GIS fault detection system and method based on multi-source information fusion and deep learning network

A deep learning network and multi-source information fusion technology, which is applied in neural learning methods, biological neural network models, measurement electronics, etc., can solve the problems of BP and other neural networks that cannot be accurately modeled, and judgment result errors, etc., to increase diagnosis Accuracy, low hardware requirements, and the effect of saving system costs

Inactive Publication Date: 2017-04-26
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

[0006] Aiming at the defects that the neural networks such as BP used in the existing detection methods cannot be accurately modeled, and most detection methods only involve one evaluation mechanism, resulting in large errors in judgment results, the present invention proposes a metho

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  • GIS fault detection system and method based on multi-source information fusion and deep learning network
  • GIS fault detection system and method based on multi-source information fusion and deep learning network
  • GIS fault detection system and method based on multi-source information fusion and deep learning network

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Embodiment Construction

[0025] Such as figure 1As shown, this embodiment includes: a multi-source information collection and conditioning module, a deep learning module, and an information fusion and fault reasoning module, wherein: the multi-source information collection and conditioning module uniformly modulates signals collected by sensor systems corresponding to different signal sources It is a digital signal, uniformly input in the form of a matrix, and through the method of feature extraction, the related vectors are removed to obtain the feature vector of each signal source. Provide input data for the subsequent deep learning module; the deep learning module uses the feature vector input by the multi-source information collection method to carry out the construction of the deep learning network, parameter tuning, input and output calculation operations, and finally draws the identification conclusion corresponding to the multi-source information. There are two working modes of the deep learni...

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Abstract

The invention discloses a GIS fault detection system and a GIS fault detection method based on multi-source information fusion and a deep learning network. The GIS fault detection system comprises a multi-source information acquisition and conditioning module, a deep learning module and an information fusion and fault reasoning module, wherein the multi-source information acquisition and conditioning module performs fault state monitoring on a GIS system by adopting a partial discharge time analysis method, a partial discharge phase analysis method and an ultrahigh frequency method separately, extracts corresponding feature vectors separately from obtained current, voltage and electromagnetic information and outputs the feature vectors to the deep learning module; the deep learning module performs online pattern recognition on the three kinds of feature vectors based on the deep learning network obtained through offline learning optimization to acquire corresponding recognition results, and outputs the recognition conclusions to the information fusion and fault reasoning module; and the information fusion and fault reasoning module carries out fusion processing on the three recognition conclusions to obtain a fault feature matrix, and then obtains a fault conclusion by means of a CLIPS reasoning machine. By adopting the GIS fault detection system and the GIS fault detection method, the fault information of the GIS system can be diagnosed quickly, efficiently and precisely.

Description

technical field [0001] The invention relates to a technology in the field of electrical equipment, in particular to a GIS fault detection system and method based on multi-source information fusion and deep learning network. Background technique [0002] As a form of high-voltage distribution equipment, gas-insulated metal-enclosed switchgear (GIS, Gas Insulated Switchgear) organically combines all the primary equipment in the substation except the transformer into a whole through optimized design, and is enclosed in a metal shell , filled with SF6 gas as an arc extinguishing and insulating medium to form a closed combined electrical appliance, the highest distribution voltage can reach 1100kV. GIS overcomes many limitations of conventional open switchgear, and has the advantages of small footprint, high reliability, strong security, and small maintenance workload, making it possible for high-voltage and ultra-high-voltage power transmission and transformation to directly ent...

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Application Information

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IPC IPC(8): G01R31/12G06K9/62G06N3/08
CPCG06N3/084G01R31/1254G06F18/256
Inventor 李双宏朱琳许振华杨煜普
Owner SHANGHAI JIAO TONG UNIV
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