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  • Open Access

    ARTICLE

    A Convolutional Autoencoder Based Fault Detection Method for Metro Railway Turnout

    Chen Chen1,2, Xingqiu Li2,3,*, Kai Huang4, Zhongwei Xu1, Meng Mei1

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 471-485, 2023, DOI:10.32604/cmes.2023.024033

    Abstract Railway turnout is one of the critical equipment of Switch & Crossing (S&C) Systems in railway, related to the train’s safety and operation efficiency. With the advancement of intelligent sensors, data-driven fault detection technology for railway turnout has become an important research topic. However, little research in the literature has investigated the capability of data-driven fault detection technology for metro railway turnout. This paper presents a convolutional autoencoder-based fault detection method for the metro railway turnout considering human field inspection scenarios. First, the one-dimensional original time-series signal is converted into a two-dimensional image by data pre-processing and 2D representation. Next,… More >

  • Open Access

    ARTICLE

    Method for Fault Diagnosis and Speed Control of PMSM

    Smarajit Ghosh*

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2391-2404, 2023, DOI:10.32604/csse.2023.028931

    Abstract In the field of fault tolerance estimation, the increasing attention in electrical motors is the fault detection and diagnosis. The tasks performed by these machines are progressively complex and the enhancements are likewise looked for in the field of fault diagnosis. It has now turned out to be essential to diagnose faults at their very inception; as unscheduled machine downtime can upset deadlines and cause heavy financial burden. In this paper, fault diagnosis and speed control of permanent magnet synchronous motor (PMSM) is proposed. Elman Neural Network (ENN) is used to diagnose the fault of permanent magnet synchronous motor. Both… More >

  • Open Access

    ARTICLE

    Transformer Internal and Inrush Current Fault Detection Using Machine Learning

    R. Vidhya1,*, P. Vanaja Ranjan2, N. R. Shanker3

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 153-168, 2023, DOI:10.32604/iasc.2023.031942

    Abstract Preventive maintenance in the transformer is performed through a differential relay protection system, and it protects the transformer from internal and external faults. However, the Current Transformer (CT) in the differential protection system mal-operates during inrush currents. CT saturates due to magnetizing inrush currents and causes false tripping of the differential relays. Moreover, identification of tripping in protection relay either due to inrush current or internal faults needs to be diagnosed. For the above problem, continuous monitoring of transformer breather and CT terminals with thermal camera helps detect the tripping in relay due to inrush or internal fault. The transformer’s… More >

  • Open Access

    ARTICLE

    Value-Based Test Case Prioritization for Regression Testing Using Genetic Algorithms

    Farrukh Shahzad Ahmed, Awais Majeed, Tamim Ahmed Khan*

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2211-2238, 2023, DOI:10.32604/cmc.2023.032664

    Abstract Test Case Prioritization (TCP) techniques perform better than other regression test optimization techniques including Test Suite Reduction (TSR) and Test Case Selection (TCS). Many TCP techniques are available, and their performance is usually measured through a metric Average Percentage of Fault Detection (APFD). This metric is value-neutral because it only works well when all test cases have the same cost, and all faults have the same severity. Using APFD for performance evaluation of test case orders where test cases cost or faults severity varies is prone to produce false results. Therefore, using the right metric for performance evaluation of TCP… More >

  • Open Access

    ARTICLE

    A Secure Hardware Implementation for Elliptic Curve Digital Signature Algorithm

    Mouna Bedoui1,*, Belgacem Bouallegue1,2, Abdelmoty M. Ahmed2, Belgacem Hamdi1,3, Mohsen Machhout1, Mahmoud1, M. Khattab2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2177-2193, 2023, DOI:10.32604/csse.2023.026516

    Abstract Since the end of the 1990s, cryptosystems implemented on smart cards have had to deal with two main categories of attacks: side-channel attacks and fault injection attacks. Countermeasures have been developed and validated against these two types of attacks, taking into account a well-defined attacker model. This work focuses on small vulnerabilities and countermeasures related to the Elliptic Curve Digital Signature Algorithm (ECDSA) algorithm. The work done in this paper focuses on protecting the ECDSA algorithm against fault-injection attacks. More precisely, we are interested in the countermeasures of scalar multiplication in the body of the elliptic curves to protect against… More >

