Diagnostics of Inter-Turn Short Circuit Fault in Dry-Type Air-Core Reactor Based on Lissajous Graph and Lightweight Network Model

Binglong Xiang, Xiaojing Dang, Junlin Zhu, Lian Chen, Chao Tang and Zhongyong Zhao ()
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Binglong Xiang: College of Engineering and Technology, Southwest University, Chongqing 400716, China
Xiaojing Dang: Shenzhen Power Supply Co., Ltd., Shenzhen 518000, China
Junlin Zhu: Electric Power Research Institute, China Southern Power Grid, Guangzhou 510663, China
Lian Chen: College of Engineering and Technology, Southwest University, Chongqing 400716, China
Chao Tang: College of Engineering and Technology, Southwest University, Chongqing 400716, China
Zhongyong Zhao: College of Engineering and Technology, Southwest University, Chongqing 400716, China

Energies, 2025, vol. 18, issue 5, 1-21

Abstract: Dry-type air-core reactors (DARs) often have inter-turn short circuit (ITSC) faults. However, traditional fault detection methods for DARs generally demonstrate poor timeliness and low sensitivity, and few methods combine intelligent algorithms for objective and accurate diagnosis. Therefore, a novel online diagnosis method for ITSC faults was proposed. First, the “field-circuit” coupling 2D model of reactors was established to simulate the impact of ITSC faults on the characteristics of various state parameters; accordingly, the Lissajous graph was introduced to characterize the short circuit fault. Then, the variation law of the Lissajous graph under different inter-turn fault layers, turns, and degrees was explored to verify the feasibilities of the proposed method. Finally, to achieve rapid diagnosis and fulfill the requirements of edge computing, a lightweight network model named MobileNetV3-Small was used and combined as a classifier to achieve accurate diagnosis of ITSC faults. The results robustly validate that the Lissajous graphical method can significantly reflect ITSC faults through observing the variation in the graph and feature parameters. Furthermore, the MobileNetV3-Small model achieves a diagnostic accuracy of up to 95.91%, which can further enhance the diagnostic accuracy of the ITSC fault degree.

Keywords: dry-type air-core reactor; Lissajous graph; MobileNetV3-Small; inter-turn short circuit; fault diagnosis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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