摘要
电力设备故障时将产生具有奇异性的非平稳信号 ,小波变换在时域和频域内同时具有局部化能力 ,是分析故障信号奇异性的有利工具 ,为电力设备故障检测提供了新思路。首先讨论了信号奇异性的小波变换特性 ,在此基础上 ,研究了信号全局奇异性指数和局部奇异性指数 (Lipschitz指数 )的计算方法。仿真分析了电流基波及各次谐波等理论信号等的奇异性指数特点 ,将其应用于电力设备故障检测中 。
Non stationary signal with singularities is presented when electrical devices are faulting.Wavelet transform possesses time frequency localization ability, so it provides a powerful tool to analyze fault signal and a new idea to detect fault. Signal singularities based on wavelet transform are introduced. According to this,a computational approach to it is studied. The singularity exponents (Lipschitz exponents) of current and harmonics are analyzed, simulation result demonstrates that the global and partial singularity exponent is suitable for electrical device fault detection.
出处
《电力自动化设备》
EI
CSCD
2000年第3期12-15,共4页
Electric Power Automation Equipment
