期刊文献+

基于幅值恢复法的电机电流测试系统设计

Motor Current Measurement System Design Based on Amplitude Recovery Algorithm
下载PDF
导出
摘要 提出了一种信号处理方法——幅值恢复算法作为对定子电流信号进行快速傅里叶变换前的预处理,目的是为了分析除基波以外的谐波从而诊断电机的轻微故障。作为过滤器功能的幅值恢复算法能够把定子电流信号中各次谐波同基波分离开来,过滤结果用于快速傅里叶变换做进一步的频谱分析。幅值恢复算法有其自身优势,包括阻频带足够窄而且仅阻止基频、不使用积分只用简单的代数和三角运算、易从公式直接推导得来,可单独对运行中的电机作初步故障诊断,实验结果验证了系统设计和方法的有效性。 The paper presented a signal processing method-amplitude the signal pre-processing for Fast Fourier Transform (FFF) in order to recovery method that can be used as analyze the spectrum of the other-order harmonics rather than the fundamental frequency in stator currents and to diagnose subtle faults in motors. The amplitude recovery function as a filter can filter out the component of the fundamental frequency from three phases of stator currents of the motor, and the result can be provided to FFT for further spectrum analysis. It has benefits including its impedance-band narrow enough just to filter out the fundamental frequency; its simple operations with algebra and trigonometry without any integration, and its deduction directly from mathematics equations, which can be independently used as preliminary diagnosis of faults in motors. The experiment proves the effectiveness of the proposed system design and method.
机构地区 河北科技大学
出处 《微电机》 北大核心 2011年第11期14-17,26,共5页 Micromotors
基金 河北省自然科学基金(E2009000703) 河北省高等学校科学技术研究基金(Z2010135)
关键词 信号处理 幅值恢复法 定子电流 故障诊断 signal processing amplitude recovery method stator current fault diagnosis
  • 相关文献

参考文献7

  • 1R.M. Mersereau, M. J. T. Smith. Digital Filtering: a Computer La- boratory Textbook[ M]. Hoboken: John Wiley & Sons Inc. , 1994.
  • 2Y.C. Lim, Y.J. Yu. Synthesis of Very Sharp Hilbert Transformer Using the Frequency-response Masking Technique[ J]. IEEE Trans- actions on Signal Processing, 2005, 53 (7) : 2595 -2597.
  • 3魏伟,王琳.电机故障诊断技术研究现状与发展趋势[J].微电机,2009,42(10):66-68. 被引量:9
  • 4付大金,王秀和,张荣,杨玉波.感应电动机故障诊断技术综述[J].大电机技术,2004(3):27-32. 被引量:10
  • 5Y. Liu, L. Guo, Q. Wang, et al. A System of Detection, Analysis and Diagnosis on E|ectromechanic Systems [ C ]. Proceedings of the Eighth International Conference on Electronic Measurement and In- struments, 2007 : 772 - 775.
  • 6R. Casimir, E. Boutleux, G. Clerc, et al. The Use of Features Se- lection and Nearest Neighbors Rule for Faults Diagnostic in Induction Motors [ J ]. Engineering Applications of Artificial Intelligence, 2006, 19(2): 169-177.
  • 7J. Zarei, J. Poshtan. Bearing Fault Detection Using Wavelet Packet Transform of Induction Motor Stator Current [ J ]. Tribology Interna- tional, 2007, 40(5): 763 -769.

二级参考文献32

  • 1虞和济.设备故障诊断技术的现状及其发展[J].基础自动化,1996,3(5):1-5. 被引量:5
  • 2Kajior Watanabe. Incipient Fault Diagnosis of Chemical Processes via Artifical Neural Networks [ J ]. Journal of AIChE, 1989, 3 (11): 1803-1812.
  • 3Falconer,K.J.分形几何-数学基础及应用[M].沈阳:东北工学院出版社,1992.
  • 4King I J. Plant Diagnostic Relies on Artificial Intelligence Transmissions from Remote Site [J]. Power, 1988, 132: 57-60.
  • 5徐敏.我国设备诊断发展简史与未来[C].1995年全国设备诊断学术会议论文集(上册):7-15.
  • 6Ho T K, Hull J J, Srihari S N.. Decision Combination in Multiple Classifier Systems [J]. IEEE Trans on PAMI, 1994, 16 (1) : 66-75.
  • 7B. Delyon, A. Juditsky, A. Benveniste. Accuracy Analysis for Wavelet Approximations [ J ]. IEEE Transactions on Neural Networks, 1995, 6 (2): 332-348.
  • 8Flandrin, P.. On the Spectrum of Fractional Brownian Motions [J]. IEEE Traps on Information Theory, 1989, 35 (1): 197-199.
  • 9J Kandel A.. Fuzzy Techniques in Patterll Recognition [ M ]. New York : Wiley Interscience, 1982.
  • 10Yazici,Kliman.''An adaptive statistical time-frequency method for detection of broken bars and bearing faults in motors using stator current'' [J].IEEE IA,Vol.35,No.2,1999,pp442-452.

共引文献17

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部