一种基于遗传算法的局部放电噪声抑制方法

发布时间：2018-05-09 08:57

本文选题：局部放电 + 在线监测　；参考：《华北电力大学》2017年硕士论文

【摘要】：电力变压器是电力系统中重要的电力设备,但是电力变压器通常会受到局部放电的影响而导致电力变压器绝缘发生劣化和老化等现象,严重威胁着电力变压器的安全运行。当电力变压器在发生局部放电时,会从局部放电源向外辐射超高频电磁波。通过超高频(UHF)在线监测技术能够有效地监测电力变压器的局部放电情况。本文主要以超高频(UHF)在线监测技术的关键技术,即局部放电信号的去噪处理技术,为研究对象而开展的研究工作。在了解电力变压器局部放电产生机理和特征参数基础上,分析了局部放电超高频电磁波的产生以及在电力变压器内传播特性,并给出了局部放电UHF在线监测的典型方案。分析了局部放电的噪声干扰的来源,详细介绍了连续小波变换和FFT阈值去噪方法在局部放电信号去噪过程中的去噪原理和操作流程,通过仿真分析了这两种去噪方法的去噪效果。此外,还提出了一种基于遗传算法的局部放电信号去噪方法,给出了去噪方法的实现过程和仿真实例。连续小波变换的去噪效果与小波基函数、小波分解层数以及阈值处理方式等因素有关,合理的选择这些影响因素对于达到较好的去噪效果非常关键,连续小波变换方法能有效地滤除掉局部放电信号中的白噪声。FFT阈值去噪法的去噪效果与功率谱阈值系数有关,适当大小的功率谱阈值系数可以使FFT阈值去噪方法的去噪效果达到最佳,但FFT阈值去噪方法只能够有效地滤除局部放电信号中的周期性窄带噪声。基于遗传算法的局部放电去噪方法,综合了连续小波变换和FFT阈值去噪的优缺点,不仅能够很好的抑制白噪声和周期性窄带噪声的干扰,而且还能够自动设置优化参数,提高去噪效率。
[Abstract]:Power transformer is an important power equipment in power system, but power transformer is usually affected by partial discharge, which leads to deterioration and aging of power transformer insulation, which seriously threatens the safe operation of power transformer. When partial discharge occurs in power transformer, UHF electromagnetic wave will radiate from partial discharge source. The UHF on-line monitoring technology can effectively monitor the partial discharge of power transformers. In this paper, the key technology of UHF on-line monitoring technology, that is, partial discharge signal denoising processing technology, is studied for the research object. Based on the understanding of the generation mechanism and characteristic parameters of partial discharge (PD) in power transformers, the generation of UHF electromagnetic waves and propagation characteristics in power transformers are analyzed, and a typical scheme for on-line monitoring of PD UHF is given. The source of noise interference of partial discharge is analyzed, and the principle and operation flow of continuous wavelet transform and FFT threshold denoising method in the process of partial discharge signal denoising are introduced in detail. The effect of these two denoising methods is analyzed by simulation. In addition, a partial discharge signal de-noising method based on genetic algorithm is proposed, and the realization process and simulation example of the de-noising method are given. The denoising effect of continuous wavelet transform is related to the wavelet basis function, the number of wavelet decomposition layers and the method of threshold processing. The reasonable selection of these factors is very important to achieve a better denoising effect. Continuous wavelet transform method can effectively filter white noise. FFT threshold denoising method is related to the threshold coefficient of power spectrum. The proper power spectrum threshold coefficient can make the denoising effect of the FFT threshold denoising method to be the best, but the FFT threshold denoising method can only effectively filter the periodic narrowband noise in the partial discharge signal. The partial discharge denoising method based on genetic algorithm combines the advantages and disadvantages of continuous wavelet transform and FFT threshold denoising. It not only can suppress the interference of white noise and periodic narrowband noise, but also can set the optimized parameters automatically. Improve the efficiency of denoising.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM855

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