基于声纹压缩的变压器状态检测技术研究
Research on Transformer State Detection Technology Based on Voiceprint Compression
李敏昱 1程航 1黄宇轩 1蔡嘉炜 1高瑞鑫 1孙斌1
作者信息
- 1. 国网福建省电力有限公司福州供电公司,福建 福州 350000
- 折叠
摘要
为提高变压器运维的智能化水平,提出一种基于声纹压缩的变压器状态检测新方法.该方法利用声纹特征提取技术从变压器运行声音中提取关键特征,应用声纹压缩算法实现高效编码,并基于压缩后的特征训练状态识别模型.实验结果表明,该方法在故障检测率、虚警率、准确率等指标上均优于传统方法,可有效提升变压器状态检测的效率和可靠性.
Abstract
To improve the intelligence level of transformer operation and maintenance,a new method for transformer state detection based on voiceprint compression is proposed.This method utilizes voiceprint feature extraction technology to extract key features from the sound of transformer operation,applies voiceprint compression algorithm to achieve efficient encoding,and trains a state recognition model based on the compressed features.The experimental results show that this method outperforms traditional methods in terms of fault detection rate,false alarm rate,accuracy,and other indicators,effectively improving the efficiency and reliability of transformer state detection.
关键词
变压器状态检测/声纹压缩/特征提取Key words
transformer status detection/voiceprint compression/feature extraction引用本文复制引用
基金项目
国网福建省电力有限公司科技项目(521310230009)
出版年
2024
NETL
NSTL
万方数据