基于概率神经网络的全向足球机器人运动系统的故障诊断  

Fault Diagnosis for Motion System of Omni-directional Soccer Robot Based on PNN

作　　者：赵爽[1] 李立[1] 

机构地区：[1]西南交通大学机械工程学院,四川成都610031

出　　处：《机床与液压》2014年第21期46-49,共4页Machine Tool & Hydraulics

基　　金：四川省应用基础研究项目(2008JY0063)

摘　　要：全向足球机器人运动系统故障诊断研究对于增强其鲁棒性具有重要意义。在分析全向足球机器人运动系统故障类型的基础上,提出了基于概率神经网络的全向足球机器人运动系统故障诊断方法。在该方法中,采用卡尔曼滤波器实时处理全向足球机器人运动速度的残差信号,并通过概率神经网络对其故障进行诊断。给出的仿真实例证明了该方法的有效性。It is of important significance to diagnose study the fault for motion system of the omni-directional soccer robot to en-hance its robustness. On basis of analyzing the fault types of motion system,the method based on probability neural network （PNN）for Omni-directional soccer robot was proposed. Among the method,the Kalman filtering method was used to process the residuals signal generated by the robot’s velocity in real time,and then the fault of the motion system was diagnosed accurately through the PNN. A simulation example is given to demonstrate the validity of the method.

关 键 词：全向足球机器人 故障诊断 概率神经网络 卡尔曼滤波 

分 类 号：TP24[自动化与计算机技术—检测技术与自动化装置]