| 1. |
- Hoang, M. L., et al.
(författare)
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A New Technique for Optimization of Linear Displacement Measurement based on MEMS Accelerometer
- 2020
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Ingår i: Proceedings. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728110738 ; , s. 155-158
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Konferensbidrag (refereegranskat)abstract
- Linear displacement has been widely applied in the technology and applications for Industry 4.0. The Micro-electromechanical systems (MEMS) accelerometer is a potential candidate in linear displacement measurement by means of acceleration acquisition. However, the error still presents on the displacement measurement at the starting point or each time the sensor ends its motion and returns to a static state due to the noise and imperfection of mechanical structure. The paper presents a new algorithm, 'No Displacement Zero Translational Accumulation' (NDZTA), to solve the cumulative error of linear measurement when the sensor stays at stationary points. The proposed filter removes noise by pulling down the current velocity and acceleration to 0 immediately when the sensor finishes its motion. Moreover, a simple but practical way to calculate the displacement via the 'Area Integration Method' was visualized and analyzed in detail. The experimental result shows a good accuracy as well as stability of measured result with the maximum error only about 0.2 cm in the range of 200 cm. © 2020 IEEE.
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| 2. |
- Koyazo, J. T., et al.
(författare)
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Collaborative systems for telemedicine diagnosis accuracy
- 2021
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Ingår i: Acta IMEKO. - : International Measurement Confederation (IMEKO). - 0237-028X. ; 10:3, s. 192-197
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Tidskriftsartikel (refereegranskat)abstract
- The transmission of medical data and the possibility for distant healthcare structures to share experiments about a given medical case raises several conceptual and technical questions. Good remote healthcare monitoring deals with more problems in personalized heath data processing compared to the traditional methods nowadays used in several parts of hospitals in the world. The adoption of telemedicine in the healthcare sector has significantly changed medical collaboration. However, to provide good telemedicine services through new technologies such as cloud computing, cloud storage, and so on, a suitable and adaptable framework should be designed. Moreover, in the chain of medical information exchange, between requesting agencies, including physicians, a secure and collaborative platform enhanced the decision-making process. This paper provides an in-depth literature review on the interaction that telemedicine has with cloud-based computing. On the other hand, the paper proposes a framework that can allow various research organizations, healthcare sectors, and government agencies to log data, develop collaborative analysis, and support decision-making. The electrocardiogram (ECG) and electroencephalogram EEG case studies demonstrate the benefit of the proposed approach in data reduction and high-fidelity signal processing to a local level; this can make possible the extracted characteristic features to be communicated to the cloud database. © 2021 International Measurement Confederation (IMEKO). All rights reserved.
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| 3. |
- Ugwiri, M. A., et al.
(författare)
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Cascade based methods in detecting rotating faults using vibration measurements
- 2021
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Ingår i: Conference Record - IEEE Instrumentation and Measurement Technology Conference. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728195391
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Konferensbidrag (refereegranskat)abstract
- In the paper, the pursued objective is to take advantage of two main relevant cascade methods, namely Ensemble Empirical Mode Decomposition (EEMD) and Discrete Wavelet Transform (DWT), for the improvement of the sensitivity of scalar indicators such as Kurtosis (Kurt) and Crest Factor (CF) within the application of condition monitoring by vibration analysis on electric machines. The measurements were possible thanks to the piezoelectric sensors, where the signals were recorded from the machine's critical and judiciously chosen points. The paper demonstrates that when the motor runs under faulty conditions, it is possible to notice the appearance of spallings, which cause the signal to be disturbed and consequently modify the distribution (which is of Gaussian kind in a flawless situation). Nevertheless, those impulse excitations can have a tremendous effect on the values of time-domain indicators. The paper proposes two powerful denoising methods, discussed in-depth the effectiveness of each technique. The conclusion drawn from the analysis shows that the approach improves the sensitivity of selected indicators and therefore increases their reliability for fault presence detection. © 2021 IEEE.
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| 4. |
- Ugwiri, M. A., et al.
(författare)
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Vibrations measurement and current signatures for fault detection in asynchronous motor
- 2020
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Ingår i: Proceedings. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728144603
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Konferensbidrag (refereegranskat)abstract
- In most industrial applications, Fault Detection (FD) is an important function. Understanding equipment's conditions help engineers and operators avoiding the inevitable catastrophe that could lead to a significate impact on system reliability and safety. For electromechanical devices such as asynchronous motors, which play an essential role in production lines, mastering vibrations for Fault Detection is interesting. Downtime, costly maintenance, and energy waste are damages resulting from faults. The paper presents an overview of different techniques used in asynchronous motors fault detection. Vibrations signals processing and techniques for extracting characteristic features from them are largely developed. Spectrum analysis of the envelope signal is employed to process vibration signals resulting from rolling bearings. The paper also proposes rotors broken bars detection using Park Transformation. It was shown that Park's transformation is an effective tool to detect broken bars even at the incipient stage, which gives to it the merit to be a complementary technique to vibration analysis. © 2020 IEEE.
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| 5. |
- Lay-Ekuakille, A., et al.
