数据驱动的航空装备协同分析与智能保障决策方法

现代化战争模式对装备保障的响应性、精准性、可视性及自协同提出了更高的要求,而传统被动保障方式具有信息不精准、协同能力差、保障响应不及时等问题,迫切需要利用当前先进信息物理融合技术,实现“精准”、“敏捷”的主动式保障。针对主动式装备保障管理的需求,以及航空装备建立部件/系统数学模型困难等问题,提出一种状态协同分析与智能保障决策方法。该方法通过故障测试用例离线和在线的执行,产生测试数据;基于传感器的在线状态监测和历史数据,对装备状态进行估计和判断,从而提供智能保障决策服务。选取飞机燃油系统为对象,验证了提出方法的有效性,为主动式装备保障系统的研制奠定技术基础。

Data-driven collaborative analysis of aviation equipment and intelligent support decision-making method

The modern war mode puts forward higher requirements for the responsiveness, accuracy, visibility, and self-coordination of equipment support, while traditional passive support methods have problems such as inaccurate information, poor coordination capabilities, and untimely support response, which are in urgent need of use the current advanced cyber-physical fusion technology realizes the active guarantee of "precision" and "agile". Aiming at the needs of active equipment support management and the difficulty of establishing a component/system mathematical model for aviation equipment, a method of state collaborative analysis and intelligent support decision-making is proposed. This method generates test data through offline and online execution of fault test cases; based on online state monitoring and historical data of sensors, the equipment state is estimated and judged, thereby providing intelligent guarantee decision-making services. The aircraft fuel system is selected as the object to verify the effectiveness of the proposed method and lay a technical foundation for the development of active equipment support systems.