摘要
提出一种基于自适应最优核时频分布(AOKTFR)理论的电力系统暂态信号特征分析新方法。该方法首先对信号求取模糊函数,并在模糊域采用自适应最优高斯核函数抑制交叉项,然后求模糊函数的二维傅里叶变换,从而得到仅有自项分量的时频分布,并在此基础上实现时频平面脊信息的提取。分别以绕线式异步电动机转子绕组单相开焊故障和变压器内部、外部故障的区分为例进行仿真。仿真结果表明:该方法适用于多分量、时变的非平稳信号的分析,具有很好的时频聚集性、强自适应性和抗噪声性能,且不受交叉项的影响;脊信息的提取进一步提高了时频分辨率。
An analysis method of power system transient signals based on AOK TFR （Adaptive Optimal Kernel Time-Frequency Representation） is proposed,which seeks the fuzzy function of signals,uses adaptive optimal Gauss kernel to restrain the cross-components in fuzzy domain,carries out two-dimension FFT（Fast Fourier Transform） to obtain the time-frequency distribution of auto-components,and then extracts the ridges from it. The single-phase winding open-weld fault of induction motor and the transformer fault are simulated as examples. Results show that,it has better time-frequency aggregation capability,adaptability and anti-noise ability,not influenced by cross-terms and suitable for the analysis of multi-component,time-varying signals. Time-frequency resolution is improved by ridges extraction.
出处
《电力自动化设备》
EI
CSCD
北大核心
2008年第5期63-67,81,共6页
Electric Power Automation Equipment
基金
湖南省自然科学资助项目(07JJ6079)~~
关键词
AOK
TFR
脊
电力系统
暂态信号
频谱重排
adaptive optimal kernel time-frequency representation
ridges
power system
transient signal
spectrogram reassignment
