Research on Fault Diagnosis of Fixed Wing Unmanned Aerial Vehicles Based on Convolutional Neural Networks
Due to the high temperature,high pressure,strong interference,strong impact and other complex environment of fixed-wing UAV system actuator for a long time,its fault characteristics are often complex,hierarchical,correlation and uncertain-ty.Therefore,a fault diagnosis method based on convolutional neural network is proposed in this paper for actuator faults of fixed-wing UAV.Compared with traditional fault diagnosis methods,it has stronger feature learning and feature expression capabili-ties.The experimental results show that the fault diagnosis method of fixed-wing UAV based on convolutional neural network can ac-curately and reliably judge the fault types of various actuators,and effectively improve the task security of fixed-wing UAV.
万方数据
维普
