摘要
针对当前装备维修质量评价忽视维修过程影响因素的问题,将过程评价指标体系作为修后评价指标体系的先验知识,构建了一种基于贝叶斯网络的复杂装备维修质量评价模型。首先,建立了过程评价指标体系和修后评价指标体系,并对各项指标进行了简要分析;然后,建立了维修质量评价的贝叶斯网络模型,通过模糊综合评价方法确定了根节点的先验概率,通过专家经验法确定了子节点的条件概率,并给出了模型的具体求解步骤;最后,通过算例仿真与分析对提出的方法进行了验证。结果表明:该方法能够在一定程度上解决复杂装备的维修质量评价问题,为完善复杂装备的维修质量评价理论提供了借鉴。
Considering the problems that influence factors in repair process are always ignored while conducting the maintenance quality assessment, this paper studies a maintenance quality assessment method for complex equipment based on Bayesian network by taking the procedural indicator system as a prior knowledge of the repaired indicator system. Firstly, the procedural and repaired indicator systems are built and simple analysis of the indexes is given. Secondly, a maintenance quality assess- ment model based on Bayesian network is built, and the prior probability and conditional probability are also confirmed by fuzzy comprehensive evaluation method and the expert experience method respectively. Finally, simulations and analysis of one instance are conducted to verify the proposed method. The results show that the proposed method can solve the problem of maintenance quality assessment for complex electronic equipment to a certain extent, and it can also provide a reference to perfecting the maintenance quality assessment theory.
出处
《海军工程大学学报》
CAS
北大核心
2017年第1期84-90,共7页
Journal of Naval University of Engineering
基金
国家部委基金资助项目(KJ2014023200B11145)
关键词
复杂装备
维修质量评价
贝叶斯网络
熵权
模糊综合评价
指标体系
complex equipment
maintenance quality assessment
Bayesian network
entropy weight
fuzzy comprehensive evaluation
indicator system
