Research On Fault Diagnose Method Based On Qualitative Simulation For Quad-rotor Aircraft

Because the quad-rotor aircraft has the characteristic of hovered, hovering, easy to land and take off, good flexibility and so on, it's more and more widely used. In most cases, quad-rotor aircraft is used for reconnaissance, rescue and other special occasions, the applications of occasions and environment are complex, and it also usually carry expensive device, so it wants high security, the fault diagnosis for the quad-rotor air craft is particularly important. But its mathematical model is complex, it has the characteristics of nonlinear, high coupling, sensitive to interference, under actuated and other characteristics, the traditional methods of fault diagnosis based on quantitative information are complex, there are many shortcomings when it apply for reality system. This paper use the qualitative simulation method for research of fault diagnosis, designing an intelligent, good real-time fault diagnosis system of four rotor aircraft, and then comparison with the simulation verifies feasibility.Firstly, quad-rotor aircraft is introduced in this paper about the main diagnostic methods and development present situation of fault diagnosis technology, and analyzing the advantages and disadvantages of each method, choosing the qualitative simulation method according to the characteristic of fault diagnosis.Secondly it introduces the basic principle of qualitative simulation method and QSIM algorithm, and the hardware composition of four rotor aircraft and possible failure are analyzed, and putting forward the control system of qualitative methods, setting up four rotor aircraft typical fault qualitative fault model, and being compared with data from four rotor aircraft simulation platform, verifying the correctness and feasibility of qualitative simulation method.For the lack of QSIM algorithm time sequence expression and reduce the virtual state with difficulty, we introduced the fuzzy quaternion array, blurring the qualitative variables and equations, and using the fuzzy qualitative simulation method for fault reasoning to solve the problem that QSIM algorithm time sequence cannot express, reducing the misdiagnosis rate of qualitative fault diagnosis method.