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

A BP neural network, transformer fault technology, applied in transformer fault diagnosis, transformer fault diagnosis field based on BP neural network with added momentum term, can solve problems such as speeding up gas production rate, achieve high practicability, convenient maintenance, method rules concise effect

Inactive Publication Date: 2013-06-12
JINING POWER SUPPLY CO OF STATE GRID SHANDONG ELECTRIC POWER CO +1
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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

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

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Embodiment Construction

[0040] The present invention will be further described below in conjunction with the accompanying drawings and embodiments. It should be noted that the following description is only for explaining the present invention and not limiting its content.

[0041] The transformer fault diagnosis method based on the BP neural network with added momentum, the specific steps are as follows:

[0042] 1) Determination of input layer and output layer neurons:

[0043] The transformer fault gas is used as the characteristic gas, and its component content is used as the input layer neuron of the neural network;

[0044] No fault, medium and low temperature overheating, high temperature overheating, low energy discharge, and high energy discharge are used as five output layer neurons, corresponding to O 1 , O 2 , O 3 , O 4 , O 5 , the maximum output value is 1, which means it belongs to this type of fault, and the larger the value, the greater the possibility of this type of fault; the m...

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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...

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Application Information

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IPC IPC(8): G06N3/02
Inventor 王彦良李伟明许磊孔令明刘宗杰李斌曾振刘磊张向东王岩吉树亮王红亮
Owner JINING POWER SUPPLY CO OF STATE GRID SHANDONG ELECTRIC POWER CO
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