基于粗糙集理论的机械故障诊断方法研究  

Study of Machinery Fault Diagnosis Based on RS Theory

作　　者：王树梅[1] 吴天荣[1] 

机构地区：[1]同济大学CAD中心

出　　处：《煤矿机械》2007年第3期176-178,共3页Coal Mine Machinery

摘　　要：机械故障诊断中存在着许多不确定性和知识冗余性,而粗糙集理论是一种新型的处理不确定性信息的数学工具,粗糙集理论提供了对机械故障进行诊断全新的有效途径。将基于可变精度粗糙集模型应用于故障诊断,同时与遗传算法相结合,在保证诊断精度大致不变的情况下对故障征兆属性化简,消除诊断规则判断条件的冗余,获取精简的规则。实例证明了基于粗糙集理论的机械故障诊断方法的可行性。There exists a lot of uncertainty and redundant knowledge in machinery fault diagnosis, while rough set theory is a new mathematical tool to deal with uncertain information. And a new effective approach is provided for machinery faulty diagnosis by applying RS theory. Variable precision rough set model combined with genetic algorithm is applied to reduce the number of fault attribute on the condition that the diagnosing precision is almost not changed, and the redundancy of antecedent of rules is eliminated to acquire more concise rules. The experiment proves the validity of machinery fault diagnosis based on RS theory.

关 键 词：粗糙集理论 机械故障诊断 可变精度粗糙集模型 遗传算法 属性约简 

分 类 号：TD441.1[矿业工程—矿山机电] TP306.3[自动化与计算机技术—计算机系统结构]