山东电力技术2025，Vol.52Issue(7)：76-85,10.DOI:10.20097/j.cnki.issn1007-9904.2025.07.008
变压器短路实验下基于WOA-SVM的顶层油温声学反演方法
Acoustic Inversion Method for Top-oil Temperature in Transformers Based on WOA-SVM Under Short-circuit Testing
摘要
Abstract
The top-oil temperature of transformer windings serves as a crucial health monitoring indicator,effectively characterizing the internal state and potential defects.Leveraging the advantages of ultrasonic sensing technology,known for its strong penetrative power and sensitivity to temperature changes,a novel inversion method combining ultrasonic sensing technology with whale optimization algorithm-optimized support vector machine(WOA-SVM)is proposed.This study focuses on a 35 kV transformer,where internal temperature rise is induced through short-circuit testing,and ultrasonic signals carrying temperature information are collected.An in-depth exploration is conducted on the characteristics of ultrasonic wave signals inside the transformer under different temperature conditions ranging from 20℃to 50℃.By extracting and processing key acoustic signal parameters,such as peak amplitude,peak-to-peak value,root mean square,waveform factor,crest factor,and variance,accurate inversion of the top-oil temperature was successfully achieved.The research results demonstrate that this method exhibits high accuracy(97.95%)in the inversion of transformer top-oil temperature,providing a new technical avenue for transformer health monitoring.关键词
油浸式电力变压器/顶层油温/超声检测/支持向量机Key words
oil-immersed power transformer/top-oil temperature/ultrasonic testing/support vector machine分类
信息技术与安全科学引用本文复制引用
杨超,薛帅,李承振,郭昊鑫,杨梦娇..变压器短路实验下基于WOA-SVM的顶层油温声学反演方法[J].山东电力技术,2025,52(7):76-85,10.基金项目
国网山东省电力公司科技项目(2022A-125). Science and Technology Project of State Grid Shandong Electric Power Company(2022A-125). （2022A-125）
