中文摘要：

电能质量扰动分析是提高电能质量的基础和依据，其关键问题就是如何准确检测与定位混有噪声电能波形畸变的发生时刻。该文提出了将小波变换后的高频数据进行阀值滤波和信号增强的处理，然后再利用模极大值的方法来检测突变信息。该算法不仅能很好地抑制噪声，还能有效地增强突变点信息，为后续的突变点的精确定位提供了有利条件。仿真实验结果表明，该算法在较强的噪声干扰的情况下仍然有较高的精度和可靠性，是一种行之有效的方法。

英文摘要：

The analysis of power quality disturbances is the basis to improve the power quantity, and its key problem is how to accu- rately detect and position the occurrence time of the form of power mutation with noises. This paper proposes a signal processing algorithm that carries on the threshold filter and the correlation enhancement to high frequency data of wavelet transformation, then makes use of the mold biggest to detect sahation. This algorithm can not only well eliminate noise, but also validly strengthen the point of discontinuity information. It provides advantageous condition for following saltation detection. The simulation experiment result indicates that this algorithm has high precision and reliability in the strong noise jamming situation.