and the prevention and mitigation of its consequences increase the profit and safety of the facilities concerned. Prognosis is the most critical part of this process and is nowadays recognized as a key feature in maintenance strategies since estimation of the remaining useful life (RUL) is essential.PHM can provide a state assessment of the future health of systems or components, e.g. when a degraded state has been found. The aim of using PHM is to estimate how long it will take before the equipment will reach a failure threshold, in future operating conditions and future environmental conditions.The aim of the paper is to improve the estimation of bearing RUL by dynamically updating the SKF L10 bearing life length calculation. Using a physics-based prognostic approach, the behaviour of a roller in a paper machine was simulated using the finite element method (FEM). A transfer function representing the relation between bearing acceleration and bearing forces was generated and used to convert the acceleration signal into an estimation of the dynamically changing bearing force. The estimated force is then used as input to the bearing life length calculation generating an updated L10 calculation for each time step.
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| 38. |
- Mishra, Madhav, 1980-, et al.
(författare)
-
Bayesian hierarchical model-based prognostics for lithium-ion batteries
- 2018
-
Ingår i: Reliability Engineering & System Safety. - : Elsevier. - 0951-8320 .- 1879-0836. ; 172, s. 25-35
-
Tidskriftsartikel (refereegranskat)abstract
- To optimise operation and maintenance, knowledge of the ability to perform the required functions is vital. The ability is governed by the usage of the system (operational issues) and availability aspects like reliability of different components. This paper proposes a Bayesian hierarchical model (BHM)-based prognostics approach applied to Li-ion batteries, where the goal is to analyse and predict the discharge behaviour of such batteries with variable load profiles and variable amounts of available discharge data. The BHM approach enables inferences for both individual batteries and groups of batteries. Estimates of the hierarchical model parameters and the individual battery parameters are presented, and dependencies on load cycles are inferred. A BHM approach where the operational and reliability aspects end of life (EoD) and end of life (EoL) is studied where its shown that predictions of EoD can be made accurately with a variable amount of battery data. Without access to measurements, e.g. predicting a new battery, the predictions are based only on the prior distributions describing the similarity within the group of batteries and their dependency on the load cycle. A discharge cycle dependency can also be identified in the result giving the opportunity to predict the battery reliability.
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| 39. |
- Mishra, Madhav, 1980-, et al.
(författare)
-
Bearing Life Prediction with Informed Hyperprior Distribution: A Bayesian Hierarchical and Machine Learning Approach
- 2021
-
Ingår i: IEEE Access. - : IEEE Robotics and Automation Society. - 2169-3536. ; 9, s. 157002-157011
-
Tidskriftsartikel (refereegranskat)abstract
- A Bayesian hierarchical model (BHM) is developed to predict bearing life using envelope acceleration data in combination with a degradation model and prior knowledge of the bearing rating life. The BHM enables the inference of individual bearings, groups of bearings, or bearings operating under certain conditions. The key benefit of the BHM approach is that the relationships between the bearing model parameters and their prior distributions can be expressed at different hierarchical levels. We begin our analysis using a bearing rating life calculation L10h and an estimate of its associated failure time distribution. Realistic variations to constrain our prior distribution of the failure time are then applied before measurements are available. When data become available, estimates more representative of our specific batch and operating conditions are inferred, both on the individual bearing level and the bearing group level. The proposed prognostics methodology can be used in situations with varying amounts of data. The presented BHM approach can also be used to predict the remaining useful life (RUL) of bearings both in situations in which the bearing is considered to be in a healthy state and in situations after a defect has been detected.
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| 40. |
- Mishra, Madhav, 1980-, et al.
(författare)
-
Hierarchical model-based prognostics for Li-ion batteries
- 2018
-
Ingår i: Advances In Engineering. - Ontario, CANADA : Advances In Engineering.
