基于小波能量矩的输电线路暂态信号分类识别方法

A Wavelet Energy Moment Based Classification and Recognition Method of Transient Signals in Power Transmission Lines

信号能量的时频分布可以反映不同信号的本质区别,小波能量矩既可以反映信号能量在频域上的分布,也可以间接体现能量在时域上的分布。文章将基于小波能量矩的信号特征提取方法用于区分输电线路的故障暂态信号与非故障暂态信号。首先基于500kV输电线路仿真模型得到电容投切、三相断路器操作、单相接地短路、一次电弧故障、非故障性雷击和故障性雷击6种类型的暂态信号;然后利用小波变换提取这些信号各频带的能量矩,得到能量矩统计图并对各暂态信号小波能量矩的分布特点进行分析,在此基础上提出了暂态信号分类识别判据。基于小波能量矩方法提取的暂态信号特征较明显,分类识别简便,仿真结果验证了该方法的可行性和有效性。

The distribution of signal energy in time domain and frequency domain can reveal essential differences among various signals in detail comparatively. The wavelet energy moment can reflect the distribution of signal energy in frequency domain and that in time domain indirectly as well. The authors apply the wavelet energy moment based method of signal feature extraction to distinguish fault transient signal from non-fault transient signal. At first, the wavelet energy moment based signal feature extraction method is applied to six types of transient signals from three-phase circuit breaker operation, single-phase earth fault, arcing fault in primary circuit, non-fault lightning stroke and fault lightning stroke, which are obtained by the simulation model of 500kV transmission line; then by use of wavelet transform the energy moments of these transient signals in various frequency bands are extracted to obtain statistical graphs of energy moments and the distribution characteristics of the wavelet energy moment of each transient signal is analyzed. On this basis the classification and recognition criteria for transient signals can be acquired. The transient signals extracted by wavelet energy moment possess evident features and are easy to classified and recognized. Simulation results verify the feasibility and effectiveness of the proposed method.