摘要
针对传统齿轮箱智能诊断系统获取知识的困难,提出了基于案例(case-based reasoning,CBR)和规则(rule-based reasoning,RBR)混合推理方式的智能诊断技术.在研究此2种推理技术优缺点的基础上,取长补短,合理地将其应用到轧机齿轮箱故障诊断工作中,提高了故障诊断的准确率和效率.针对传统案例检索中相似度算法的不足之处,提出了一种新的案例检索算法,有效地解决了传统的相似度算法检索案例不准确的问题.
Due to the difficulty of knowledge accessing in traditional gear-box intelligent diagnosis system, a diagnosis technology based on CBR （Case-based Reasoning） and RBR （Rule-based Reasoning） hybrid method was proposed in this paper. On the basis of analyzing the advantages and disadvantages of the two methods, the combination of the reasoning technologies was utilized in fault diagnosis of gearbox of rolling mills. As a result, the accuracy and efficiency of fault diagnosis were improved greatly. Due to the shortage in similarity algorithm in traditional retrieval, a new case retrieval algorithm was proposed. Therefore, the problem of inaccuracy in traditional similarity algorithm was solved effectively.
出处
《北京工业大学学报》
EI
CAS
CSCD
北大核心
2010年第9期1174-1180,共7页
Journal of Beijing University of Technology
基金
国家自然科学基金资助项目(50705001)
关键词
轧机齿轮箱
智能诊断
案例推理
规则推理
gearbox of the rolling mills
intelligent diagnosis
case-based reasoning
rule-based reasoning
