基于ASW-MUSIC的电能质量扰动分析

针对MUSIC算法无法分析非平稳电能质量扰动,提出了一种基于自适应滑窗-多信号分类算法(Adaptive Sliding Win-dow-Multiple Signal Classification,ASW-MUSIC)的时频分析方法。该方法首先根据非平稳电能质量扰动信号特征,采用自适应滑窗对信号数据进行分块,然后利用MUSIC算法对每块中的数据进行处理,检测出频率和幅值信息。并联合所有窗口的分析结果,从而得到整个信号的时频率分布信息。最后对电能质量干扰的非平稳信号进行了仿真实验。实验结果表明,提出的方法适合动态电能质量扰动检测,具有实际应用前景。

Power Quality Disturbance Analysis Based on ASW-MUSIC

According to MUSIC algorithm which can't analyze non-stationary power quality disturbances, it presents a time-frequency analysis based on adaptive sliding window- MUSIC algorithm in this paper. According to the characteristics of non-stationary power quality signal, the signal is first divided into small blocks by the adaptive sliding window. In order to get the frequencies and amplitudes of each block, an MUSIC algorithm is then applied. Next, it receives the whole information of time-frequency distribution with the parameters of each block. At last, simulations have been performed to several non-stationary signals; the results have strongly indicated that the proposed method is very suitable for the detection of power quality disturbance with practically applied prospect.