Transformer fault diagnosis method based on added momentum item BP (back propagation) neural network

Abstract

The invention discloses a transformer fault diagnosis method based on an added momentum item BP (back propagation) neural network. On the basis of the added momentum item BP neural network, the invention structures a full sense of intelligent method, namely a transformer fault diagnosis method based on gas data dissolved in oil, so as to improve the speed and accuracy rate of fault diagnosis. The method comprises the following steps of 1) determining neural elements of an input layer and an output layer; 2) determining activation function, the number of hidden layers of the neural network and the neural element number of the hidden layers, thereby establishing a neural network; 3) utilizing a BP algorithm of the added momentum item to adjust the network parameter, and training the established neural network; and 4) utilizing an MATLAB (matrix laboratory) software to simulate the tested neural network, thereby performing test diagnosis for the transformer fault.

Description

technical field [0001] The invention relates to a transformer fault diagnosis method, in particular to a transformer fault diagnosis method based on a BP neural network with an added momentum term. The invention belongs to the technical field of transformer equipment status online monitoring. Background technique [0002] With the continuous development of the power system, higher requirements are put forward for the safety and reliability of power equipment. While continuously improving the quality of power supply, the power supply department should take practical measures to ensure the normal operation of power equipment to improve safety. Electricity reliability. The role of transformers in power transmission and transformation systems is extremely important, and the importance of its long-term, safe, reliable, and efficient operation is self-evident. For large-scale power transformers, oil is mostly used for insulation and heat dissipation at present. Transformer oil a...

AI Technical Summary

Problems solved by technology

For large-scale power transformers, oil is mostly used for insulation and heat dissipation at present. The solid organic insulating materials in transformer oil and oil will gradually deteriorate due to various factors such as electricity, heat, oxidation and local arcing under operating voltage, and crack into Low-molecular gas; latent overheating or discharge faults inside the transformer will accelerate the rate of gas production

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