-
Tidskriftsartikel (populärvet., debatt m.m.)abstract
- Recent global trend towards a fossil-fuel-free society has yielded the rapid soar in demand of electrically powered systems. Specifically, the demand for battery powered systems has fueled the desire to have better performing batteries with lithium-ion batteries being the most widely used. Presently, for application in unmanned vehicles, exploratory rovers, submarines among others demand a better comprehension of battery performance metrics. Case and point, battery capacity and state of charge have become increasingly vital when it comes to determining the end of discharge. As of now, several techniques have already been established for determining such parameters. Unfortunately, their prognostic capability for determining remaining battery charge is still not optimal. Therefore, there is a need to develop prognostic and health management technology for critical systems (such as Mars rovers) to successfully predict and manage the lifetime of batteries, monitor their health state in real time, evaluate the performance and predict the remaining useful life.To this note, Luleå University of Technology researchers in Sweden: Dr. Madhav Mishra, Dr. Jesper Martinsson, and Dr. Matti Rantatalo in collaboration with Dr. Kai Goebel at NASA in the United States proposed a study whose main objective was to measure the battery discharge and predict the end of discharge considering the operating conditions for lithium ion batteries. To be precise, they purposed on employing a Bayesian Hierarchical Model (BHM)-based end of discharge prognostic for Li-ion batteries. Their work is currently published in the research journal, Reliability Engineering and System Safety.The research technique employed entailed the utilization of two batteries with 16 discharge events with a simplified battery circuit model of the battery. Next, the research team examined the detailed discharge voltage profiles during different discharging cycles with variable load profiles. They then proceeded to demonstrate the BHM approach and group-level dependencies by utilizing more than one battery and more than one discharge cycle.The authors observed that the BHM approach enabled inferences for both individual batteries and groups of batteries. The researchers then recorded the estimates of the hierarchical model parameters and the individual battery parameters after which their dependencies on load cycles were inferred. In addition, they noted that by using the BHM approach the predictions of end of discharge could be made accurately with a variable amount of battery data. Furthermore, this technique was seen to applicable even for new batteries without prior recorded data where the predictions were based only on the prior distributions describing the similarity within the group of batteries and their dependency on the load cycle.In conclusion, the study presented a Bayesian hierarchical model (BHM)-based prognostics approach for Li-ion batteries, where the goal was to analyze and predict the discharge behavior of such batteries with variable load profiles and variable amounts of available discharge data. The results obtained showed that the technique could address cases with or without data. Altogether, the proposed method can capture additional relationships between parameters and use it to improve prognostics. Lastly, the BHM approach has been seen to permit inference at both the individual battery level and group of battery level.
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| 41. |
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| 42. |
- Mishra, Madhav, et al.
(författare)
-
Particle filter-based prognostic approach for railway track geometry
- 2017
-
Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 96, s. 226-238
-
Tidskriftsartikel (refereegranskat)abstract
- Track degradation of ballasted railway track systems has to be measured on a regular basis, and these tracks must be maintained by tamping. Tamping aims to restore the geometry to its original shape to ensure an efficient, comfortable and safe transportation system. To minimize the disturbance introduced by tamping, this action has to be planned in advance. Track degradation forecasts derived from regression methods are used to predict when the standard deviation of a specific track section will exceed a predefined maintenance or safety limit. This paper proposes a particle filter-based prognostic approach for railway track degradation; this approach is demonstrated by examining different railway switches. The standard deviation of the longitudinal track degradation is studied, and forecasts of the maintenance limit intersection are derived. The particle filter-based prognostic results are compared with the standard regression method results for four railway switches, and the particle filter method shows similar or better result for the four cases. For longer prediction times, the error of the proposed method is equal to or smaller than that of the regression method. The main advantage of the particle filter-based prognostic approach is its ability to generate a probabilistic result based on input parameters with uncertainties. The distributions of the input parameters propagate through the filter, and the remaining useful life is presented using a particle distribution.
