基于BP神经网络的并联机构误差分析  

Error Analysis of Parallel Manipulator Based on BP Neural Network

作　　者：苗蓉[1] MIAO Rong(Shandong Weihai Career Technical College, Weihai Shandong 264210, China)

机构地区：[1]山东威海职业技术学院,山东威海264210

出　　处：《机床与液压》2017年第11期13-17,共5页Machine Tool & Hydraulics

基　　金：国家自然科学基金资助项目(51305333)

摘　　要：以3-UPS/S并联机器人机构为研究对象,构建一种基于虚拟实验与BP神经网络的并联机构输出误差预测模型,能够快速预测并联机器人机构的输出误差。充分考虑并联机构铰链安装误差与铰链轴线误差,建立包含上述输入误差的虚拟样机模型,通过虚拟实验仿真求解该机构输出误差;假定机构零部件在大批量生产情况下误差服从正态分布,构造多组服从正态分布的输入误差样本,进而建立该机构的BP神经网络预测模型。研究结果表明:该BP神经网络模型可以准确、快速地对机构位姿输出误差进行预测,为并联机器人机构的误差分析与精度综合提供了新的依据。Taking the 3-UPS/S parallel manipulator as the research object, a output error prediction model of parallel manipulator based on virtual experiment and BP neural network was constructed, which could predict the output error of parallel manipulator. A vir-tual prototype model with the input error was established by considering the hinge installation error with the hinge axis. It was assume that the error of the components in the mass production was in the normal distribution, and the input error samples of the multi group followed the normal distribution were constructed, and then the BP neural network prediction model of the parallel manipulator was es-tablished. The results show that the BP neural network model can predict accurately output pose error of the manipulator, which pro-vides a new basis for the error analysis and accuracy synthesis of parallel manipulator.

关 键 词：并联机构 精度分析 BP神经网络 误差 

分 类 号：TH112[机械工程—机械设计及理论]