| Summary: | Relay protection device is an important part to ensure the safe and stable operation of power system. With the rapid increase of the number of substations and relay protection devices,the daily inspection workload of the operation and maintenance personnel has become saturated,which can not guarantee the high quality and no dead angle inspection every time and brings hidden dangers to the reliable operation of the protection devices. In this paper,an intelligent inspection technology of protection device based on convolution neural network image recognition algorithm is proposed. With the help of the cameras installed in the front and back of the cabinet,the unmanned or few people inspection of the protection device can be realized. Firstly,the intelligent inspection system of the protection device is introduced,and the intelligent inspection items that can be realized is analyzed. The conclusion that convolution neural network can be used for image recognition is drawn. Secondly,taking the platen state recognition as an example,the training sample set and test sample set required by the inspection items are introduced,and the convolution neural network level of the inspection items is given. Then the training sample set is used to train the convolution neural network of different inspection items,and finally each network is tested. The test results show that the neural network image recognition rate of each inspection item is above 96%,even 98%,and the recognition effect is good.
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