Framework of Knowledge Acquisition and Representation Reasoning for Gas Turbine Health Maintenance

被引：1

作者：

Wang Z. ^{[1
]}

Gu Y. ^{[1
]}

Han X. ^{[1
]}

Sun S. ^{[1
]}

Zhu J. ^{[1
]}

Huang Y. ^{[2
]}

机构：

[1] National Thermal Power Engineering & Technology Research Center, North China Electric Power University, Beijing

[2] Guangdong Yudean Zhongshan Thermal Power Limited Company, Zhongshan

来源：

Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2021年 / 32卷 / 02期

关键词：

Gas turbine; Health maintenance; Knowledge acquisition; Knowledge representation and reasoning;

D O I：

10.3969/j.issn.1004-132X.2021.02.015

中图分类号：

学科分类号：

摘要：

Aiming at the problems of incomplete knowledge collection, poor knowledge portability, and inefficient knowledge reasoning in current gas turbine health maintenances, a systematic framework for knowledge acquisition, expression, and reasoning was proposed. Firstly, using combination of failure mode and effect analysis, and fault tree analysis, necessary expert knowledge of gas turbine health diagnosis was obtained from different perspectives. Secondly, acquired expert knowledge was structured, expressed and managed based on ontology modeling. The combination of ontology axioms and custom rules was used to realize searching and reasoning of fault knowledge. Finally, a real gas turbine was selected as an example to illustrate the application of knowledge engineering framework in gas turbine health maintenance systems. © 2021, China Mechanical Engineering Magazine Office. All right reserved.

引用

页码：235 / 241

页数：6

共 25 条

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