摘要
为满足专家系统在故障诊断过程中的智能化的要求,提出基于本体自主学习的故障诊断专家系统架构,定义故障诊断知识结构,并构建与之相对应的结构本体和核心故障本体;在设计故障诊断数据仓库的基础上,用机器学习中的决策树和Apriori算法从数据仓库中挖掘故障知识,实现本体自主学习。并以农机液压系统为原型,开发了基于本体自主学习的农机液压故障诊断专家系统。
In order to meet intelligent requirement during fault diagnosis by expert system,the structure of fault diagnosis expert system based on self-learning ontology was proposed.The fault diagnosis knowledge structure was defined and the relevant structure ontology and core fault ontology were constructed.Based on design of data warehouse of fault diagnosis,the decision tree in machine learning and Apriori algorithm were used to acquire fault knowledge to realize ontology self-learning.Taking the hydraulic system of agricultural machinery as a prototype,the hydraulic fault diagnosis expert system was developed based on self-learning ontology.
出处
《机床与液压》
北大核心
2011年第9期142-145,141,共5页
Machine Tool & Hydraulics
基金
江西省自然科学基金资助项目(2009GZS0015)
江西省教育厅科技攻关资助项目(GJJ10467)
国家高技术研究发展计划资助项目(2009AA04Z106)
