摘要
为了进一步加强武器装备维修管理,引入基于状态的维修(Condition Based Maintenance,CBM)概念,介绍了装备健康评估技术的研究现状;在此基础上,为了克服单一BP神经网络无联想记忆功能的缺点,引入Hopfield网络加以组合,构建了组合神经网络状态的评估模型,提出了状态评估的具体步骤,并进行可行性分析;最后,以某型飞机发动机燃油控制系统为例进行了健康状态评估,取得了较为理想的评估效果。
The concept of Condition Based Maintenance （CBM）was introduced for maintenance management of military equipment. The current situation of study on health condition assessment of equipment was analyzed. Since the single BP neural network has no associative memory capability, the Hopfield network was introduced to construct a combined neural network for condition assessment. The detailed steps for health condition assessment were presented and the feasibility was analyzed. Finally, the health condition assessment was implemented taking the fuel control system of a certain aero-engine as an example, and the result was satisfactory.
出处
《电光与控制》
北大核心
2011年第12期84-88,共5页
Electronics Optics & Control
关键词
状态维修
组合神经网络
状态评估
武器装备
Condition Based Maintenance （CBM）
combined neural network
condition assessment
military equipment
