Abstract:

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) is 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.