计算机与数字工程2019，Vol.47Issue(5)：1249-1253,5.DOI:10.3969/j.issn.1672-9722.2019.05.046
基于深度学习的无人机故障诊断方法研究
Research on Fault Diagnosis Method of UAV Based on Deep Learning
摘要
Abstract
Due to the high coupling of the quadrotor UAV system,it is difficult to establish the appropriate system model,the accuracy of fault diagnosis is low. At the same time,due to the complex working environment of UAV,it is easy to be affected by the external and internal noise,which makes most methods have the problem of insufficient robustness. Therefore,this paper proposes the Stacked Denoising Autoencoder(SDA)fault diagnosis method. It not only does not rely too much on the system model,but also enhances its robustness and improves the accuracy of fault diagnosis. The simulation results show that the UAV fault diagnosis meth?od based on SDA can correctly and reliably judge the fault type of the actuator,and effectively improve the safety and reliability of the four rotor UAV system.关键词
四旋翼无人机/栈式降噪自编码/鲁棒性Key words
quadrotor UAV/stacked denoising autoencoder/robustness分类
航空航天引用本文复制引用
李炜,崔佳佳..基于深度学习的无人机故障诊断方法研究[J].计算机与数字工程,2019,47(5):1249-1253,5.基金项目
国家自然科学基金项目(编号:61364011)资助. （编号:61364011）
