摘要
位置敏感器件(PSD)具有性价比高、外围电路简单等优点,在角度等高精度测量领域具有广泛应用.但PSD的非线性限制了其精度,针对PSD(位置敏感器)固有的非线性,分析了二维PSD非线性特征及对测量结果的影响,提出了一种基于神经网络的二维PSD线性优化的算法,使用两个稳含层对神经网络进行训练,建立非线性映射关系,对二维PSD实现非线性补偿,通过MATLAB仿真实验对比,结果显示该算法能有效地减少二维PSD非线性的影响,且精度较高,收敛速度快,提高了测量数据的准确性.
Position-sensing devices( PSD) have the advantages of cost-effectiveness,simple peripheral circuits,and are widely used in high-precision measurement fields such as angles. However,the nonlinearity of the PSD limits its accuracy. Based on the inherent nonlinearity of the PSD( Position Sensor),the nonlinear characteristics of the two-dimensional PSD and the influence on the measurement result are analyzed. A two-dimensional PSD linear optimization based on a neural network is proposed. The algorithm uses two stable layers to train the neural network,establishes a nonlinear mapping relationship, and achieves nonlinear compensation for the two-dimensional PSD. The results of the MATLAB simulation show that the algorithm can effectively reduce the nonlinearity of the two-dimensional PSD. Impact,high accuracy,fast convergence,improve the accuracy of measurement data.
作者
韩小雨
李田泽
陈洪涛
HAN Xiaoyu;LI Tianze;CHEN Hongtao(School of Electrical Engineering,Shandong University of Technology,Zibo 255000,China)
出处
《商丘师范学院学报》
CAS
2019年第3期25-28,共4页
Journal of Shangqiu Normal University
基金
山东省自然科学基金资助项目(ZR2012FL19)
山东省高等学校科技计划项目(J14LN31)
作者简介
韩小雨(1992—),女,山东淄博人,山东理工大学硕士研究生,主要从事光电检测的研究;通讯作者:李田泽(1963—),男,山东淄博人,山东理工大学教授,硕士生导师,主要从事光电技术的研究.