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| 43. |
- Mishra, Madhav, 1980-
(författare)
-
Prognostics and Health Management of Engineering Systems for Operation and Maintenance Optimisation
- 2018
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Prognostics and health management (PHM) is an engineering discipline that aims to maintain system behaviour and function and ensure mission success, safety and effectiveness. Prognostics is defined as the estimation of remaining useful life. It is the most critical part of this process and is a key feature of maintenance strategies since the estimation of the remaining useful life (RUL) is essential to avoiding unscheduled maintenance. Prognostics is relatively immature compared to diagnostics, and a challenging task facing the research community is to overcome some of the major barriers to the application of PHM technologies to real-world industrial systems. This thesis presents research into methods for addressing these challenges for industrial applications. The thesis work focuses on prognostic approaches for three different engineering systems with different characteristics in terms of the prognostics of operation and maintenance aspects. The aim of this thesis is to facilitate better operation and maintenance decision making. The main benefits of prognostics are in anticipating future failures to increase uptime, implementing dynamic maintenance planning toward decreasing total costs and decreasing energy consumption. Therefore, there is a need for methods that can be used in these cases to classify the health states and predict the remaining useful life of assets. The studied engineered systems in this thesis are railway tracks, batteries and rolling element bearings.In a railway system, the track geometry has to be maintained to provide a safe and functional track. Therefore, track degradation of ballasted railway track systems has to be measured on a regular basis to determine when to maintain the track by tamping. Tamping aims to restore the geometry to its original state to ensure an efficient, comfortable and safe transportation system. To minimise the disruption introduced by tamping, this action has to be planned in advance. Track degradation forecasts derived from regression methods are used to predict when the standard deviation of a specific track section will exceed a predefined maintenance or safety limit. In this thesis, a particle-filter-based prognostic approach for railway track degradation for railway switches is proposed. The particle-filter-based prognostic will generate a probabilistic prediction result that can facilitate risk-based decision making.Li-ion batteries are another important components in engineering system and battery life prediction matters. Li-ion batteries are commonly used in a wide range of consumer electronic devices, electric vehicles of all types, military electronics, maritime applications, astronaut suits, and space systems. Many critical operations depend on such batteries as a reliable power source. It is therefore important for the user to get an accurate estimate of the battery end of discharge because an unforeseen discharge of a battery could have catastrophic consequences. To address this issue, a Bayesian hierarchical model (BHM)-based prognostics approach was applied to Li-ion batteries, where the goal was to analyse and predict the discharge behaviour of such batteries with variable load profiles and variable amounts of available discharge data. The BHM approach enables inferences for both individual batteries and groups of batteries. Estimates of the hierarchical model parameters and the individual battery parameters are presented, and dependencies on load cycles are inferred. The operational and reliability aspects, end of life (EoD) and end of life (EoL), are studied; it is shown that predictions of the EoD can be made accurately with a variable amount of battery data. Without access to measurements, e.g., predicting performance of a new battery, the predictions are based only on the prior distributions describing the similarity within a group of batteries and their dependency on the load cycle. A discharge cycle dependency is identified helping with estimation of battery reliability.Batteries have become a very important engineering system, rotating machines have played an important role, possibly the most important role, in the field of engineering. They have been used to drive the industrialisation of the world.For rotating machinery, rolling element bearings are a vital component and have several failure modes. Hence, there is significant need to monitor the health of bearings and detect degraded states and upcoming failures as early as possible to avoid serious accidents and equipment failure. For rolling element bearings, an investigation in using FEM models for estimating bearing forces from acceleration measurements was conducted. This study was performed at a paper mill where a bearing monitoring system was installed. The purpose of the study was to feed the bearing rating life L10 (a bearing life length calculation) with estimations of the dynamic bearing forces to continuously update the L10 calculation by generating a dynamic L10. In a second study for bearing lifetime prediction, a Bayesian hierarchical modelling (BHM) approach , which includes different data sources, such as enveloped acceleration data, in combination with degradation models and prior distributions of other parameters, was developed, in which the bearing rating life calculation can be included. The proposed prognostics methodology can be used in cases where there is less or noisy data. The above approach can even be used in cases whereby there is no prior knowledge of the system or little measurement data on the conditions. The presented BHM approach can also be used to predict the remaining useful life (RUL) of bearings both in situations in which the bearing is considered to be in a healthy state and in situations after a defect has been detected.
