SF6 electrical device fault diagnosis method

A fault diagnosis and electrical equipment technology, applied in the security field, can solve problems such as low diagnosis efficiency, and achieve the effect of reducing the requirements of professional skills, strong adaptive ability, and easy parameter training

Inactive Publication Date: 2015-12-16
刘利强
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Problems solved by technology

[0005]Aiming at the problem that the current SF6 electrical equipment fault diagnosis method will cause low diagnostic efficiency when applied to a large number of equipment, a SF6 electrical equipment that can improve the diagnostic efficiency is proposed Troubleshooting method

Method used

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  • SF6 electrical device fault diagnosis method
  • SF6 electrical device fault diagnosis method
  • SF6 electrical device fault diagnosis method

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Embodiment Construction

[0047] A preferred embodiment of the present invention will be described below with reference to the accompanying drawings.

[0048] Adaptive Network-based Fuzzy Inference System (ANFIS for short), also known as network-based adaptive fuzzy inference system; it combines the learning mechanism of artificial neural network (ANN) and the language reasoning ability of fuzzy system, etc. Compared with other fuzzy neural systems, the prediction accuracy of ANFIS is higher than that of ordinary neural networks, and the training time is significantly less than that of artificial neural networks with backpropagation method.

[0049] It is the combination of neural network and Sugeno type fuzzy reasoning system. The reason why the Sugeno type fuzzy reasoning system is used is that the system has the advantages of simple calculation and favorable mathematical analysis, and is suitable for data-based modeling methods, and is easy to combine with optimization and self-adaptive methods...

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Abstract

The present invention provides an SF6 fault diagnosis system and method. The system comprises: a training unit, used for performing training by means of an ANFIS algorithm according to training data to obtain a basic fault diagnosis fuzzy neural inference model; a test unit, used for testing the basic fault diagnosis fuzzy neural inference model according to test data to determine a diagnosis accuracy rate of the basic fault diagnosis fuzzy neural inference model, and adjusting the basic fault diagnosis fuzzy neural inference model according to the diagnosis accuracy rate to obtain a fault diagnosis fuzzy neural inference model; and a diagnosis unit, used for inputting to-be-diagnosed data into the fault diagnosis fuzzy neural inference model and performing fault diagnosis on an SF6 electrical device corresponding to the to-be-diagnosed data.

Description

technical field [0001] The invention relates to the field of safety technology, in particular to a fault diagnosis method for SF6 electrical equipment. Background technique [0002] Gas has excellent physical and chemical properties and insulation and arc extinguishing properties, so it is widely used as an insulating medium in electrical equipment, such as gas-insulated switchgear (GIS). Therefore, the safe and reliable operation of SF6 gas equipment is directly related to the safe and reliable operation of the power system. [0003] Long-term operating experience shows that there may be some defects inside SF6 electrical equipment. These defects are harmless and not easy to find at first, but as time goes by, these defects will gradually develop into equipment failures and affect the safe and reliable operation of the system. accident hazards. [0004] In the prior art, the corresponding relationship between the operating state of SF6 electrical equipment and the decompo...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/08G06N7/02
Inventor 刘利强王姣王连旌
Owner 刘利强
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