【摘要】 为了在故障诊断信息不一致的情况下提取简单有效的诊断规则,提出了一种基于粗糙集理论的决策规则提取方法。该方法从定义的故障诊断决策系统出发,将故障诊断问题用一个具有不同简化层次的决策网络表示,在引入诊断决策规则的覆盖度概念后,推导出每个网络节点的诊断决策规则集。在应用网络进行故障诊断时,用待诊实例的信息与网络中相应节点的诊断决策规则集进行匹配,即使在故障诊断信息不完备的情况下,也能得到正确的诊断结果。以某往复机械故障为例验证了该方法的有效性。更多还原

【Abstract】 In order to extract simple and effective diagnostic rales from inconsistent diagnostic information, an extraction method of decision rules for fault diagnosis based on rough set theory is proposed. According to the definition of fault diagnosis decision system, a decision network with different reduced levels is constructed to denote the fault diagnosis problems. The diagnostic decision rules at each node are deduced by introducing the coverage factor of diagnostic decision rules. When the decision network is applied to fault diagnosis of a new case, the diagnostic conclusion is obtained by matching the information of the new case with the diagnostic decision rules of the relative network nodes. Even when the information of fault diagnosis is incomplete, the diagnosis results are correct. The availability of this method is proved by a fault diagnosis example of reciprocating machines.更多还原