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双通道多级旋转变压器的标定和基于BP神经网络的误差补偿方法
引用本文:张飞,史士财,孙敬颋,郭闯强,陈泓,刘宏.双通道多级旋转变压器的标定和基于BP神经网络的误差补偿方法[J].机械与电子,2011(9):13-15.
作者姓名:张飞  史士财  孙敬颋  郭闯强  陈泓  刘宏
作者单位:哈尔滨工业大学机器人技术与系统国家重点实验室;
摘    要:通过高精度的编码器实现对旋转变压器的标定,为了提高旋转变压器的精度,提出了一种基于BP神经网络的误差补偿方法,用该网络对误差曲线进行训练,再将训练结果写入DSP程序中进行实时补偿。实验结果表明,通过该方法对误差进行补偿,可以将误差从±9′补偿到±0.3′,重复性好。

关 键 词:旋转变压器  零位误差  幅值误差  BP神经网络

Calibration for Twin-channel Multipole Resolvers and the Method of Error Compensation on BP Neural Network
ZHANG Fei,SHI Shi-cai,SUN Jing-ting,GUO Chuang-qiang,CHEN Hong,LIU Hong.Calibration for Twin-channel Multipole Resolvers and the Method of Error Compensation on BP Neural Network[J].Machinery & Electronics,2011(9):13-15.
Authors:ZHANG Fei  SHI Shi-cai  SUN Jing-ting  GUO Chuang-qiang  CHEN Hong  LIU Hong
Affiliation:ZHANG Fei,SHI Shi-cai,SUN Jing-ting,GUO Chuang-qiang,CHEN Hong,LIU Hong(State Key Laboratory of Robotics and System,Harbin Institute of Technology,Harbin 150001,China)
Abstract:The paper realizes calibration for resolvers by high - accuracy encoder. To enhance measure precision,a method of error compensation on BP neural network is presented and trains the error curve by this network, then writes the training result into DSP to realize the real - time compensation. The experiment shows that the resolver's error can be reduced from 9′ to 0. 3′ by the compensation and the repeatability is high.
Keywords:resolver  zero-position error  magnitude error  BP neural network  
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