基于音频信号频谱分析的智能环网柜放电状态识别方法

Mingming Zhang, Jin Hu, Wenjun Li
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引用次数: 0

摘要

传统的放电状态识别方法主要侧重于局部识别。现场识别环境受到来自戈塘的各种干扰信号的影响,导致环形主机组放电状态识别性能较差。为此,设计了一种基于音频信号频谱分析的智能环网机柜放电状态识别方法。采集智能环网柜局部放电数据,提取智能环网柜局部放电特征。在音频信号频谱分析的基础上,对环形主机部分放电噪声信号进行处理,并对放电噪声信号进行滤波,保证放电信号的准确识别。通过对比实验,验证了该方法的识别效果较好,可以应用于现实生活中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Discharging state recognition method of intelligent ring network cabinet based on audio signal spectrum analysis
The conventional discharge state identification method mainly focuses on partial identification. The field identification environment is subject to various interference signals from Getang, resulting in poor performance of the ring main unit discharge state identification. Therefore, an intelligent ring network cabinet discharge state recognition method based on audio signal spectrum analysis is designed. Collect the partial discharge data of the intelligent ring network cabinet, and extract the characteristics of the partial discharge of the intelligent ring network cabinet. Based on the audio signal spectrum analysis, the partial discharge noise signal of the ring main unit is processed, and the discharge noise signal is filtered to ensure accurate identification of the discharge signal. By means of comparative experiments, it is verified that the recognition effect of this method is better and can be applied to real life.
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