Year: 2026
Type: article
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.
Source: Applied Sciences
DOI: 10.3390/app16020657
Authors: Jinbo Wu, Zhanlong Zhang, Jun Deng, Zhihao Gao
Institution: Chongqing University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Funder: China Southern Power Grid
OpenAlex ID: W7118424911