摘要
In this paper, a vacuum circuit breaker test platform was built and four kinds of mechanical failure state, such as principle axles jam fault, were realized. The intrinsic mode function(IMF)needed was gotten by empirical mode decomposition(EMD)of vibration signal measured under normal and fault condition. The energy method was used to get the total energy of all intrinsic mode function weights containing main fault feature information. The total energy of all intrinsic mode function weights was taken as a feature vector, and put into support vector machine(SVM). The different classification strategy as well as the classification time and accuracy of kernel function were analyzed and compared. By the experiment, OAOT classification strategy and RBF kernel function were chosen for their better classification effect. The study provides the theoretical basis and actual data base for the R & D of the circuit breaker fault diagnosis system.
| 源语言 | 英语 |
|---|---|
| 页(从-至) | 1-7 and 13 |
| 期刊 | Gaoya Dianqi/High Voltage Apparatus |
| 卷 | 53 |
| 期 | 2 |
| DOI | |
| 出版状态 | 已出版 - 16 2月 2017 |
指纹
探究 'Research of Fault Diagnosis of Circuit Breaker Based on Vibration Signal Recognition' 的科研主题。它们共同构成独一无二的指纹。引用此
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