To enhance the accuracy of insulation performance testing for high-voltage electrical equipment,this study has designed an automated detection system based on machine vision.The system initially captures images of the insulation surface of the equipment using an industrial camera,followed by analysis with a target detection algorithm to precisely identify insulation defects.Additionally,the system employs binocular stereo vision technology for accurate defect localization and dimension measurement.Results demonstrate that the system can effectively recognize defects such as damage and contamination on the surface of insulating equipment,providing robust technical support for the safe operation and maintenance management of electrical equipment.
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