多小波消噪算法在局部放电检测中的应用

Application of Multi-wavelet Based on Denoising Algorithm in Partial Discharge Detection

在简单介绍多小波理论及其消噪算法的基础上,将其应用于抑制局部放电检测中的噪声干扰。局部放电是具有多种形态的非平稳信号,针对常见的4种形态的局部放电脉冲,以均方误差为衡量指标,通过蒙特卡罗仿真分析,研究了小波与多小波在不同局部放电模型下的消噪效果,并就二者提取多态性局部放电的性能进行了比较。研究结果表明,多小波对局放的先验知识要求较低,能够有效地处理多种形态的局放信号,在抑制噪声干扰的同时,能够保留更完整的局部放电信息。

After briefly introducing the theory of multi-wavelet based on denoising algorithm, it was applied to detect the signals of partial discharge. Partial discharges were nonstationary electric signals with various modes. In the contribution, denoising performance of multi-wavelet and wavelet under different mode of partial discharge were analyzed by Monte-Carlo simulation. Furthermore, the capability of extracting the multi-mode partial discharges was demonstrated. The results show that, compared with wavelet, multi-wavelet depends less on the prior knowledge of partial discharge, can process partial discharge with various modes, and preserves more signal features while removing noise from the measured data.