Development of infrared thermal simulation platform for voltage-induced defects in arresters

This paper introduces the design, development, and application of an infrared thermal simulation platform to mimic voltage-induced defects in arresters. The platform features 110kV zinc oxide arresters and high-precision heating membranes as core components, with an embedded PID control system to ensure precise temperature management with an accuracy of ±0.5°C. Using 24V low-voltage control, the platform ensures operational safety while supporting independent simulation of multiple defect scenarios. This project aims to address deficiencies in current testing technologies, enhancing personnel training and improving fault detection in high-voltage equipment. The integration of deep learning algorithms and multimodal analysis further optimizes the precision of defect identification.

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Publication Details

Published
2025-05-07
DOI
https://doi.org/10.1117/12.3060372
Primary Topic
Non-Destructive Testing Techniques
Type
article
Field-Weighted Citation Impact
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Development of infrared thermal simulation platform for voltage-induced defects in arresters

Xiaoyun Tian, Guojun Zhang, Zhihui Li, Dr Helena Qian et al.
Non-Destructive Testing Techniques
article

Development of infrared thermal simulation platform for voltage-induced defects in arresters

Xiaoyun Tian, Guojun Zhang, Zhihui Li, Dr Helena Qian, Deqian Dou
article en

Abstract

This paper introduces the design, development, and application of an infrared thermal simulation platform to mimic voltage-induced defects in arresters. The platform features 110kV zinc oxide arresters and high-precision heating membranes as core components, with an embedded PID control system to ensure precise temperature management with an accuracy of ±0.5°C. Using 24V low-voltage control, the platform ensures operational safety while supporting independent simulation of multiple defect scenarios. This project aims to address deficiencies in current testing technologies, enhancing personnel training and improving fault detection in high-voltage equipment. The integration of deep learning algorithms and multimodal analysis further optimizes the precision of defect identification.

Inner Mongolia Electric Power (China) (CN)
Openalex Percentile: Top 91%
Non-Destructive Testing Techniques
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