  • Open Access

    ARTICLE

    Fault Detection and Identification Using Deep Learning Algorithms in Induction Motors

    Majid Hussain1,2,*, Tayab Din Memon3,4, Imtiaz Hussain5, Zubair Ahmed Memon3, Dileep Kumar2

    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 435-470, 2022, DOI:10.32604/cmes.2022.020583

    Abstract Owing to the 4.0 industrial revolution condition monitoring maintenance is widely accepted as a useful approach to avoiding plant disturbances and shutdown. Recently, Motor Current Signature Analysis (MCSA) is widely reported as a condition monitoring technique in the detection and identification of individual and multiple Induction Motor (IM) faults. However, checking the fault detection and classification with deep learning models and its comparison among themselves or conventional approaches is rarely reported in the literature. Therefore, in this work, we present the detection and identification of induction motor faults with MCSA and three Deep Learning (DL) models namely MLP, LSTM, and… More >

  • Open Access

    ARTICLE

    An AOP-Based Security Verification Environment for KECCAK Hash Algorithm

    Hassen Mestiri1,2,3,*, Imen Barraj1,4,5, Mohsen Machhout3

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4051-4066, 2022, DOI:10.32604/cmc.2022.029794

    Abstract Robustness of the electronic cryptographic devices against fault injection attacks is a great concern to ensure security. Due to significant resource constraints, these devices are limited in their capabilities. The increasing complexity of cryptographic devices necessitates the development of a fast simulation environment capable of performing security tests against fault injection attacks. SystemC is a good choice for Electronic System Level (ESL) modeling since it enables models to run at a faster rate. To enable fault injection and detection inside a SystemC cryptographic model, however, the model’s source code must be updated. Without altering the source code, Aspect-Oriented Programming (AOP)… More >

  • Open Access

    ARTICLE

    Computer Vision Technology for Fault Detection Systems Using Image Processing

    Abed Saif Alghawli*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1961-1976, 2022, DOI:10.32604/cmc.2022.028990

    Abstract In the period of Industries 4.0, cyber-physical systems (CPSs) were a major study area. Such systems frequently occur in manufacturing processes and people’s everyday lives, and they communicate intensely among physical elements and lead to inconsistency. Due to the magnitude and importance of the systems they support, the cyber quantum models must function effectively. In this paper, an image-processing-based anomalous mobility detecting approach is suggested that may be added to systems at any time. The expense of glitches, failures or destroyed products is decreased when anomalous activities are detected and unplanned scenarios are avoided. The presently offered techniques are not… More >

  • Open Access

    ARTICLE

    Condition Monitoring and Maintenance Management with Grid-Connected Renewable Energy Systems

    Md. Mottahir Alam1,*, Ahteshamul Haque2, Mohammed Ali Khan3, Nebras M. Sobahi1, Ibrahim Mustafa Mehedi1,4, Asif Irshad Khan5

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3999-4017, 2022, DOI:10.32604/cmc.2022.026353

    Abstract The shift towards the renewable energy market for carbon-neutral power generation has encouraged different governments to come up with a plan of action. But with the endorsement of renewable energy for harsh environmental conditions like sand dust and snow, monitoring and maintenance are a few of the prime concerns. These problems were addressed widely in the literature, but most of the research has drawbacks due to long detection time, and high misclassification error. Hence to overcome these drawbacks, and to develop an accurate monitoring approach, this paper is motivated toward the understanding of primary failure concerning a grid-connected photovoltaic (PV)… More >

  • Open Access

    ARTICLE

    Smart Anti-Pinch Window Simulation Using H-/H Criterion and MOPSO

    Maedeh Mohammadi Azni1, Mohammad Ali Sadrnia1, Shahab S. Band2,*, Zulkefli Bin Mansor3

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 215-226, 2022, DOI:10.32604/cmc.2022.023030

    Abstract Automobile power windows are mechanisms that can be opened and shut with the press of a button. Although these windows can comfort the effort of occupancy to move the window, failure to recognize the person's body part at the right time will result in damage and in some cases, loss of that part. An anti-pinch mechanism is an excellent choice to solve this problem, which detects the obstacle in the glass path immediately and moves it down. In this paper, an optimal solution is presented for fault detection of the anti-pinch window system. The anti-pinch makes it possible to detect… More >

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