Research on an Online Preload Detecting Method for Power Transformers Based on FBG
Source abstract
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: crossref · Quality: baseline
Research context
OpenAlex topics: Power Transformer Diagnostics and Insulation · Advanced Fiber Optic Sensors · High voltage insulation and dielectric phenomena
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Electrical Engineering, Chongqing University, Chongqing 400044, China
Funding
China Southern Power Grid Guizhou Power Supply Co., Ltd.
References (47)
Show source-provided references
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