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机队设备可靠性是实现航空公司“安全、正点和经济”目标的核心内容,对其进行评估是实现机队设备系统综合技术保障的重要手段。根据航空公司机队设备可靠性统计、数据采集和监控方式的关键技术与重要环节,应用物理-事理-人理(WSR)思想和Delphi法,建立了机械原因使用困难报告(SDR)和非计划停场率等航空公司机队设备可靠性的5大指标体系。基于灰色聚类方法和反步(BP)神经网络的优缺点,结合机队设备可靠性的随机性和波动性,设计了航空公司机队设备可靠性非线性动力学评估模型。航空公司机队设备可靠性评估实例的分析表明:该可靠性非线性动态评估模型是可行的,能够实现动态和静态的评估。
The reliability of fleet equipment is the key to achieving the goal of airlines “safety, punctuality and economy”. Evaluation of fleet equipment is an important means to achieve comprehensive technical support for fleet equipment systems. According to the key technologies and important links of airlines’ fleet equipment reliability statistics, data acquisition and monitoring methods, the use of physical-business-human (WSR) ideas and the Delphi method, the establishment of a mechanical cause of difficulty reporting (SDR) and unplanned Stop rate and other aviation fleet equipment reliability of the five major indicators system. Based on the advantages and disadvantages of gray clustering method and BP neural network, the reliability nonlinear model of airline fleet equipment is designed based on the randomness and volatility of fleet reliability. The analysis of the example of airline fleet reliability evaluation shows that this reliability nonlinear dynamic assessment model is feasible and can realize the dynamic and static assessment.