The invention discloses a CNN-based transformer fault diagnosis method
A transformer fault and diagnosis method technology, applied in the direction of instruments, measuring electrical variables, image data processing, etc., can solve the problems of inability to achieve real-time performance, waste of human resources, etc., to reduce computational complexity, improve efficiency, and strengthen Lu sticky effect
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[0030] Hereinafter, the present invention will be further described in detail with reference to the accompanying drawings and specific embodiments.
[0031] Please refer to Figure 1 to 3 , The embodiment of the present invention provides a CNN-based transformer infrared image fault diagnosis method, the method includes
[0032] Step 1. Obtain the monitoring image of the transformer;
[0033] Step 2: Input the monitoring image into a CNN judgment model, and obtain the probability value that the monitoring image is a transformer in a normal state;
[0034] Step 3. Determine whether the probability value is lower than the set probability threshold, and if so, determine that the transformer is in a fault state.
[0035] Prior to this, the monitoring images need to be preprocessed. In addition, in order to establish a model that can automatically diagnose the infrared monitoring images of the transformer, the method needs to build a complete and unified image library at the initial stage, ...
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