基于证据理论的齿轮故障诊断
For the reason of low-reliability exists in the gear fault diagnosis of traditional methods,a method based on evidence theory hybrid diagnosis algorithm is presented.According to the fault feature vectors,two parallel BP neural networks are used to carry on local fault diagnosis to acquire the indep...
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| Published in | Jixie Chuandong Vol. 35; pp. 62 - 64 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
Editorial Office of Journal of Mechanical Transmission
01.01.2011
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| Online Access | Get full text |
| ISSN | 1004-2539 |
| DOI | 10.3969/j.issn.1004-2539.2011.09.020 |
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| Summary: | For the reason of low-reliability exists in the gear fault diagnosis of traditional methods,a method based on evidence theory hybrid diagnosis algorithm is presented.According to the fault feature vectors,two parallel BP neural networks are used to carry on local fault diagnosis to acquire the independent evidences each other.Then evidence theory is employed to fuse evidences,and gear fault diagnosis is fulfilled finally.Example shows that,various faults redundant and complement information can be sufficiently used and the reliability of diagnosis is effectively improved. |
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| ISSN: | 1004-2539 |
| DOI: | 10.3969/j.issn.1004-2539.2011.09.020 |