Fault Diagnosis of Bearing based on Local Characteristic-scale Decomposition and Base-scale Entropy
Aiming at diagnosing the fault of roller bearing accurately,a method based on Local Characteristic-scale Decomposition（ LCD） and Base-scale Entropy（ BE） is proposed. Firstly,the rationality of using the BE to extract the fault information of the bearing vibration signal is analyzed,according to the...
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| Main Authors: | , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Transmission
2017-01-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2017.09.037 |
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| Summary: | Aiming at diagnosing the fault of roller bearing accurately,a method based on Local Characteristic-scale Decomposition（ LCD） and Base-scale Entropy（ BE） is proposed. Firstly,the rationality of using the BE to extract the fault information of the bearing vibration signal is analyzed,according to the parameter selection problem of BE,a method based on phase space reconstruction theory is proposed,and the delay time and embedding dimension are selected. Secondly,in order to extract the fault feature fully,a kind of adaptive multi-scale BE based on LCD is proposed. Finally,the denoising signal and the useful components of LCD are selected to compute the BEs as the feature vector of support vector machine（ SVM） to fault diagnosis. The analysis of the bearing fault data shows that the method can identify the normal,inner ring fault,outer ring fault and rolling fault effectively. |
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| ISSN: | 1004-2539 |