Rough Set Neural Network-based Automatic Fault Identification for Infrared Images of High Voltage Equipment
In view of the problems of excessive loss of recognition results and poor accuracy of currently prevailing fault recognition methods in infrared image fault recognition of high voltage equipment,this paper introduces rough set neural network to the method of automatic fault recognition of infrared images of high voltage equipment.The method works by collecting infrared images of high voltage equipment of different types,models and operating states,establishing infrared image sample database of high voltage equipment,using rough set neural network to mine the infrared image data,and calculating the warning threshold and warning coefficient to realize automatic fault identification and warning.The experi-mental results show that the new fault identification method achieves significant reduction in the loss value of equipment results,and higher identification accuracy.
rough set neural networkhigh voltage equipmentinfrared imagefault identification
万方数据
维普
