基于粗糙集的装载机液压系统故障诊断专家系统知识获取研究

Fault Diagnosis Expert System Rule Attaining for Loader Hydraulic System Based on Rough Set

针对当前专家系统知识获取瓶颈的难题,提出一种基于粗糙集的装载机液压系统故障诊断专家系统知识获取模型。将装载机液压系统的故障历史数据离散化,构建故障诊断决策表,通过粗糙集数据挖掘算法获取故障诊断的最小约简属性集和潜在的诊断规则,并建立诊断规则知识库。以ZL50型装载机液压系统中的齿轮泵故障分析为例进行了验证。

A novel mode for fault diagnosis of loader hydraulic system based on rough set（RS） data mining theory is brought forward aimed at overcoming shortages of some current knowledge attaining methods. The historical fault data of loader hydraulic system is processed with scatter method. The processed data is used to structure the fault diagnosis decisionmaking table. Introduced rough sets data mining method to take smallest reduction attribute collection and potential diagnosis rule from the fault diagnosis decision - making table of loader hydraulic system. An example of fault analysis of ＂gear pump of ZL50 loader hydraulic system＂ was verified.