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Brake fault diagnosis through machine learning approaches - A review
T.M. Alamelu Manghai, ,
Published in Tech Science Press
Volume: 12
Issue: 1
Pages: 43 - 67
Diagnosis is the recognition of the nature and cause of a certain phenomenon. It is generally used to determine cause and effect of a problem. Machine fault diagnosis is a field of finding faults arising in machines. To identify the most probable faults leading to failure, many methods are used for data collection, including vibration monitoring, thermal imaging, oil particle analysis, etc. Then these data are processed using methods like spectral analysis, wavelet analysis, wavelet transform, short-term Fourier transform, high-resolution spectral analysis, waveform analysis, etc., The results of this analysis are used in a root cause failure analysis in order to determine the original cause of the fault. This paper presents a brief review about one such application known as machine learning for the brake fault diagnosis problems. © Copyright 2017 Tech Science Press.
About the journal
JournalData powered by TypesetSDHM Structural Durability and Health Monitoring
PublisherData powered by TypesetTech Science Press