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中文摘要：
针对电力系统暂态振荡信号频率检测中存在的检测过程复杂、易受噪声影响且通用性不强的问题,提出了一种基于Morlet复小波谱峭度的暂态振荡信号频率检测方法.采用Morlet复小波对含噪暂态振荡信号进行小波分解获得小波系数；利用小波系数绝对值计算信号的谱峭度；最后,通过最大值检测方法实现对暂态振荡的频率检测.针对谱峭度对噪声适用范围不明确的问题,提出并定义相似度函数,用于分析算法对噪声的敏感程度.仿真实验表明,该方法通用性较强,且计算过程简单,检测精度可以满足实际需求.
英文摘要：
The existed methods of frequency detection of transient oscillation signal in power system are intricate and susceptible to noise and abominable in versatility. To overcome these disadvantages a novel method based on Morlet wavelet-based-spectral kurtosis （SK） is proposed in this paper. In this method, the Morlet wavelet transform is initial- ly adopted to obtain the wavelet coefficients. Then the wavelet-based-SK is calculated via the absolute value of the wavelet coefficients. Finally, the transient oscillation frequency is detected by the maximum of the SK. In order to ana- lyze the influence on the detection results caused by noise, the similarity function is proposed and defined in the paper. The simulation results indicate that this method is applicable and effective to most of the common oscillation signals. In addition the calculation process is simple, and the accuracy can meet the actual needs.
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A New Classification Method for Transient Power Quality Combining Spectral Kurtosis with Neural Netw
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