摘要
提出了一种用于建造多塔精馏过程故障诊断专家系统知识库的方法。该方法借助于实例，通过基于解释学习（Ｅｘｐｌａｎａｔｉｏｎ－Ｂａｓｅｄ－Ｌｅａｒｎｉｎｇ，ＥＢＬ）的学习模型及定量深层知识库来产生故障诊断领域知识。若用该方法建立专家系统知识库，则相应的专家系统在进行蒸馏系统故障诊断时比较快速、准确。
This paper proposed a method of establishing knowledge base in troubleshooting expert system for multi-column distillation. The proposed method employs the quantitative deep-level knowledge base and the explanation-based learning model to build troubleshooting domain knowledge base by means of examples. The tronble can be diagnosed correctly and rapidly by using the proposed troubleshooting domain knowledge base.
出处
《计算机与应用化学》
CAS
CSCD
1995年第1期7-10,50,共5页
Computers and Applied Chemistry
基金
国家自然科学基金
国家教委博士点基金
关键词
故障诊断
蒸馏系统
多塔精馏
知识库
Expert system,Machine learning, Fault diagnosis, Distillation system, Knowledge acquisition
