摘要
依据状态监控信息对民航发动机进行性能排序,可以及时了解发动机性能衰减程度及梯次差异,从而便于制定最优维修计划,达到降低维修费用的目的,因此已成为提高机队管理质量的重要手段.目前航空公司机队管理中对多指标性能排序问题还缺乏科学的方法.该文基于模糊等价聚类和粗糙集理论中的属性信息熵方法,对该类权重信息完全未知的多指标风险决策问题进行理论建模,得到求取各指标综合权重的算法,并举例验证了该算法的客观有效性.
Performance ranking of civil aviation engine based on surveillance information can provide the degree of engine deterioration and stagger difference, make optimal maintenance plan, and reduce maintenance cost. Therefore it has become a critical issue in improving fleet management.＇ However rational methods for evaluating engine＇s overall performance in civil aviation management are unavailable. This paper establishes a theoretical model and proposes an algorithm to distribute all parameter weights based on a fuzzy equivalent aggregation technique and attribute information entropy of rough set theory when multi-attribute weight information are unknown. As an example, the algorithm has been verified in performance ranking of ten CF6 engines from a civil aviation company. The result shows that the method is objective and effective.
出处
《应用科学学报》
CAS
CSCD
北大核心
2006年第3期288-292,共5页
Journal of Applied Sciences
关键词
民航发动机
多指标
性能排序
模糊理论
信息熵
aeroengine
multi-parameter
performance ranking
fuzzy theory
information entropy
