Transformer fault diagnosis method based on neural network

Abstract

The invention relates to a transformer fault diagnosis method based on a neural network. The method comprises the following steps: analyzing fault reasons, and extracting a sample set of dissolved gas in transformer oil and a corresponding a fault type inside a transformer; determining the number of Neurons in a neural network hidden layer according to experience and a successive optimization searching method, and building a neural network; adopting an improved Cuckoo optimization algorithm to train the neural network; and finally utilizing the trained neural network to diagnose a fault of the transformer. The entire design method has the characteristics of high search precision and high global search capability, and effectively improves the accuracy of fault diagnosis for a transformer.

Description

technical field [0001] The invention relates to a transformer fault diagnosis method based on a neural network, belonging to the technical field of transformer fault processing. Background technique [0002] The power transformer is one of the important components of the power system. Its safety performance directly affects whether the electrical system in our country can operate reliably, and also indirectly affects the daily life of our residents. Therefore, the maintenance and testing of power transformers have become very urgent, but frequent disassembly and assembly of transformers will damage the equipment again and bury safety hazards for the equipment. With the increase of power consumption, the load on power transformers is also increasing. Therefore, it is necessary to monitor the operation status of power equipment in real time. Through real-time detection, early defects of electrical equipment can be found, so as to prevent accidents and reduce the risk of accide...

AI Technical Summary

Problems solved by technology

[0003] In view of the above-mentioned technical problems, the technical problem to be solved by the present invention is to provide a transformer fault diagnosis method based on neural network, which not only solves the problem that the neural network parameters are difficult to optimize, but also improves the speed and accuracy of the global convergence of the neural network, and Improve the ability and accuracy of transformer fault diagnosis

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