Research on fault diagnosis and comprehensive suppression function of airborne system

At present, the aircraft fault decision-making function only deals with a single fault, but the aircraft fault has concurrency. The existing aircraft fault decision-making function lacks the ability to deal with multiple fault concurrence situations. How to trace the source of multiple fault alarm information and excavate the original fault is of great significance for simplifying the alarm display and improving the pilot’s fault handling efficiency. In this paper, a fault diagnosis and comprehensive suppression function is designed, which consists of a fast fault location method based on prior knowledge and a comprehensive diagnosis and suppression method based on fault tree knowledge. The fast fault location method based on prior knowledge is based on case reasoning, which writes the past troubleshooting cases and many elements into the fault case base. When new faults occur, the matching degree of similar cases in the case base is obtained through retrieval model, so as to quickly obtain the current fault processing method. The comprehensive diagnosis method based on fault tree knowledge converts the fault tree into a binary decision diagram, and uses Huffman coding to realize computer programming. The probability of each cut set event in the binary decision graph is the probability product of its contained bottom event, so as to determine the risk degree of the failure to locate the cause of the failure. The fault sup-pression method classifies and processes the alarm information when multiple faults occur in a single system and multiple faults occur in multiple systems. The original fault and derivative fault are filtered by using the fault correlation value, the original fault is displayed, and the corresponding derivative fault is suppressed. The fault diagnosis and comprehensive suppression function of the aircraft airborne system designed in this paper provides sup-port for the development of the large aircraft alarm system.