用于提取PD信号的复小波簇消噪算法  

Algorithm of Complex Wavelet Cluster for Extracting PD Signal

作　　者：刘双宝[1] 陶善宏[2] 于继来[1] 王力欣[1] 

机构地区：[1]哈尔滨工业大学电气工程及自动化学院,哈尔滨150001 [2]华北电力大学科技学院,保定071003

出　　处：《高电压技术》2007年第10期69-72,95,共5页High Voltage Engineering

摘　　要：因电气设备处在强烈电磁干扰环境中,常被噪声淹没,为了准确检测PD信号,需有效抑制其噪声干扰。根据PD信号和白噪干扰的复小波系数各有其特点和小波变换的本质是被分析信号和小波做内积运算,提出了从一簇复小波中逐层选择最优复小波并根据模极大值原理确定分解层数的方法即以阈值消噪法为基础的复小波簇消噪法。采用该方法对PD染噪信号进行去噪处理,并用去噪前后的信噪比(SNR)和波形相似性参数(NCC)对仿真PD信号的消噪结果进行评价。结果表明,复小波簇消噪法在满足SNR>10 dB的要求下,两个信号的NCC都>0.9,复小波簇消噪法从白噪干扰中提取PD信号的能力更强,在高SNR的情况下,信号的畸变也更小。In order to accurately detect partial discharge of power equipment, white noise must be suppressed. In this paper, according to the characteristic of partial discharge （ PD ） signal and the complex wavelet coefficients of white noise and that the nature of wavelet transform is to calculate the inner product of the signal and wavelet, the algorithm in which an optimum complex wavelet is selected from a cluster of complex wavelets is put forward. Based on the threshold de-nosing algorithm, an algorithm of complex wavelet cluster is given. In this algorithm, the decompose level is decided by the theory of modulus minimum. Then the white noise in polluted PD signal is suppressed by this algorithm, and the de-noising effect is compared with the effect by the algorithm of single complex wavelet threshold. At the same time, the de-noising effect of the emulation PD signal is evaluated by Signal to Noise Ratio （SNR） and Normalized Correlation Coefficient （NCC）. If complex wavelet cluster method is applied, its SNR is more than 10 dB, and its NCC is more than 0.9. However, if single complex wavelet threshold method is applied, its SNR is lower than the former, and its NCC is just more than 0.73. The results indicate that the de-noising effect of complex wavelet cluster is better than that of single complex wavelet and it can suppress white noise effectively with small distortion and high SNR.

关 键 词：局部放电 复小波 复小波簇 阈值 白噪干扰 去噪 

分 类 号：TM85[电气工程—高电压与绝缘技术]