期刊信息
- 刊名： 河北师范大学学报（自然科学版）Journal of Hebei Normal University (Natural Science)
- 主办： 河北师范大学
- ISSN： 1000-5854
- CN： 13-1061/N
- 中国科技核心期刊
- 中国期刊方阵入选期刊
- 中国高校优秀科技期刊
- 华北优秀期刊
- 河北省优秀科技期刊
基于多重自相关的局部放电信号小波去噪分解层数确定方法
- （1.内蒙古电力（集团）有限责任公司 呼和浩特供电局，内蒙古 呼和浩特 010000； 2.华北电力大学 电气与电子工程学院，北京 102206）
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DOI：10.13763/j.cnki.jhebnu.nse.202202019
Determination of the Decomposition Level in Wavelet Threshold Denoising for Partial Discharge Signal Based on Multi-layer Autocorrelation
摘要/Abstract
摘要：
测量系统的白噪声给电气设备局部放电信号的准确测量带来困难. 小波阈值法是常用的去噪方法，其分解层数的选择会影响去噪效果.利用小波分析Mallat算法频带划分原理，提出了一种基于多重自相关的小波分解层数确定方法. 仿真实验结果证明，针对混有测量系统白噪声的电气设备局部放电信号，基于所提出的分解层数确定方法使用小波阈值法可以取得较好的去噪效果.
Abstract：
The white noise of the measurement system brings disturbance to the accurate measurement for partial discharge signal of electrical equipment. Wavelet threshold denoising is a common method，but the decomposition level will affect the denoising effect. Based on the frequency band division principle of wavelet analysis Mallat algorithm，a new method using multi-layer autocorrelation to determine the wavelet decomposition level is proposed in this paper. The simulation results show that for the partial discharge signal of the electrical equipment mixed with white noise of the measurement system, the decomposition level determined by the method can achieve better effects in wavelet threshold denoising.
关键词
参考文献 13
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