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Brake Fault Diagnosis Through Machine Learning Approaches–A Review
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作者 T.M.Alamelu Manghai R.Jegadeeshwaran V.Sugumaran 《Structural Durability & Health Monitoring》 EI 2017年第1期41-61,共21页
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 isa field of finding faults arising in machines. To... 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 isa field of finding faults arising in machines. To identify the most probable faults leadingto failure, many methods are used for data collection, including vibration monitoring,thermal imaging, oil particle analysis, etc. Then these data are processed using methodslike spectral analysis, wavelet analysis, wavelet transform, short-term Fourier transform,high-resolution spectral analysis, waveform analysis, etc. The results of this analysis areused 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 learningfor the brake fault diagnosis problems. 展开更多
关键词 Vibration analysis machine learning feature extraction feature selection feature classification brake fault diagnosis
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