(författare)
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Medical image measurement and characterization : Extracting mechanical and thermal stresses for surgery
- 2021
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Ingår i: Metrology and Measurement Systems. - : Polska Akademia Nauk. - 0860-8229. ; 28:1, s. 3-21
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Tidskriftsartikel (refereegranskat)abstract
- Whatever the type of surgery related to inner organs, traditional or robotic, the contact with them during surgery is a key moment for pursuing the intervention. Contacts by means of surgery instruments namely scalpels, staples, clamps, graspers, etc. are decisive moments. False, and erroneous touching and manoeuvring of organs operated on can cause irreversible damage as regard morphological aspects (outer impact) and physiological aspects (inner impact). The topic is a great challenge in the effort to measure and characterize damages. In general, electrical instruments for surgery employ the following technologies: Ultrasound, radiofrequency (monopolar, and bipolar), and laser. They all result in thermal damages difficult to evaluate. The article proposes a method for a pre-screening of organ features during robotic surgery sessions by pointing out mechanical and thermal stresses. A dedicated modelling has been developed based on experimental activities during surgery session. The idea is to model tissue behaviour from real images to help surgeons to be aware of handling during surgery. This is the first step for generalization by considering the type of organ. The measurement acquisitions have been performed by means of an advanced external camera located over the surgery quadrant. The modelling and testing have been carried out on kidneys. The modelling, carried out through Comsol Multiphysics, is based on the bioheat approach. A further comparative technique has been implemented. It is based on computer vision for robotics. The findings of human tissue behavior exhibit reliable results. © 2021. The Author(s).
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| 6. |
- Ugwiri, M. A., et al.
(författare)
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Edge sensor signal processing algorithms for earthquake early detection
- 2020
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Ingår i: Proceedings. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728144603
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Konferensbidrag (refereegranskat)abstract
- A new earthquake early warning algorithm is proposed in this paper. Intelligent sampling technique is used to expose signal information in a way to facilitate the inference of knowledge. The goal is to assess, by observing the first few seconds of P-wave, whether the incoming earthquake is destructive or not, and to generate an alert or eventually take action. Once the proposed method has been developed, performance results obtained using real seismic data from open-access databases are presented, thereby validating the effectiveness of the proposed method in estimating seismic magnitude. Since real-time and device interoperability are critical aspects in applications such as seismic detection, the suitability and compatibility of the proposed method with the IEEE1451 family of standards are demonstrated. © 2020 IEEE.
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| 7. |
- Capriglione, D., et al.
(författare)
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Design and Implementation of a Diagnostic Scheme for Stroke Sensors in Motorcycle Semi-active Suspension Systems
- 2020
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Ingår i: Lect. Notes Electr. Eng.. - Cham : Springer. - 9783030375577 ; , s. 335-341
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Konferensbidrag (refereegranskat)abstract
- Today the reliability of electronic systems strictly depends on the correct operations of the sensor involved in the normal use. This fact is more evident in applications where the security and safety of end-users are involved, reason why a suitable Instrument Fault Detection Scheme (IFD) including also Isolation feature (IFDI) becomes fundamental. The automotive field is one of the main areas where an IFDI scheme is mandatory. As an example, systems designed to on-line adapt and to electronically control the suspensions of motorcycles are today of great interest for motorcycle and after-market manufacturers. By the way meanwhile semi-active suspension systems can drastically improve the comfort and the traction performance of motorcycle, a promptness detection of faults involving this kind of system is fundamental for the safety and performance of the motorcycle. With this aim, the paper proposes an Instrument Fault Detection and Isolation (IFDI) scheme using analytical redundancy for the fault diagnosis of the front and rear stroke suspension sensors. Both suitable mathematical links and soft sensors based on artificial neural networks are proposed for the residuals generation in order to design and validate the proposed IFDI scheme. © 2020, Springer Nature Switzerland AG.
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| 8. |
- Lay-Ekuakille, A., et al.
(författare)
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SAR sensors measurements for environmental classification : Machine learning-based performances
- 2020
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Ingår i: IEEE Instrumentation & Measurement Magazine. - : Institute of Electrical and Electronics Engineers Inc.. - 1094-6969 .- 1941-0123. ; 23:6, s. 23-30
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Tidskriftsartikel (refereegranskat)abstract
- Artificial intelligence, in particular a supervised and unsupervised machine learning approach, has been becoming an interest in the field of measurement and instrumentation. Many problems of classification can be faced by a machine learning approach. We know machine learning is a broad area of artificial intelligence that comprises some other lines of research and activities such as deep learning. Synthetic aperture radar (SAR) measurements by means of its sensors are of great interest in environmental monitoring, in particular in land classification. This paper presents findings related to measurements and characterization through land classification of an environmentally sensitive area in Italy over two different time periods in order to assess changing parameters. A deep learning algorithm has been designed and implemented, and a comparison has been established with a spectral density approach.
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| 9. |
- Ugwiri, M. A., et al.
(författare)
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Spectral negentropy and kurtogram performance comparison for bearing fault diagnosis
- 2020
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Ingår i: Proceedings. - : International Measurement Confederation (IMEKO). ; , s. 105-110
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Konferensbidrag (refereegranskat)abstract
- While investigating rotating faults in vibration signals, one of the typical symptoms is the presence of repetitive transients, which are characterized by impulsive and cyclostationarity signature. The approach quite popular nowadays in the industry for their detection is time-frequency techniques. Those techniques are mainly analysis tools as opposed to processing tools, and in any case, are unable to offer a versatile methodology that applies to all mechanical signals in all circumstances. The paper is motivated by ideas borrowed from thermodynamics, where transients are seen as departures from a state of equilibrium; it is proposed to measure the negentropy of the squared envelope (SE) and the squared envelope spectrum (SES) of the signal. The main objective of the work is to investigate connections in both negentropy and kurtogram approaches to capture the signature of this repetitive behavior. The methodology used in this paper proposes to display spectral negentropy as images. The impulsive events are then detected and localized in frequency by high values of the squared envelope spectrum (SES) infogram in some frequency bands. In order to analyze the signal in the frequency domain, the Short-Time Fourier Transform (STFT) can then be used. The STFT is suggested in this study due to its simplicity and high flexibility. On the other hand, STFT is used for the analysis of kurtosis of temporal signals; this is well known as Kurtogram. For fault, such as bearings, Kurtogram was demonstrated to be efficient.
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