Fault condition recognition of rolling bearing in bridge crane based on PSO–KPCA
When the rolling bearing in bridge crane gets out of order and often accompanies with occurrence of nonlinear behaviours, its fault information is weak and it is difficult to extract fault features and to distinguish diverse failure modes. Kernel principal component analysis (KPCA) may realize nonli...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2017-01-01
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| Series: | MATEC Web of Conferences |
| Online Access: | https://doi.org/10.1051/matecconf/201710401002 |