项目名称: 亚健康理论方法在空管运行安全管理中的应用研究
项目编号: No.U1533112
项目类型: 联合基金项目
立项/批准年度: 2016
项目学科: 无线电电子学、电信技术
项目作者: 岳仁田
作者单位: 中国民航大学
项目金额: 32万元
中文摘要: 空管系统是一个对安全性要求极高的运行系统。目前,关于空管运行安全管理理论方法的研究主要集中空管风险管理方面,而侧重事前预防的空管运行安全理论方法的研究在公开报导中还很少见到。本项目从分析空管运行过程入手,基于改进SHELL模型、数据挖掘和系统安全管理等进行亚健康理论在空管运行安全管理中的应用研究。本项目开展四个方面的研究:空管运行亚健康的概念及特性研究、空管运行的亚健康诊断理论方法研究、空管运行的亚健康调理理论方法研究、空管运行亚健康理论方法的仿真应用研究。本项目的研究,将初步揭示空管运行亚健康发生与发展的演化机理,将实现空管运行安全管理关口的前移,为提高空管运行安全管理水平、满足空中空中交通发展的需要提供有效支持工具,并将有助于实现在空管运行亚健康安全管理理论上的一个突破。
中文关键词: 空中交通管制;亚健康理论;安全管理;大数据;数据挖掘
英文摘要: Air traffic control system is an operation system that requires high safety level.At present, the study of safety management for air traffic control operation is mainly concentrated on ATM risk management. The research of taking precautions against the accident in the field of the air traffic control operation could be rarely seen in the published reports. From the view of the process of air traffic control operation, based on the revised SHELL model, data mining and system safety management, we'll stuty the application of the sub-health theory in the safety management for air traffic control operation. This project is carrying out on four aspects: the concepts and features of air traffic control operation in sub-health state, the diagnosis theory and method of air traffic control operation in sub-health state, the recuperation theory and method of air traffic control operation in sub-health state, the simulation and application of air traffic control operation in sub-health state. The research may expose the evolution mechanism of the occurrence and development of air traffic control operation in sub-health state. Besides, it may move forward the gate of safety management for air traffic control. It also provides an effective and supportive tool that improves the safety management level for air traffic, which meets the requirements of the air traffic development. Moreover, it may help to achieve the breakthrough in the theory of safety management for air traffic control operation in sub-health state.
英文关键词: air traffic control;sub-health theory;safety management;big data;data mining