基于范例推理的智能故障诊断在机载系统中的应用研究  

The Application Research of Intelligent Fault Diagnosis Based on CBR in Airborne System

作　　者：田存英 邱冬 

机构地区：[1]航空工业第一飞机设计研究院,陕西西安710089

出　　处：《航空科学技术》2017年第12期68-72,共5页Aeronautical Science & Technology

摘　　要：为了实现机载系统故障诊断的自动化与智能化,构造了以粗糙集为理论基础、基于范例推理(CBR)的智能故障诊断模型,并将其应用于机载武器系统发射故障诊断中,对机载武器系统发射故障诊断模型进行仿真分析。结果表明,CBR的智能故障诊断模型理论可行,具有较高的准确率,使用该方法可以对机载系统进行故障诊断。In order to realize the automation and intelligentization of airborne system fault diagnosis, an intelligent fault diagnosis model based on CBR and rough set theory was constructed and applied in the launching fault diagnosis of airborne weapon system. The fault diagnosis model of airborne weapon system was simulated and analyzed. The results show that the intelligent fault diagnosis model based on CBR is feasible and highly accurate. This model can be used for fault diagnosis of airborne system.

关 键 词：故障诊断 人工智能 范例推理 粗糙集 

分 类 号：V267[航空宇航科学与技术—航空宇航制造工程]