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| 44. |
- Mishra, Madhav, et al.
(författare)
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Simulations and Measurements of the Dynamic Response of a Paper Machine Roller
- 2015
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Konferensbidrag (refereegranskat)abstract
- The paper industry is a highly automated industry that includes many different production steps where a variety of machine components are used. In the paper machine where the pulp is being transformed into paper, rotating components like bearing mounted rollers play an important part to drive the wire with the pulp through the process. In this type of industry with a serial layout, the failure of a single roller or bearing could lead to stoppage of several production steps with costly consequences as a result. To ensure and optimize the asset availability, a condition based maintenance (CBM) strategy could be implemented. However, CBM is dependent on an appropriate condition monitoring (CM) technique to detect physical phenomenon that defines the state of critical components or systems. For the development of CM techniques, it is therefore important to understand and model the physical behaviour of the system in question. In this paper the behaviour of a roller in a paper machine is analysed using finite element method (FEM). The physical model was compared with vibration measurements collected from an online monitoring system and an experimental modal analysis.
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| 45. |
- Mishra, Madhav, et al.
(författare)
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Simulations and measurements of the dynamic response of a paper machine roller
- 2016
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Ingår i: Insight. - : British Institute of Non-Destructive Testing (BINDT). - 1354-2575 .- 1754-4904. ; 58:4, s. 210-212
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Tidskriftsartikel (refereegranskat)abstract
- The paper industry is a highly automated industry that includes many different production steps, in which a variety of machine components are used. In a paper machine, where the pulp is being transformed into paper, rotating components such as bearing-mounted rollers play an important part in driving the wire with the pulp through the process. In this type of industry with a serial layout, the failure of a single roller or bearing could lead to the stoppage of several production steps, with costly consequences as a result. To ensure and optimise asset availability, a condition-based maintenance (CBM) strategy could be implemented. However, CBM is dependent on an appropriate condition monitoring (CM) technique to detect a physical phenomenon that defines the state of critical components or systems. For the development of CM techniques, it is therefore important to understand and model the physical behaviour of the system in question. In this paper, the behaviour of a roller in a paper machine is analysed using the finite element method (FEM). The physical model was compared with vibration measurements collected from an online monitoring system and an experimental modal analysis.
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| 46. |
- Mohammed, Omar D., et al.
(författare)
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Analytical crack propagation scenario for gear teeth and time-varying gear mesh stiffness
- 2012
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Konferensbidrag (refereegranskat)abstract
- In this paper an analytical crack propagation scenario is proposed which assumes that a crack propagates in the tooth root in both the crack depth direction and the tooth width direction, and which is more reasonable and realistic for non-uniform load distribution cases than the other presented scenarios. An analytical approach is used for quantifying the loss of time-varying gear mesh stiffness with the presence of crack propagation in the gear tooth root. The proposed crack propagation scenario can be applied for crack propagation modelling and monitoring simulation, but further research is required for comparison and evaluation of all the presented crack propagation scenarios from the condition monitoring point of view.
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| 47. |
- Mohammed, Omar D., et al.
(författare)
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Dynamic modelling of a one-stage spur gear system and vibration-based tooth crack detection analysis
- 2015
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Ingår i: Mechanical systems and signal processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 54:1, s. 293-305
-
Tidskriftsartikel (refereegranskat)abstract
- For the purpose of simulation and vibration-based condition monitoring of a geared system, it is important to model the system with an appropriate number of degrees of freedom (DOF). In earlier papers several models were suggested and it is therefore of interest to evaluate their limitations. In the present study a 12 DOF gear dynamic model including a gyroscopic effect was developed and the equations of motions were derived. A one-stage reduction gear was modelled using three different dynamic models (with 6, 8 and 8 reduced to 6 DOF), as well as thedeveloped model (with 12 DOF), which is referred as the fourth model in this paper. The time-varying mesh stiffness was calculated, and dynamic simulation was then performed for different crack sizes. Time domain scalar indicators (the RMS, kurtosis and the crest factor) were applied for fault detection analysis. The results of the first model showa clearly visible difference from those of the other studied models, which were made more realistic by including two more DOF to describe the motor and load. Both the symmetric and the asymmetric disc cases were studied using the fourth model. In the case of disc symmetry, the results of the obtained response are close to those obtained from both the second and third models. Furthermore, the second model showed a slight influence from inter-tooth friction, andtherefore the third model is adequate for simulating the pinion’s y-displacement in the case of the symmetric disc. In the case of the asymmetric disc, the results deviate from those obtained in the symmetric case. Therefore, for simulating the pinion’s y-displacement, the fourth model can be considered for more accurate modelling in the case of the asymmetric disc.
