融合粗糙集与D-S证据理论的航空装备故障诊断

针对航空电子装备故障诊断中出现的多源诊断信息存在冲突的情况,基于粗糙集与证据理论在处理不确定问题时的优势,提出了一种融合粗糙集与证据理论的故障诊断方法.该方法利用粗糙集将信息源给出的诊断数据转化为证据理论中的mass函数,进行结果融合.同时,该方法给出边界粗糙熵的定义,并基于边界粗糙熵获得反映各信息源在诊断融合过程中重要度的动态权重参数,提出一种新的证据理论的冲突合成规则.仿真实验表明,该方法可以有效地提升诊断信息融合结果的准确性,在航空电子装备故障诊断方面有较好的实用价值.

Avionic devices fault diagnosis based on fusion method of rough set and D-S theory

In order to solve the conflict of multi-sources information in the fault diagnosis process of avionics electric equipment, a method based on rough set theory and evidence theory for fault diagnosis was proposed. Because both rough set theory and evidence theory had advantages in dealing with uncertainty problems. The method proposed converted diagnostic data to mass function which was needed in evidence theory in order to fuse results with rough set theory. Meanwhile, the method defined boundary rough entropy, got dynamic weight parameters which reflected the significance of every information source used in fusion process with the entropy and improve the rule for conflicting evidence combination. The experiment shows that the method improves the fusion results' accuracy of diagnostic information effectively and has a good practical value in process of avionics electric fault diagnosis.