Research on Fault Diagnosis of High-Voltage Circuit Breakers Using Gramian-Angular-Field-Based Dual-Channel Convolutional Neural Network

Research on Fault Diagnosis of High-Voltage Circuit Breakers Using Gramian-Angular-Field-Based Dual-Channel Convolutional Neural Network

The challenge of accurately diagnosing mechanical failures in high-voltage circuit breakers is exacerbated by the non-stationary characteristics of vibration signals. This study proposes a Dual-Channel Convolutional Neural Network (DC-CNN) framework based on the Gramian Angular Field (GAF) transform...

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Bibliographic Details
Main Authors: Mingkun Yang, Liangliang Wei, Pengfeng Qiu, Guangfu Hu, Xingfu Liu, Xiaohui He, Zhaoyu Peng, Fangrong Zhou, Yun Zhang, Xiangyu Tan, Xuetong Zhao
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Energies
Subjects:
high-voltage circuit breaker
vibration faults
Gramian Angular Field
convolutional neural network
Online Access:https://www.mdpi.com/1996-1073/18/14/3837
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