Recognition method for switch status of pressure plates in electrical substations based on YOLOv5 neural network model
Coal mine electrical substation is an important part of large coal mine power supply system,and the accurate recognition of the switch status of pressure plates in coal mine electrical substation is crucial for power supply status detection.However,with the significant increase in the number of pressure plate switches in substations,the traditional manual inspection method is facing the problems of slow inspection speed and low inspection accuracy.Aiming at the above problems,a recognition method for the switch status of pressure plates in electrical substations based on YOLO-v5 neural network model was proposed.The model was trained with the Pytorch deep learning framework.A preprocessing method was designed for the image of pressure plate switches.The preprocessed pressure plate switch images were detected and evaluated based on the obtained optimal model.The experimental results show that this method can achieve intelligent recognition of the switch status of the pressure plate,and has the performance of fast speed and high accuracy.
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