基于粗糙集理论的旋转机械故障诊断方法

Fault Diagnosis Method of Rotating Machinery Based on Rough Set Theory

粗糙集理论是一种新的数据分析和处理方法,使用粗糙集理论可以对决策表进行简化,去除冗余属性。该文针对旋转机械故障诊断问题,计算旋转机械振动故障数据库中的频域征兆,使用粗糙集理论对其进行约简,根据约简的结果生成规则。利用得到的规则对故障样例进行诊断。结果表明:使用粗糙集理论可以在保留分类能力不变的前提下,去掉诊断中的不重要的要素,保留重要的要素,从而可以简化对诊断信息的需求。对故障样例的诊断结果也表明:得到的规则基本上是可信的。

Rough set theory is a new method for analyzing and dealing with uncertain and incomplete data. By using rough set theory, decision table can be simplified and redundant attributes can be cut off. According to a vibration fault database, a rotating machinery fault diagnosis approach based on rough set theory is proposed in this paper. The spectrum symptoms are calculated and reducted and rules generated from the reduct. The rules are used to diagnosis some fault examples. It shows that rough set theory can cut off unimportant factor with the class capability unchanged. The result also shows that the rules are mostly reliable. Tables 5 and refs 8.