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The methods in infrared thermal imaging diagnosis technology of power equipment

Infrared thermography, which has been widely used, is an important electrical equipment monitoring and fault diagnosis technology. It has two key steps about infrared thermal image processing and artificial intelligence diagnosis faults. In order to improve the accuracy of diagnosing electrical equipment thermal fault, the algorithms of denoising, segmentation and feature extraction in image processing, the BP and RBF network model of neural networks for intelligent diagnosis are discussed with the specific experimental conditions, the advantages and disadvantages of the various technologies and the improved methods are pointed out.