节点文献

基于小波模糊网络的电厂汽轮发电机组故障诊断

FAULT DIAGNOSIS METHOD FOR TURBOGENERATOR SET BASED ON WAVELET FUZZY NETWORK

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 刘琳沈颂华刘强

【Author】 LIU Lin1,SHEN Song-hua1,LIU Qiang2 (1.School of Automation Science and Electrical Engineering,Beijing University of Aeronautics and Astronautics,Haidian District,Beijing 100083,China;2.School of Mechanical Electronical and Information Engineering,China University of Mining and Technology,Haidian District,Beijing 100083,China)

【机构】 北京航空航天大学自动化科学与电气工程学院中国矿业大学机电与信息科学学院 北京市海淀区100083北京市海淀区100083北京市海淀区100083

【摘要】 针对传统故障诊断方法在汽轮发电机组振动类多重并发故障诊断中的局限性,提出了小波变换与模糊理论相结合的诊断方法。采用二进离散小波变换获取有效的故障特征向量,利用模糊诊断方程进行故障模式分类。通过选择足够的样本对故障诊断方程进行训练,将代表故障的信息输入训练好的诊断方程,由输出结果即可判定故障类型。实际应用表明该方法可以有效诊断汽轮发电机组振动类多重并发故障,诊断结果全面、准确。

【Abstract】 To improve the limitation of applying traditional fault diagnosis method to the diagnosis of multi-concurrent vibrant faults of turbogenerator sets, a new diagnosis method integrating the wavelet transform with fuzzy theory is proposed. The effective eigenvectors are acquired by binary discrete wavelet transform and the fault modes are classified by fuzzy diagnosis equation. By means of choosing enough samples to train the fault diagnosis equation and the information representing the faults is input into the trained diagnosis equation, and according to the output result the type of fault can be determined. Actual applications show that the proposed method can effectively diagnose the multi-concurrent vibrant faults of turbogenerator sets and the diagnosis result is correct.

  • 【文献出处】 电网技术 ,Power System Technology , 编辑部邮箱 ,2005年16期
  • 【分类号】TM311
  • 【被引频次】15
  • 【下载频次】201
节点文献中: 

本文链接的文献网络图示:

本文的引文网络