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.
Authors
- Zhanlong Zhang
- Jun Deng (ORCID: https://orcid.org/0000-0003-3302-5784)
- Jinbo Wu
- Zhihao Gao
Institutions
- Chongqing University (CN)
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
Funders
- China Southern Power Grid