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Harmonic analysis of traction power supply system based on wavelet decomposition

机译：基于小波分解的牵引电源系统谐波分析

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With the rapid development of high-speed railway and heavy-haul transport, AC drive electric locomotive and EMU large-scale operation in the country on the ground, the electrified railway has become the main harmonic source of China's power grid. In response to this phenomenon, the need for timely monitoring of power quality problems of electrified railway, assessment and governance. Wavelet transform is developed on the basis of Fourier analysis, the basic idea comes from the harmonic analysis, with a rigorous theoretical model, which has inherited and developed the local thought of Garbor transformation, and has overcome the disadvantages such as window fixation and lack of discrete orthogonally, so as to become a more recently studied spectral analysis tool. The wavelet analysis takes the gradual and precise time domain step in the high frequency part so as to focus on any details of the signal being analyzed, thereby comprehensively analyzing the harmonics of the traction power supply system meanwhile use the pyramid algorithm to increase the speed of wavelet decomposition. The matlab simulation shows that the use of wavelet decomposition of the traction power supply system for harmonic spectrum analysis is effective.
机译：随着高速铁路的快速发展和重量运输，交流电力机车和鸸大尺度运行在地上，电气化铁路已成为中国电网的主要谐波源。针对这种现象，需要及时监测电气化铁路电力质量问题，评估和治理。小波变换是在傅立叶分析的基础上开发的，基本思想来自谐波分析，具有严谨的理论模型，它继承并开发了加尔堡转型的本地思想，并克服了窗户固定等缺点离线性离线性，以便成为最近研究的光谱分析工具。小波分析采用高频部分中的逐渐和精确的时域步骤，以聚焦正在分析的信号的任何细节，从而综合分析牵引电源系统的谐波同时使用金字塔算法增加速度小波分解。 MATLAB仿真表明，使用小波分解的牵引电源系统进行谐波频谱分析是有效的。

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