传统的电能质量分析方法通常只针对某一类特定的电能质量扰动问题进行分析，为了实现对常见电能扰动信号进行有效的区分与辨识，提出小波分析与 Prony 方法相结合的分析算法。首先引入小波多分辨分析(multi-resolution analysis)，选取合适的小波函数对扰动信号进行分解，判断分解信号是否存在模极大值点，从而区分出稳态与暂态电能质量扰动问题。对于暂态扰动问题，优化了Mallat重构层数，提取出暂态扰动波形，以实现对扰动类型的判断。对于稳态扰动问题，改进Prony方法对于系统阶数估计的过程，提高了参数辨识精度。最后对混合扰动信号进行分析，并使用Matlab进行了仿真和实验验证。仿真和实验结果表明，该算法能准确地识别出各种类型的电能质量扰动信号。%The traditional analysis method for power quality only analyzes one kind of specific problems. In order to effectively distinguish and identify common power disturbance signal, an algorithm combining wavelet analysis with Prony method is proposed. Firstly,the wavelet multi-resolution analysis is introduced, the appropriate wavelet function is proposed to decompose the disturbance signal and whether the decomposed signal modulus maxima exist is judged.Thus the steady state and transient state power quality disturbance problems are distinguished. For the transientdisturbance problem, Mallat refactoring layer is optimized, the transient disturbance waveform are extracted andthe type of disturbance is distinguished. For the steady disturbance problem, the process of estimating system order by Prony method and the accuracy of parameter identification are improved.Finally,mixed disturbance signals are analyzedandthe simulation and experimental verification are performed by Matlab. Results of simulation and experiments show that the proposed method algorithm can accurately identify the various types of power quality disturbance signal.
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