基于节点重要度和AHP的无人机健康评估

Health Assessment of Unmanned Aerial Vehicle Based on Node Importance and AHP

针对无人机系统的维修成本高、维修决策滞后等问题,建立了一种基于节点重要度的无人机系统健康状况评估方法。所提方法在符号有向图的基础上建立虚引力模型,并引入介数的概念以优化节点的紧密性与影响力,优化了节点重要度计算,完善了层次分析法(analytic hierarchy process,AHP)的初始判断矩阵构造方法,最终结合改进岭型隶属度函数对无人机系统的健康状况进行模糊评价。实验结果表明,所提方法不仅能够实现无人机系统的健康状况等级划分,还能够为系统的故障预测与维修决策提供科学依据,具有重要的意义。

In order to solve the problems of high maintenance cost and lag in maintenance decision-making of unmanned aerial vehicle(UAV)systems,a method for evaluating the health status of UAV systems based on node importance is established.A virtual gravity model is set up based on the signed directed graphs,and the concept of betweenness is introduced to optimize the tightness and influence of nodes,which optimizes the calculation of node importance and improves the construction method of the initial judgment matrix of the analytic hierarchy process(AHP).Finally,combined with the improved ridge membership function,the health status of UAVS is fuzzy evaluated.The experimental results show that the proposed method can not only realize the classification of the health status of the UAV system,but also provide a scientific basis for the failure prediction and maintenance decision of the system,which has important significance.