Fault Identi fication of Rolling Bearing Based on Adaptive Wavelet Analysis and Multiple Layers Convolution Extreme Learning Auto-encoder
Aiming at the problems of rolling bearing vibration signals were dif ficult to identify due to strong time-varying and strong noisy characteristics, a method based on adaptive wavelet analysis (AWA) and multiple layers convolution extreme learning auto-encoder (MLCELAE) was proposed. Firstly, a new...
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| Main Author: | |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Electric Drive for Locomotives
2021-11-01
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| Series: | 机车电传动 |
| Subjects: | |
| Online Access: | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128x.2021.06.015 |
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