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Oil-immersed transformer fault diagnosis method based on neural network and decision fusion

A technology for oil-immersed transformers and transformer faults, applied in neural learning methods, biological neural network models, transformer testing, etc., can solve problems such as poor fault identification effect and unbalanced identification performance of different faults, and achieve high identification accuracy Effect

Active Publication Date: 2020-03-13
WUHAN NARI LIABILITY OF STATE GRID ELECTRIC POWER RES INST
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Problems solved by technology

[0004] Artificial neural network is a classification algorithm, which can effectively fit the nonlinear mapping relationship between input and output. It has very good classification performance and can be applied to fault detection, but it may fall into local problems when using neural network for training. Optimum, further may lead to unbalanced identification performance of different faults in fault identification, that is, it can identify certain types of faults well, but the identification effect on other faults is poor

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[0019] In order to make the purpose, technical solution and advantages of the patent of the present invention clearer, the patent of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the patent of the present invention, and are not intended to limit the patent of the present invention. In addition, the technical features involved in the various embodiments of the patent of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0020] A kind of oil-immersed transformer fault diagnosis method based on neural network and decision fusion proposed by the present invention, its flow chart and detection principle diagram are respectively as follows figure 1 and figure 2 shown.

[0021] A neural network and decision-making fusion oil-im...

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Abstract

The invention provides an oil-immersed transformer fault diagnosis method based on a neural network and decision fusion. The method based on the neural network and the decision fusion comprises the steps of fault coding, construction and training of a neural network model, and calculation of a decision fusion matrix. The method comprises the following steps: after encoding fault low-temperature overheating, medium-temperature overheating, high-temperature overheating, partial discharge, low-energy discharge and high-energy discharge, training a plurality of neural networks by using the contentof dissolved gas in five kinds of transformer oil as identification features, and calculating a decision fusion matrix according to the test accuracy of the neural networks to realize decision fusionof the plurality of neural networks. According to the method, the weight of the specific fault in the whole model identification can be adjusted according to the identification performance of the single neural network for the specific fault, so that the accuracy of fault diagnosis is improved, and the method has important significance for timely processing of transformer faults and stable and reliable operation of a power system.

Description

technical field [0001] The invention belongs to the field of transformer fault diagnosis, and in particular relates to a fault diagnosis method for an oil-immersed transformer integrated with neural network and decision-making. Background technique [0002] As the key equipment of the power system, the transformer plays the role of voltage conversion, current conversion, power transmission and so on in the conversion of electric energy. With the gradual expansion of power grid capacity and the rapid development of EHV and UHV technologies, the power grid needs to have higher reliability and safety. Bring inconvenience, also can seriously affect the development progress of national economy. The operating status of the transformer will directly affect the stability, safety, integrity and economy of the power system, so it is of great significance to ensure the safety and stability of the transformer and timely troubleshooting. [0003] Dissolved gas analysis (DGA) in transfo...

Claims

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Application Information

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IPC IPC(8): G01R31/62G06N3/04G06N3/08
CPCG06N3/04G06N3/08
Inventor 罗传仙周正钦龚浩许晓路江翼吴念周文朱诗沁倪辉
Owner WUHAN NARI LIABILITY OF STATE GRID ELECTRIC POWER RES INST
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