• CN:11-2187/TH
  • ISSN:0577-6686

›› 2009, Vol. 45 ›› Issue (1): 195-199.

• 论文 • 上一篇    下一篇

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基于信息熵的裂纹转子动力特征分析与诊断方法

谢平;杜义浩   

  1. 燕山大学电气工程学院
  • 发布日期:2009-01-15

Crack Rotor Dynamic Feature Analysis and Diagnosis Method Based on Information Entropy

XIE Ping;DU Yihao   

  1. College of Electrical Engineering, Yanshan University
  • Published:2009-01-15

摘要: 针对裂纹转子系统运行过程中的非线性、非平稳突变性等复杂特征,运用信息熵特征提取和融合分析方法,将裂纹转子系统动力分析与参量识别方法有机结合,分析裂纹转子在不同状态下响应参量随转速变化的信息熵特征及变化规律,实现裂纹转子动力响应特征参量的信息熵定量描述;在此基础上,将理论方法用于裂纹转子系统实测信号的分析诊断,并构建小波神经网络模型对裂纹转子信息熵特征曲线进行识别,实现裂纹转子系统故障状态诊断,验证理论方法的有效性。

关键词: 定量描述, 故障诊断, 裂纹转子, 信息熵, 状态特征, H型达里厄风轮, 风洞实验, 风能, 襟翼, 静扭矩, 雷诺数, 自启动

Abstract: Aiming at complex features in the running process of crack rotor system such as non-linear, un-steady abrupt changes, the information entropy feature extracting and fusion analysis method are used to make the dynamic analysis and parameters recognition method combined together in the crack rotor system. The information entropy feature and transformation rule of crack rotor response parameters in various rotating speeds and different states are analyzed to realize the quantitative description of the response feature of crack rotor; Based on this, the proposed new method is used to analyze the testing signals of crack rotor system, and a wavelet neural network model is established to recognize the different information entropy feature curves of crack rotor and realize the fault diagnosis of rotor system. The validity of the proposed method is shown by experimental result.

Key words: Crack rotor, Fault diagnosis, Information entropy, Quantitative description, State feature, Gurney flaps, H-Darrieus wind turbine, Reynolds number, Self-starting, Static torque, Wind energy , Wind tunnel test

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