Novel Diagnosis Method for GIS Mechanical Defects Based on an Improved Lightweight CNN Model With Load Adaptive Matching
Yao Zhong, Jian Hao, Qingsong Lliu, Ying Li, Xu Li, Ruijin Liao, Xiping Jiang
Abstract
Mechanical defects of GAS-insulated metal-enclosed switchgear (GIS) equipment seriously threaten power grid security, but <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> -site complex operating conditions create great challenges for defect diagnosis. Therefore, this article proposes a novel diagnosis and state assessment method for GIS mechanical defects under varying currents. First, a time-frequency analysis method of GIS vibration signals based on neighboring mode noise suppression was proposed, and a defect type and severity diagnosis model with load adaptive matching was designed with the improved SqueezeNet. Then, vibration datasets with different severities and currents of typical defects were established based on 110 kV GIS mechanical vibration platform. Finally, model validation and comparison analysis are carried out. Results show that the proposed method effectively mines feature and achieves accurate multiobjective diagnoses of the defect type and severity under varying currents, which is more accurate than traditional methods. The smaller model and faster computing speed are more suitable for edge deployment application.