Bearing Fault Diagnosis with Kernel Sparse Representation Classification Based on Adaptive Local Iterative Filtering-Enhanced Multiscale Entropy Features
To improve the bearings diagnosis accuracy considering multiple fault types with small samples, a new approach that combined adaptive local iterative filtering (ALIF), multiscale entropy features, and kernel sparse representation classification (KSRC) is put forward in this paper. ALIF is used to ad...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2019-01-01
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| Series: | Mathematical Problems in Engineering |
| Online Access: | http://dx.doi.org/10.1155/2019/7905674 |