融合粗糙集和证据理论的车地无线通信设备故障诊断

Fault Diagnosis Method for TrainGround Wireless Communication Unit Based on Fusion of Rough Sets and Evidence Theory

摘要:

针对车地无线通信设备故障诊断信息不一致的情况进行故障推理和诊断,提出了一种融合粗糙集与证据理论综合集成的车地无线通信设备故障诊断方法.该方法首先利用粗糙集剔除故障特征数据的冗余成分,提取互不相关的必需特征,将车地无线通信设备故障诊断问题用一个不同简化层次的故障决策网络表示,由网络节点根据定义出的规则置信度和覆盖度可推导出对应有效的故障诊断规则集合.在建立规则库的基础上,引入基于证据理论的信息融合技术,解决多传感器故障监测数据与诊断规则准确匹配的问题,建立故障推理机制,便可方便得出车地无线通信单元故障诊断结果,实例分析表明该方法能有效提高模型故障诊断能力,具有较强实用性.

Abstract:

Under the condition of inconsistent fault diagnosis information,fault diagnosis reasoning fusion strategy integrating rough sets and evidence theory method for trainground wireless communication unit of communicationbased train control (CBTC) is proposed.By using rough sets,redundant part of characteristic data is eliminated and irrelevant indispensable characters are extracted.Then,a decision network with different reduced levels is constructed to denote the fault diagnosis problems of the trainground wireless communication (TGWC) unit by way of the definition of the rule confidence and coverage degree.Finally,a fault identification mechanism based on evidence theory is presented to process fault data collected by various sensors and exactly match them with diagnosis rules.Results show that with the diagnosis model,the ability of model fault diagnosis is improved with strong practicality.