Early fault intelligent diagnosis on aircraft and its application

We present an intelligent method for aircraft fault diagnosis and demonstrate that our method improves the effectiveness of the fault diagnosis. The method is based on the early fault analysis of aircraft and combines D-S Evidence Theory with Multi-agent. In this paper, we built a fault intelligent diagnosis model of aircraft and analyzed basic structure of Agent, structure and feature of mixed Agent, the realization strategy of intelligent diagnosis and D-S fusion reasoning algorithm. In the end, we applied the method on the thermal protection system of space-craft. The results have shown that our method, which combines D-S with Multi-agent, is a valid and effective way to identify aircraft early fault. We demonstrated the effectiveness of our method from four aspects: (1) it can not only identify the early fault quickly but also determine the location of faulty parts; (2) its structure is simple and configuration is flexible; (3) it can avoid complex count and reason fast; (4) it can effectively extract the early fault feature and speed up aircraft early fault diagnosis.