基于粗糙集的机载电子设备故障检测专家系统的改进

The Improvement of Airborne Electronic Equipment Fault Diagnosis Expert System Based on Rough Set

由于机载电子系统的故障征兆和故障原因之间的对应关系较为复杂,设备故障诊断领域的某些经验性专家知识具有一定的模糊性和不确定性,因此本文利用粗糙集理论较强的数据分析能力和容错性,通过对专家系统中存在的冗余信息进行约简并剔除不必要的属性,降低了故障诊断专家系统构成的复杂性,并明显改善了专家系统的整体效能.

For the corresponding relationship between the fault symptom and fault inducement in the airborne electronic is complex,some experiential expert knowledge in equipment fault diagnosis field is ambiguous and uncertain to some extent.The strong data analysis ability and fault tolerant ability of the Rough Set Theory is utilized in the paper,the redundancy information in the expert system is wiped off and the unnecessary properties are eliminated,so the complexity of the fault diagnosis expert system is reduced and the overall efficiency of the expert system is improved.