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三角样条调频小波变换的电机轻微故障定位
引用本文:胡国胜,任震,黄雯莹,万国成. 三角样条调频小波变换的电机轻微故障定位[J]. 电网技术, 2003, 27(3): 28-31
作者姓名:胡国胜  任震  黄雯莹  万国成
作者单位:1. 华南理工大学电力学院,广东省,广州市,510640;广东省科技干部学院,广东省,广州市,510640
2. 华南理工大学电力学院,广东省,广州市,510640
基金项目:国家自然科学基金资助(50077008)。
摘    要:实小波变换只能提取信号的幅值特性,而电机轻微故障信号的小波幅值很小,因而用实小波变换有时很难检测到故障的发生,复值小波不仅能提取信号的幅值特性,还能提取信号的相位特性,进而在轻微故障信号的小波变换幅变化不太明显的情况下,利用相位变化的特性也能准确判断微弱故障信号的突变点,文章将线调频小波变换应用到电机微弱故障的诊断中,取二阶三角样条小波作为窗函数,并令q=0得到简化的二阶三角样条调频小波,提取故障信号的相位特性,成功地确定了微弱故障信号的突变点。

关 键 词:三角样条 调频小波变换 电机 故障定位 故障监测
文章编号:1000-3673(2003)03-0028-04
修稿时间:2002-05-28

LOCATION OF SLIGHT FAULT IN ELECTRIC MACHINE USING TRIGONOMETRIC SPLINE FREQUENCY MODULATION WAVELET TRANSFORMS
HU Guo-sheng,,REN Zhen,HUANG Wen-ying,WAN Guo-cheng. LOCATION OF SLIGHT FAULT IN ELECTRIC MACHINE USING TRIGONOMETRIC SPLINE FREQUENCY MODULATION WAVELET TRANSFORMS[J]. Power System Technology, 2003, 27(3): 28-31
Authors:HU Guo-sheng    REN Zhen  HUANG Wen-ying  WAN Guo-cheng
Affiliation:HU Guo-sheng1,2,REN Zhen1,HUANG Wen-ying1,WAN Guo-cheng1
Abstract:Real wavelets can only extract the amplitude of signals. When fault signals change slightly, real wavelets cannot detect the suddenly changing point. Therefore, sometimes it is difficult to detect the occurrence of fault by real wavelets. Using complex wavelets not only the amplitude features of signals can be extracted, but also the phase features of signals, and then the catastrophe point of faint fault signal can be accurately judged by the specific property of phase change under the condition that the amplitude variation of wavelet transform of the signals of faint fault is not evident. Here the frequency modulation wavelet transforms are applied to the diagnosis of faint fault of electrical machines. In this method taking the 2nd order trigonometric spline wavelet as the window function and let q=0, the simplified 2nd order trigonometric spline frequency modulation wavelet transforms (TSFMWT) is obtained. Thereby the phase features of the fault signal is extracted and the catastrophe point of the signals of faint fault can be successfully determined.
Keywords:trigonometric spline wavelet  frequency modulation wavelet transform  slight fault detection
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