DocumentCode :
2551202
Title :
Semantic integrated condition monitoring and maintenance of complex system
Author :
Jin, Guiyang ; Xiang, Zhanqin ; Lv, Fuzhai
Author_Institution :
Coll. of Mech. & Energy Eng., Zhejiang Univ., Hangzhou, China
fYear :
2009
fDate :
21-23 Oct. 2009
Firstpage :
670
Lastpage :
674
Abstract :
Condition monitoring and maintenance system of capital-intensive plant such as energy, chemical and manufacturing is information-intensive. It needs to integrate process parameters (such as speed, flow rate, etc) from process control systems and component condition monitoring parameters (such as vibration, oil particle size, etc) to improve fault detection, fault isolation and fault identification process. It also needs data (such as asset maintenance history information, spare parts, and costs information) from MES or ERP systems to optimize the maintenance activity decision. In this paper, we introduce ontology and rule to code the condition monitoring and maintenance domain knowledge, and then different applications can use tools (rule engine, reasoner) to manipulate the domain knowledge. In this way, it is easy to accomplish the condition monitoring and maintenance activities, reuse and share the domain knowledge.
Keywords :
computerised monitoring; condition monitoring; fault diagnosis; maintenance engineering; ontologies (artificial intelligence); production engineering computing; semantic Web; ERP systems; MES; asset maintenance history information; capital-intensive plant; complex system maintenance; component condition monitoring; domain knowledge; fault detection; fault identification; fault isolation; process control systems; process parameters; semantic integrated condition monitoring; Chemicals; Condition monitoring; Cost function; Fault detection; Fault diagnosis; History; Manufacturing; Petroleum; Process control; Vibration control; condition monitoring; maintenance; ontology; semantic web;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Engineering and Engineering Management, 2009. IE&EM '09. 16th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-3671-2
Electronic_ISBN :
978-1-4244-3672-9
Type :
conf
DOI :
10.1109/ICIEEM.2009.5344503
Filename :
5344503
Link To Document :
بازگشت