一种基于神经网络的机器人故障检测方法

A Neural Network Based Fault Detection Method for Robotic Manipulators

在对多种故障检测方法进行分析比较的基础上 ,提出一种基于神经网络的机器人故障检测系统结构 ,给出在线学习逼近机器人标称模型的故障检测方法。仿真结果表明 ,该方法能对机器人运行过程中出现的故障进行检测和定位。

This paper investigates main methods for fault detection and presents a system construction of neural network based fault detection in robotic manipulators. As well as we provide a learning architecture as on line approximation robotic nominal model with can be used in fault detection. Sumulation results show that the method deals with determining if fault has occurred and identifying a fault in the robot system.