Hydroelectric unit fault diagnosis method and system based on knowledge map of fusion features

A technology for hydroelectric generating units and knowledge graphs, applied in information technology support systems, special data processing applications, data processing applications, etc. performance, improve accuracy and stability, and ensure the effect of stability

Active Publication Date: 2021-02-12
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

[0005] In view of the defects of the prior art, the purpose of the present invention is to solve the technical problems of difficulty in fusion and utilization of various fault information, low accuracy and stability in the fault diagnosis method of the prior art

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  • Hydroelectric unit fault diagnosis method and system based on knowledge map of fusion features
  • Hydroelectric unit fault diagnosis method and system based on knowledge map of fusion features
  • Hydroelectric unit fault diagnosis method and system based on knowledge map of fusion features

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Embodiment Construction

[0039] In order to make the object, technical solution and advantages of the present invention clearer, 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 present invention, not to limit the present invention.

[0040] Unstructured text data such as hydropower unit test reports, maintenance reports, and inspection records contain a large amount of high-value fault knowledge. Reasonable extraction of textual fault knowledge is of great significance to improve the effectiveness of unit fault diagnosis. The key issue of knowledge extraction for fault diagnosis texts of hydropower units is to extract effective structured information from heterogeneous text unstructured data. At present, the focus of its research is to identify and Entity relationship extraction.

[0041] Such as figure 1 As shown, a hydroele...

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Abstract

The invention discloses a fault diagnosis method and system for a hydroelectric unit based on a knowledge graph of fusion features, and belongs to the technical field of fault diagnosis. Including: extracting the structured vibration data features of the hydropower unit according to the vibration data of the hydropower unit; extracting the unstructured text data features of the hydropower unit according to various diagnosis reports of the hydropower unit; The text data features are fused with heterogeneous knowledge to obtain fusion features; according to the fusion features, a knowledge graph of hydropower unit fault diagnosis is constructed; according to the knowledge graph of hydropower unit fault diagnosis and the current state characteristics of hydropower units, the current state of hydropower units is reasoned and diagnosed. The present invention constructs a two-layer structure of hydropower unit fault diagnosis knowledge map by fusing structured data and unstructured data, which not only ensures the rational and full utilization of text and data knowledge, but also effectively guarantees that under the condition of data update The stability of the map.

Description

technical field [0001] The invention belongs to the technical field of fault diagnosis of hydroelectric units, and more particularly relates to a method and system for fault diagnosis of hydroelectric units based on a knowledge map of fusion features. Background technique [0002] Whether the operation status of the hydroelectric generating set is safe and reliable is directly related to whether the hydropower station can provide reliable power safely and economically, and is also directly related to the safety of the hydropower station itself. With the development of science and technology, the fault diagnosis of hydroelectric generator sets is gradually developing from manual diagnosis to intelligent diagnosis, from offline diagnosis to online diagnosis, and from on-site diagnosis to remote diagnosis. [0003] The core of fault diagnosis is feature extraction, and classifiers are used to classify faults after feature extraction. At present, there are mainly fault tree fau...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/00G06Q50/06G06F16/36
CPCG06Q10/20G06Q50/06G06F16/367Y04S10/50
Inventor 李超顺陈昊赖昕杰胡鑫侯进皎陈德树
Owner HUAZHONG UNIV OF SCI & TECH
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