Research on an Online Preload Detecting Method for Power Transformers Based on FBG

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Authors: Jinbo Wu, Zhanlong Zhang, Jun Lin Deng, Zhihao Gao
Cited by: 1
References: 40

Abstract

This paper presents research on an online preload detecting method for power transformer windings that is highly sensitive, survivable and repeatable. Traditional frequency response analysis methods exhibit limitations in sensitivity, accuracy, and interference resistance, making it difficult to detect small loosening. Although the FBG offer superior performance, quartz optical fibers exhibit limited deformation capacity and are susceptible to damage from short circuit impacts. To identify FBG placement locations with minimal impact exposure, this study compared FBG sensors at different installation positions through 42 short circuit impacts. Results confirmed that the FBG positioned at the top of pressure board experienced the least impact damage. Subsequently, a transformer equipped with this online preload detecting system underwent 12 short circuit impact tests. Simulation results and hoisting cover findings aligned with the FBG online detecting data. This study proposes an experimentally validated online preload detecting method, providing a reliable and reproducible technical pathway for transformer condition assessment.

Fields of Study & Subjects

Power Transformer Diagnostics and Insulation Advanced Fiber Optic Sensors High voltage insulation and dielectric phenomena

Publication details

Journal / source
Applied Sciences
Publisher
MDPI AG
Volume
16
Issue
2
Pages
657–657
Publication date
8 January 2026
Language
EN