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| 48. |
- Mohammed, Omar D., et al.
(författare)
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Dynamic modelling of gear system with gyroscopic effect and crack detection analysis
- 2015
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Ingår i: Proceedings of the 9th IFToMM International Conference on Rotor Dynamics. - Cham : Encyclopedia of Global Archaeology/Springer Verlag. - 9783319065892 - 9783319065908 ; , s. 1303-1314
-
Konferensbidrag (refereegranskat)abstract
- In this paper a 12 DOF gear dynamic model was developed and the equations of motions were derived. A one-stage reduction gear was modelled with gyroscopic effect of the gear disc, and both cases of symmetric and asymmetric disc were studied. Gear mesh stiffness was calculated for different crack sizes, and dynamic response was simulated. Time domain scalar indicators (the RMS, kurtosis and the crest factor) were applied for fault detection analysis. In the case of asymmetric disc the simulation shows results that are different from those obtained in the symmetric case. The coupling terms have an effect on the obtained pinion’s displacement which is studied for fault detection analysis. Therefore, for simulating the pinion’s displacement, this model can be considered for more accurate modelling in case of asymmetric disc.
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| 49. |
- Mohammed, Omar D., et al.
(författare)
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Dynamic Response and Time-Frequency Analysis for Gear Tooth Crack Detection
- 2016
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Ingår i: Mechanical systems and signal processing. - : Elsevier BV. - 0888-3270 .- 1096-1216. ; 66-67, s. 612-624
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Tidskriftsartikel (refereegranskat)abstract
- Vibration health monitoring is a non-destructive technique which can be applied to detect cracks propagating in gear teeth. This paper studies gear tooth crack detection by investigating the natural frequencies and by performing time-frequency analysis of a 6 DOF dynamic gear model. The gear mesh stiffness used in the model was calculated analytically for different cases of crack sizes. The frequency response functions (FRFs) of the model were derived for healthy and faulty cases and dynamic simulation was performed to obtain the time signal responses. A new approach involving a short-time Fourier transform (STFT) was applied where a fast Fourier transform (FFT) was calculated for successive blocks with different sizes corresponding to the time segments of the varying gear mesh stiffness. The relationship between the different crack sizes and the mesh-stiffness-dependent eigenfrequencies was studied in order to detect the tooth crack and to estimate its size.
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| 50. |
- Mohammed, Omar D., et al.
(författare)
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Gear fault models and dynamics-based modelling for gear fault detection : A review
- 2020
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Ingår i: Engineering Failure Analysis. - : Elsevier. - 1350-6307 .- 1873-1961. ; 117
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Forskningsöversikt (refereegranskat)abstract
- The main purpose of condition monitoring in gear systems is to facilitate condition-based maintenance (CBM) by detecting the degradation of components, e.g. gear teeth, before the occurrence of a failure which could result in a malfunction of the whole gearing system and a reduction of the system availability. The role of vibration-based condition monitoring is to detect any change in the dynamic response related to changes in the structural integrity or the excitation forces. The early detection of a degraded gear allows a properly scheduled shutdown, which could prevent catastrophic failures with cascading effects and consequently result in safer operation and a reduced maintenance cost. The current article reviews the methods applied for gear tooth fault detection using vibration analysis, with an emphasis on tooth fault modelling and dynamic simulation. The article concludes with a brief discussion of the methods and models that have been used during the past few decades.
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