{"title":"The Intelligent Integration System of Oil Equipment Information","authors":"Qingzhong Zhou, Huie Zeng","doi":"10.1109/IHMSC.2013.121","DOIUrl":null,"url":null,"abstract":"It is the urgent problem in POL support, that the reliability of the oil equipment (OE) is ensured, and its information resources are used effectively. Therefore, the intelligent integrated systems for the OE's information is researched. By analyzing the research goals and using the design philosophy of Service-Oriented Architecture, the system architecture is built, which is divided into four levels, i.e. user level, application integration level, technical support level, and support platform level. The main function modules are discussed. The detected data of OE's condition is fused using neural network and evidence theory. OE's fault is diagnosed using the case-Based reasoning and the rule-Based reasoning. The maintenance decision is realized using the hybrid approach, in order to ensure the performance goals of OE's maintenance. It is expounded that this research has an important role to improve the rapid response capability in POL support.","PeriodicalId":222375,"journal":{"name":"2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IHMSC.2013.121","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
It is the urgent problem in POL support, that the reliability of the oil equipment (OE) is ensured, and its information resources are used effectively. Therefore, the intelligent integrated systems for the OE's information is researched. By analyzing the research goals and using the design philosophy of Service-Oriented Architecture, the system architecture is built, which is divided into four levels, i.e. user level, application integration level, technical support level, and support platform level. The main function modules are discussed. The detected data of OE's condition is fused using neural network and evidence theory. OE's fault is diagnosed using the case-Based reasoning and the rule-Based reasoning. The maintenance decision is realized using the hybrid approach, in order to ensure the performance goals of OE's maintenance. It is expounded that this research has an important role to improve the rapid response capability in POL support.