M
Moussa Hamadache
Researcher at Kyungpook National University
Publications - 20
Citations - 398
Moussa Hamadache is an academic researcher from Kyungpook National University. The author has contributed to research in topics: Fault detection and isolation & Fault (power engineering). The author has an hindex of 7, co-authored 17 publications receiving 225 citations. Previous affiliations of Moussa Hamadache include University of Birmingham & University of Ferrara.
Papers
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A comprehensive review of artificial intelligence-based approaches for rolling element bearing PHM: shallow and deep learning
TL;DR: This paper first reviews the fundamentals of prognostics and health management techniques for REBs, and provides overviews of contemporary REB PHM techniques with a specific focus on modern artificial intelligence (AI) techniques (i.e., shallow learning algorithms).
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Rotor Speed-Based Bearing Fault Diagnosis (RSB-BFD) Under Variable Speed and Constant Load
TL;DR: A novel BFD technique, the rotor speed-based BFD (RSB-BFD) method, which exploits theabsolute value-based principal component analysis (PCA), which improves the performance of classical PCA by using the absolute value of weights and the sum square error.
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Principal component analysis based signal-to-noise ratio improvement for inchoate faulty signals: Application to ball bearing fault detection
Moussa Hamadache,Dongik Lee +1 more
TL;DR: In this paper, a modified principal component analysis (PCA) algorithm was proposed to improve the signal-to-noise ratio (SNR) in inchoate faulty signals, in which the optimal subspace is selected via a cumulative percent of variance (CPV) criterion and the test statistic condition of the true information loss.
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On the Fault Detection and Diagnosis of Railway Switch and Crossing Systems: An Overview
TL;DR: The aim is to overview the state of the art in rail S&C and provide a platform for researchers, railway operators, and experts to research, develop and adopt the best methods for their applications; thereby helping ensure the rapid evolution of monitoring and fault detection in the railway industry at a time of the increased interest in condition based maintenance.
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A positive energy residual (PER) based planetary gear fault detection method under variable speed conditions
TL;DR: The proposed positive energy residual (PER) method is capable of detecting faults of a planetary gear under variable speed conditions, while showing better performance than the two other methods.