无人机系统健康状态评估方法研究

摘要

提出了一种新的无人机系统健康状态评估方法,对某型无人机部分分系统发生故障及采取修复措施后的健康状态分别进行了评估.当关键分系统出现灾难性故障时,引入惩罚函数机制,对无人机的健康指数进行了修正;对传统以概率为主的故障模式、影响及危害分析进行了改进,提出了以故障发生后的严酷度级别进行危害分析的新方法,并应用于分系统健康状态的评估;考虑到专家判断的模糊性,把三角模糊数和层次分析法相结合,用于计算分系统的权值,并在计算过程中提出了首先把三角模糊正互反判断矩阵转换为三角模糊正互补判断矩阵的思路,便于理解与计算.仿真结果表明,本文提出的评价方法可操作性强,便于工程实现,能够直观地给出无人机的健康指数值.%A novel assessment method of health condition for a unmanned air vehicle (UAV) is proposed.The method is used to assess the health condition of an UAV in the conditions of the subsystem faults and repairs. The penalty function is introduced to correct the health index of the UAV when a disasture fault appears on the key subsystem. The traditional fault mode, effect and criticality analysis (FMECA) are improved,a new criticality analysis (CA) method based on the severity level is applied to the assessment of subsystem health conditions. Considering the fuzziness of expert judgment, the combination of triangular fuzzy number (TFN) and analysis hierarchy process (AHP) i.s used to calculate the weights of subsystem. In order to reduce computation. the calculation of weights transfers the triangular fuzzy positive reciprocal judgment matrix to triangular fuzzy positive complementary judgment matrix firstly. The simulation results show that the proposed assessment method can give the health index of UAV visually and is proved to be practical and easy to implement in engineering.