Transformer fault diagnosis method based on improved cuckoo search optimal neural network

Abstract

The invention discloses a transformer fault diagnosis method based on an improved cuckoo search optimal neural network. According to the method, first, the concentrations of DGA characteristic gases are collected and subjected to normalization processing; the number of neurons in an implicit layer of a BP neural network, a training function and a transfer function from an input layer to an outputlayer are determined, and a fault diagnosis model based on the BP neural network is established; an improved cuckoo search algorithm is adopted to optimize parameters of the BP neural network, an optimal weight threshold parameter is obtained, and an optimal BP neural network model is obtained; training samples are utilized to train the optimal BP neural network model, and an improved cuckoo search neural network diagnosis model is obtained; and the improved cuckoo search neural network diagnosis model is adopted to predict test samples, and the output of the model is a transformer fault diagnosis result. Through the method, the problems that the existing BP neural network is slow in overfitting and convergence speed and a solution in a CS algorithm is poor in quality and low in diagnosisprecision are solved.

Description

technical field [0001] The invention belongs to the technical field of fault diagnosis methods for oil-immersed transformers, in particular to a transformer fault diagnosis method based on an improved cuckoo search optimization neural network. Background technique [0002] The transformer is the core equipment in the power system. According to statistics, the annual failure rate of oil-immersed transformers is 0.00625. Therefore, effective diagnosis of latent faults in transformers is of great significance to the safe and stable operation of power systems; in addition, overheating and discharge faults of oil-immersed transformers are always related to oil Dissolved gas analysis (DGA) technology developed based on this has become an important means of diagnosing transformer faults. [0003] However, in engineering practice, the three-ratio method based on DGA technology has some defects, such as incomplete coding and too absolute coding boundaries. It is an effective way to...

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Problems solved by technology

[0005] The purpose of the present invention is to provide a transformer fault diagnosis method based on the improved cuckoo search optimization neural network, which solves the problems of over-fitting and slow convergence speed of the existing BP neural network, poor solution quality and low diagnostic accuracy in the CS algorithm

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