摘要
作为视情维修(CBM)的关键环节,状态评估对装备后续CBM决策工作具有重要影响。为了使状态评估更加准确合理,针对现有评估方法主观性较强等问题,提出一种基于云模型与D-S证据理论(DST)的装备状态评估模型。第一步利用云模型求取状态指标的隶属度,第二步进行证据源修正,最后通过D-S证据理论融合装备多个测试指标得到评估结果。通过雷达导引头状态评估实例分析,验证了新方法的合理性。
As the key link of Condition-Based Maintenance（ CBM）,condition assessment has an important influence on the subsequent CBM decision-making of equipment. In order to make the status assessment more accurate and reasonable,a method of equipment condition assessment based on cloud model and D-S evidence theory is put forward to overcome the strong subjectivity of existing evaluation methods. The first step is to use the cloud model to obtain the membership degree of the state index,and the second step is to modify the source of the evidence. Finally,the multiple evaluation indexes are fused by D-S evidence theory,and the evaluation results are obtained. The rationality of the new method is verified by the example analysis of radar seeker condition evaluation.
作者
逯程
徐廷学
王虹
LU Cheng;XU Ting-xue;WANG Hong(Department of Ordnance Science and Technology, Naval Aeronautical University, Yantai 264001, China;No. 55 Institute, Joint Staff Department, Beijing 100094, China)
出处
《电光与控制》
北大核心
2018年第6期44-47,共4页
Electronics Optics & Control
基金
国家自然科学基金(51605487)
山东省自然科学基金(ZR2016FQ03)
关键词
状态评估
故障诊断
云模型
灰靶贡献度
D-S证据理论
雷达导引头
condition assessment
fault diagnosis
cloud model
grey target contribution degree
D-S evidence theory
radar seeker
