文献类型：期刊文献

中文题名：Equipment selection knowledge base system for industrial styrene process

英文题名：Equipment selection knowledge base system for industrial styrene process

作者：Weimin Zhong[1];Shuming Liu[1];Feng Wan[1];Zhi Li[1]

机构：[1]Key Laboratory of Advanced Control and Optimization for Chemical Processed of Ministry of Education, East China University of Science and Technology

年份：2018

卷号：26

期号：8

起止页码：1707

中文期刊名：Chinese Journal of Chemical Engineering

外文期刊名：中国化学工程学报（英文版）

收录：CSTPCD;;Scopus;CSCD:【CSCD2017_2018】；

基金：Supported by the National Science Foundation China(61422303);National Key Technology R&D Program(2015BAF22B02);the Development Fund for Shanghai Talents

语种：英文

中文关键词：Equipment selection;Ontology technology;Knowledge base system;Styrene process

外文关键词：知识库系统;设备选择;工业过程;苯乙烯;技术人员;推理引擎;应用程序;规则集合

摘要：Equipment selection for industrial process usually requires the extensive participation of industrial experts and technologists, which causes a serious waste of resources. This work presents an equipment selection knowledge base system for industrial styrene process(S-ESKBS) based on the ontology technology. This structure includes a low-level knowledge base and a top-level interactive application. As the core part of the S-ESKBS, the low-level knowledge base consists of the equipment selection ontology library, equipment selection rule set and Pellet inference engine. The top-level interactive application is implemented using S-ESKBS, including the parsing storage layer, inference query layer and client application layer. Case studies for the industrial styrene process equipment selection of an analytical column and an alkylation reactor are demonstrated to show the characteristics and implementability of the S-ESKBS.
Equipment selection for industrial process usually requires the extensive participation of industrial experts and technologists, which causes a serious waste of resources. This work presents an equipment selection knowledge base system for industrial styrene process（S-ESKBS） based on the ontology technology. This structure includes a low-level knowledge base and a top-level interactive application. As the core part of the S-ESKBS, the low-level knowledge base consists of the equipment selection ontology library, equipment selection rule set and Pellet inference engine. The top-level interactive application is implemented using S-ESKBS, including the parsing storage layer, inference query layer and client application layer. Case studies for the industrial styrene process equipment selection of an analytical column and an alkylation reactor are demonstrated to show the characteristics and implementability of the S-ESKBS.