Evaluation system of transformer state based on multisource information integration and evaluation method thereof

Abstract

The invention relates to an evaluation system of transformer state based on multisource information integration and an evaluation method thereof, wherein, the evaluation system in the invention is composed of an oil chromatographic analysis subsystem, a partial discharge ultrahigh frequency signal detection subsystem, a winding deformation vibration signal detection subsystem, a current transformer detection subsystem and a computer; the technical point of the evaluation method in the invention lies in evaluating the running state of a detected transformer by fusing the detection results obtained by the detection methods utilized by the four detection subsystems by utilizing a D-S evidence theory fusion evaluation algorithm. The beneficial effects of the invention lie in being capable of timely discovering and accurately judging the malfunction of transformer and comprehensively reflecting the running state of a transformer.

Description

technical field [0001] The invention relates to a transformer state evaluation system and evaluation method based on multi-source information fusion, which is suitable for fault detection of oil-immersed power transformers. Background technique [0002] At present, there are many methods for fault detection of oil-immersed power transformers, and the more commonly used methods are as follows: [0003] (1) Oil chromatography analysis method using fuzzy kernel clustering and support vector machine fault diagnosis algorithm: [0004] The gas dissolved in the insulating oil of the transformer is detected by a chromatographic analyzer, and the contents of methane, ethane, ethylene, propylene, hydrogen, acetylene, carbon monoxide and carbon dioxide are analyzed by a chromatographic analyzer, and converted into digital signals. The kernel clustering algorithm clusters the training samples, and then puts all kinds of sample data with correct clustering into the support vector machi...

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Problems solved by technology

[0012] At present, the fault detection of oil-immersed power transformers is to independently use one of the above four methods to detect the transformer, because each of the above four detection methods is aimed at one or some faults and abnormal operation Therefore, each method cannot fully reflect the operating state of a transformer under test, but can only reflect one side, that is, it cannot fully characterize the working condition of the transformer under test.

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