Image recognition method for electric meter terminal fault recognition
A technology for fault recognition and image recognition, applied in neural learning methods, character and pattern recognition, instruments, etc., can solve the problems of different, weak features, and high requirements for fault recognition accuracy, to improve efficiency, improve consistency, and achieve goals. The effect of strong detection ability
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[0074] Example 1: Such as Figure 1-7 As shown, an image recognition method for fault recognition of an electric meter terminal includes the following steps:
[0075] (1) Build a classification network based on deep learning, a meter terminal detection network, configuration matching and fault recognition network; building a deep learning network is a common industry technology, generally through configuration files or python scripts, mainly used to set the number of layers of the network, each layer How many nodes, convolution kernel size and other parameters. E.g:
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[0077] (2) The input of the deep learning classification network is an image, and the output is the model of the meter terminal device;
[0078] (3) The output of the meter terminal detection network is a main feature corresponding to each meter terminal model;
[0079] (4) Use the configuration matching detection method to obtain the information characteristics of each meter terminal panel (such as LCD screen...
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