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Primary equipment defect diagnosis and prediction method

A technology for defect diagnosis and primary equipment, applied in prediction, neural learning methods, biological neural network models, etc.

Active Publication Date: 2021-09-24
GUIZHOU POWER GRID CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is: provide a kind of equipment defect diagnosis and prediction method, to solve the technical problems existing in the prior art

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  • Primary equipment defect diagnosis and prediction method
  • Primary equipment defect diagnosis and prediction method

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Embodiment 1

[0058] Embodiment 1: A method for diagnosing and predicting primary equipment defects, the method includes a defect reporting data governance method based on an expert system algorithm, a deep learning-based intelligent risk assessment method for primary equipment, and a data mining-based primary equipment defect prediction model prediction The method is as follows: firstly, the omission and wrong filling of the key information in the defect reporting data and the problems of extracorporeal circulation are dealt with; Construct a defect standard library based on the cause, treatment measures, and operation data when the defect occurs; Based on the defect standard library, use neural network and semantic analysis technology to discriminate and diagnose the location, cause and severity of the new defect data; According to the defect diagnosis results , Combined with equipment defect aging factor, alarm factor, insulation performance factor, equipment importance, defect level, vol...

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Abstract

The invention discloses a primary equipment defect diagnosis and prediction method. The method comprises the following steps: treating defect filling data; building a defect standard library for defect description, defect representation, defect reasons, processing measures and operation data when defects occur by adopting a natural language processing technology on the basis of the treated data; based on the defect standard library, judging and diagnosing the part, the reason and the severity of the new defect data by adopting a neural network and semantic analysis technology; according to a defect diagnosis result, in combination with data such as an equipment defect aging factor, an alarm factor, an insulation performance factor, an equipment importance degree, a defect grade and a voltage grade, evaluating the risk grade of the equipment through a correlation analysis and comprehensive evaluation algorithm; and adopting a time sequence algorithm and Markov correlation analysis prediction. The method can improve the precision and depth of the model, makes up for the defects of the existing research, guarantees the availability of the model, and solves the problem of uncontrollable cost loss caused by the defects to the equipment risk.

Description

technical field [0001] The invention relates to the technical field of equipment risk assessment, in particular to a method for diagnosing and predicting primary equipment defects. Background technique [0002] With the rapid development of power grid modernization, smart grid has become the embodiment of the development and transformation of power and energy industries in the world today. The Ministry of Science and Technology of my country clearly pointed out that the smart grid is an important platform for implementing new energy strategies and optimizing the allocation of energy resources. At this stage, the development of my country's power grid has begun to transition to intelligence, and the goal of building a "unified and strong" smart grid has been proposed. In the process of smart grid construction, the intelligent management and control of power grid equipment has become the primary task of building a smart grid. The transformation from manual inspection to condit...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06F16/215G06N3/04G06N3/08G06Q50/06
CPCG06Q10/04G06F16/215G06Q10/0635G06Q10/06393G06N3/08G06Q50/06G06N3/045
Inventor 黄军凯张迅文屹吕黔苏赵超刘君陈沛龙丁江桥吴建蓉范强
Owner GUIZHOU POWER GRID CO LTD
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