上海交通大学学报(自然版) ›› 2013, Vol. 47 ›› Issue (12): 1980-1986.

• 电工技术 • 上一篇    

基于复Morlet小波变换的变压器绕组模态参数辨识

耿超1,王丰华1,黄华2,金之俭1   

  1. (1.上海交通大学 电气工程系, 上海 200240; 2.上海市电力公司, 上海 200437)
     
  • 收稿日期:2013-01-21
  • 基金资助:

    国家自然科学基金资助项目(51207090),上海市科学委员会重点资助项目(09dz1205900)

Transformer Winding Modal Parameter Identification Based on Complex Morlet Wavelet Transform

GENG Chao1,WANG Fenghua1,HUANG Hua2,JIN Zhijian1
  

  1. (1.Department of Electrical Engineering, Shanghai Jiaotong University, Shanghai 200240, China; 2.Shanghai Municipal Electric Power Company, Shanghai 200437, China)
  • Received:2013-01-21

摘要:

为了较为准确识别变压器绕组非线性系统的模态参数,对某10 kV变压器绕组进行了激振实验.基于实验数据,采用复Morlet小波变换法对变压器绕组固有频率及阻尼比进行辨识,并使用最小二乘法进一步对变压器绕组的对应振型进行了识别,得到了绕组的前4阶固有频率、阻尼比及振型.计算结果表明,实验用变压器绕组的各阶固有频率均远离电动力激励频率,各阶固有频率对应的振型呈现出较好的对称性,说明绕组结构设计较为合理.与PolyMax法进行比较,结果验证了基于复Morlet小波变换的识别方法对包括振型在内的变压器绕组模态参数识别的有效性和实用性.

 
 

 

关键词:  , 变压器, 绕组, 模态参数, 小波变换

Abstract:

The modal parameter of transformer winding, as direct reflections of mechanical performance, is an important theoretical foundation in the field of transformer manufacturing and detection of winding condition based on vibration. To identify the modal parameters accurately, a modal experiment on a 10 kV transformer winding was conducted in this paper. A wavelet transforms method based on complex Morlet wavelet to identify winding natural frequency and damping ratio was proposed using the experiment to identify transformer winding modal parameters. Meanwhile, modal shapes were extracted using the least square method. The first four order modal parameters, including natural frequency, damping ratio and modal shapes were extracted from the vibration signal. The results demonstrate that all the natural frequencies are far away from the exciting frequency, and the modal shapes are symmetrical, which indicates that the design is appropriate. The parameters extracted by the general frequencydomain method PolyMax and the proposed method match well, which verifies the effectiveness of the proposed method in identifying modal parameters of transformer winding.

Key words: transformer, winding, modal parameters, wavelet transform

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