Weak fault diagnosis of rolling bearing based on FRFT and DBN
When diagnosing the weak fault of rolling bearing, the fault characteristic is difficult to be extracted because the fault signal has a small amplitude and is susceptible to noise. Aiming at this problem, a fault diagnosis method is proposed based on fractional Fourier transform (FRFT) and deep beli...
Main Authors: | Xing He, Jie Ma |
---|---|
Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2020-01-01
|
Series: | Systems Science & Control Engineering |
Subjects: | |
Online Access: | http://dx.doi.org/10.1080/21642583.2020.1723143 |
Similar Items
-
Size and Location Diagnosis of Rolling Bearing Faults: An Approach of Kernel Principal Component Analysis and Deep Belief Network
by: Heli Wang, et al.
Published: (2021-05-01) -
Rolling element bearing weak fault diagnosis based on spatial correlation and ALIFD
by: Lei Zhao, et al.
Published: (2020-05-01) -
An End-to-End Intelligent Fault Diagnosis Application for Rolling Bearing Based on MobileNet
by: Wenbing Yu, et al.
Published: (2021-01-01) -
Research on fault law of rolling bearing under different fault levels and loads with HHT method
by: Liu Yongbao, et al.
Published: (2014-06-01) -
Improved Empirical Wavelet Transform for Compound Weak Bearing Fault Diagnosis with Acoustic Signals
by: Chaoren Qin, et al.
Published: (2020-01-01)