【摘要】 机队作为航空公司运输能力的主体,其可靠性状态直接影响到航空公司的经济效益。在分析航空公司机队可靠性日常数据统计、采集方式以及管理的基础上,综合考虑维修可靠性方案和日常运行状态监控方案等,应用Delphi法,选取了使用困难报告(SDR)、机队可利用率、非计划停场率、日利用率、不正常千次率、故障率和部件非计划拆换率这7个参数作为航空公司机队可靠性指标,并确立了指标分级标准。针对航空公司机队可靠性指标具有模糊性、随机性和复杂性的特征,应用属性区间识别理论,建立了航空公司机队可靠性状态属性区间识别模型。为了克服指标权重的主观性问题,运用熵权法确定指标权重系数。最后分别应用属性灰色贴近度、属性置信度准则、灰色聚类和模糊模式对航空机队可靠性进行危险状态等级识别和结果分析。实例分析表明,熵权属性区间灰色贴近度识别方法更为简单、可靠和客观,为航空公司机队可靠性状态识别提供了一种科学识别方法。更多还原

【Abstract】 Air flight fleet is the central part of the transportation ability of an airline,and its status of reliability affects the economic benefits directly.According to the analysis of routine data statistics,acquisition data modes,data management of the reliability of the airline fleet,this paper studies the project of maintenance reliability and daily running status monitoring of fleet operation,seven indicators of airline fleet reliability are set up by the Delphi method,including service difficulty report(SDR),availability of fleet,rate of nonscheduled down,aircraft utilization ratio,abnormal thousand-time rate,failure rate and unscheduled replacement rate of parts.The paper establishes a grading standard of the indicator systems of airline fleet reliability.In view of its fuzziness,randomness and complexity,the attribute interval recognition model of the reliability of airline fleet is established based on attribute interval recognition theory.To eliminate the subjectivity of indicator weight,the weight coefficient is determined by the entropy weight method.Finally,the identification of risk status grade and the analysis of results on the reliability of airline fleet is performed by attribute grey close degree,attribute confidence level rule,grey clustering method and fuzzy pattern recognition respectively.The case study shows that the entropy weight attribute interval grey close degree recognition method is comparatively simple,reliable and objective,and it supplies a scientific method to recognize the status of airline fleet reliability.更多还原