| 1. |
- 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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| 2. |
- 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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| 3. |
- 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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| 4. |
- Kanoni, Stavroula, et al.
(författare)
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Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.
- 2022
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Ingår i: Genome biology. - : Springer Science and Business Media LLC. - 1474-760X .- 1465-6906 .- 1474-7596. ; 23:1
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Tidskriftsartikel (refereegranskat)abstract
- Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N=1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
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| 5. |
- Rantatalo, Matti, et al.
(författare)
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Evaluation of Measurement Strategy for Track Side Monitoring of Railway Wheels
- 2023
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Ingår i: Applied Sciences. - : MDPI. - 2076-3417. ; 13:9
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Tidskriftsartikel (refereegranskat)abstract
- Wheelsets form an indispensable part of the railway rolling stock and need to be periodically inspected to ensure stable, safe, reliable, and sustainable rail operation. Wheel profiles are usually inspected and measured in a workshop environment using handheld equipment or by utilizing wayside measuring equipment. A common practice for both methods is to measure the wheel profile at one position along the circumference of the wheel, resulting in a one-slice measurement strategy, based on the assumption that the wheel profile has the same shape independent of the measurement position along the wheel. In this article, the representability of a one-slice measurement strategy with respect to the wheel profile parameters is investigated using handheld measurement equipment. The calculated range of standard deviation of the parameters estimated such as flange height, flange width, flange slope, and hollow wear from the measurements shows a spread in the parameter value along the circumference of the wheel. As an initial validation of the results, measurements from the wayside monitoring systems were also investigated to see if a similar spread was visible. The spread was significantly higher for flange height, flange width, and flange slope estimated from wayside measurement equipment than for the same parameters estimated using the handheld measurement equipment.
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| 6. |
- Rondon, David, 1986-
(författare)
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Dynamic Modeling of Hydropower Generators
- 2022
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Modeling the dynamics of hydropower generators has been the aim pursued by many studies, as providing a reliable model would lead to more cost-effective designs. Hydropower generators comprise many parts, tilting-pad bearings, shaft, rotor rim, and stator among them, that contribute to the system's nonlinearities. In this thesis, the dynamics of hydropower generator is studied first by characterizing tilting-pad bearings. Multiple pad bearings are common in the industry; an eight-pad tilting-pad bearing has been studied on vertical rotors. Previous studies have shown that multiple pad bearings display stiffness and damping coefficients dependent on eccentricity and position. A model for eight-pad tilting pad bearings has been proposed and compared to experiments. The effect of cross-coupled phenomena was also investigated.On the other hand, the generators are not rigid bodies, and the flexibility of either rotor rim or stator influences the distribution of the magnetic field, thus the force distribution. An uneven force distribution endangers the integrity of the machine. This thesis also proposes a model for a generator with flexible rotor rims and rigid stators using Lagrange equations, considering the centrifugal and Coriolis effects, the electromagnetic interaction between rotor and stator, and static and dynamic eccentricities. This model was tried on a generator prototype, discussing the impact of the connecting plates and the magnetic forces on the natural frequencies and the effect of static eccentricity.
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| 7. |
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| 8. |
- Talebiahooie, Elahe, et al.
(författare)
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Modelling of Railway Sleeper Settlement under Cyclic Loading Using a Hysteretic Ballast Contact Model
- 2021
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Ingår i: Sustainability. - : MDPI. - 2071-1050. ; 13:21
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Tidskriftsartikel (refereegranskat)abstract
- Ballasted tracks are common in the railway system as a means of providing the necessary support for the sleepers and the rails. To keep them operational, tamping and other maintenance actions are performed based on track geometry measurements. Ballast particle rearrangement, which is caused by train load, is one of the most important factors leading to track degradation. As a result, when planning maintenance, it is vital to predict the behaviour of the ballast under cyclic loading. Since ballast is a granular matter with a nonlinear and discontinuous mechanical behaviour, the discrete element method (DEM) was used in this paper to model the ballast particle rearrangement under cyclic loading. We studied the performance of linear and nonlinear models in simulating the settlement of the sleeper, the lateral deformation of the ballast shoulder and the porosity changes under the sleeper. The models were evaluated based on their ability to mimic the ballast degradation pattern in vertical and lateral direction. The linear contact model and the hysteretic contact model were used in the simulations, and the effect of the friction coefficient and different damping models on the simulations was assessed. An outcome of this study was that a nonlinear model was proposed in which both the linear and the hysteretic contact models are combined. The simulation of the sleeper settlement and the changes in the porosity under the sleeper improved in the proposed nonlinear model, while the computation time required for the proposed model decreased compared to that required for the linear model.
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| 9. |
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| 10. |
- Thiery, Florian, et al.
(författare)
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Dynamics of a Jeffcott rotor with rigid blades rubbing against an outer ring
- 2012
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Ingår i: Chaotic Modeling and Simulation (CMSIM). - 2241-0503. ; , s. 643-650
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- The non-linear behaviour of rub-impact systems have been studied recentlyby approximating rotor-stator systems as rubbing cylinders. In reality, therotor shape is more complex, resulting in richer dynamics over smaller parameter ranges. In this paper, a bladed turbine is modelled using a Jeffcott rotor with three rigid beams attached to the mass center. The contact forces are described by a radial restoring force induced by the massless outer ring, and a tangential Coulomb frictional force. The results are presented in bifurcation diagrams and compared with a previous model described by three flexible beams entering in contact with a fixed ring assuming large displacement beam theory. This paper shows that the two models described give similarities in the overall bifurcation diagram, only showing greater differences in localized frequency ranges.
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