Work

Research on GIS Circuit Breaker Fault Diagnosis Based on Closing Transient Vibration Signals

Year: 2025

Type: article

Abstract: GIS circuit breakers play a critical role in maintaining the reliability of modern power systems. However, mechanical failures, such as spring fatigue, transmission rod jamming, and loosening of structural components, can significantly impact their performance. Traditional diagnostic methods struggle to identify these issues effectively due to the enclosed nature of GIS equipment. This study explores the use of vibration signal analysis, specifically during the closing transient phase of the GIS circuit breaker. The proposed method combines wavelet packet decomposition, rough set theory for feature extraction and dimensionality reduction, and the S_Kohonen neural network for fault type identification. Experimental results demonstrate the robustness and accuracy of the method, achieving a diagnostic accuracy of 96.7% in identifying mechanical faults. Compared with traditional methods, this approach offers improved efficiency and accuracy in diagnosing GIS circuit breaker faults. The proposed method is highly applicable for predictive maintenance and fault diagnosis in power grid systems, contributing to enhanced operational safety and reliability.

Source: Machines

DOI: 10.3390/machines13040335

Authors: Yue Yu, Hongyan Zhao

Institution: Beijing University of Technology

Language: English

Topic: Machine Fault Diagnosis Techniques

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,896