• HOME
  • About Journal
    • Historical evolution
    • Journal Honors
  • Editorial Board
    • Members of Committee
    • Director of the Committee
    • President and Editor in chief
  • Submission Guide
    • Instructions for Authors
    • Manuscript Processing Flow
    • Model Text
    • Procedures for Submission
  • Academic Influence
  • Open Access
  • Ethics&Policies
    • Publication Ethics Statement
    • Peer Review Process
    • Academic Misconduct Identification and Treatment
    • Advertising and Marketing
    • Correction and Retraction
    • Conflict of Interest
    • Authorship & Copyright
  • Contact Us
  • Chinese
Site search        
文章摘要
基于小波包能量分析和信号融合的异步电机转子故障诊断
Rotor fault diagnosis of induction motor based on wavelet packet energy analysis and signal fusion
Received:February 04, 2021  Revised:February 18, 2021
DOI:10.19753/j.issn1001-1390.2024.04.023
中文关键词: 故障诊断  异步电机  转子断条  气隙偏心  小波包分析  信号融合
英文关键词: fault diagnosis, induction motor, rotor broken bar fault, air gap eccentricity fault, wavelet packet analysis, signal fusion
基金项目:国家重点研发计划资助项目(2018YFB0904800),国家自然科学基金资助项目( 51677078,51477060),湖北省自然科学基金资助项目(2019CFB812)
Author NameAffiliationE-mail
Zhang Yahui State Key Laboratory of Advanced Electromagnetic Engineering and Technology,School of Electrical and Electronics Engineering,Huazhong University of Science and Technology zhangyahui@hust.edu.cn 
Yang Kai* State Key Laboratory of Advanced Electromagnetic Engineering and Technology,School of Electrical and Electronics Engineering,Huazhong University of Science and Technology yk@hust.edu.cn 
Yang Fan State Key Laboratory of Advanced Electromagnetic Engineering and Technology,School of Electrical and Electronics Engineering,Huazhong University of Science and Technology m201971485@hust.edu.cn 
Hits: 482
Download times: 246
中文摘要:
      为提高异步电机转子故障诊断的可靠性,文中介绍了一种基于小波包能量分析和信号融合的异步电机转子故障诊断方法。采用定子电流信号和振动信号的频谱特征融合作为转子断条以及气隙偏心故障的诊断依据,首先对信号进行小波包分解,获得不同小波包频带节点下对应的能量分布,并与正常电机信号进行比较,进而对能量异常的信号频段进行小波包节点重构,最后通过快速傅里叶变换识别故障特征频率,诊断电机故障是否发生。通过仿真分析,验证了该方法的有效性和实用性,对于电机运行状态的准确监测具有重要意义。
英文摘要:
      Aiming to improve the reliability of rotor fault diagnosis for induction motor, this paper proposed a method of rotor fault diagnosis for induction motor based on wavelet packet energy analysis and signal fusion. The frequency spectrum fusion of stator current signal and vibration signal is used as the diagnosis basis of rotor broken bar fault and air gap eccentric fault. First, the signal is decomposed by wavelet packet to obtain the corresponding energy distribution under different wavelet packet frequency band nodes and compare it with the normal motor signal. Then, the wavelet packet node reconstruction is carried out for the signal frequency band with abnormal energy. Finally, the fault characteristic frequency is identified by the fast Fourier transform to diagnose whether the motor fault occurs. Through simulation analysis, the effectiveness and practicability of the method are verified, and it is of great significance for the accurate monitoring of motor running state.
View Full Text   View/Add Comment  Download reader
Close
  • Home
  • About Journal
    • Historical evolution
    • Journal Honors
  • Editorial Board
    • Members of Committee
    • Director of the Committee
    • President and Editor in chief
  • Submission Guide
    • Instructions for Authors
    • Manuscript Processing Flow
    • Model Text
    • Procedures for Submission
  • Academic Influence
  • Open Access
  • Ethics&Policies
    • Publication Ethics Statement
    • Peer Review Process
    • Academic Misconduct Identification and Treatment
    • Advertising and Marketing
    • Correction and Retraction
    • Conflict of Interest
    • Authorship & Copyright
  • Contact Us
  • 中文页面
Address: No.2000, Chuangxin Road, Songbei District, Harbin, China    Zip code: 150028
E-mail: dcyb@vip.163.com    Telephone: 0451-86611021
© 2012 Electrical Measurement & Instrumentation
黑ICP备11006624号-1
Support:Beijing Qinyun Technology Development Co., Ltd