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

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.

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Publication Details

Journal
Applied Sciences
Published
2026-01-08
DOI
https://doi.org/10.3390/app16020657
Primary Topic
Power Transformer Diagnostics and Insulation
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Zhanlong Zhang, Jun Deng, Jinbo Wu, Zhihao Gao
Applied Sciences
Power Transformer Diagnostics and Insulation
article

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

Zhanlong Zhang, Jun Deng, Jinbo Wu, Zhihao Gao
article en

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.

Applied SciencesVol. 16(2)
Chongqing University (CN)
China Southern Power Grid
Affordable and clean energy
Openalex Percentile: Top 96%
Power Transformer Diagnostics and Insulation
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Research on an Online Preload Detecting Method for Power Transformers Based on FBG — Zhanlong Zhang, Jun Deng, et al. · Applied Sciences (2026) | TGRS Research Map | TGRS