直线电机动子位置的快速精密测量方法  

Fast-Precision Measurement Method of Linear Motor Mover Position

作　　者：方媛 周杨 赵静[1] 宫凯歌 Fang Yuan;Zhou Yang;Zhao Jing;Gong Kaige(School of Electrical Engineering and Automation,Aohui University,Hefei,Anhui 230601,China)

机构地区：[1]安徽大学电气工程与自动化学院,安徽合肥230601

出　　处：《激光与光电子学进展》2020年第18期79-87,共9页Laser & Optoelectronics Progress

基　　金：国家自然科学基金(51707002);安徽省自然科学基金(1808085QE123);安徽省教育厅项目(KJ2017A003)。

摘　　要：为了从目标图像上提高直线电机动子位置测量的精度、抗干扰性和实时性,引入了一种基于相关峰精确内插(FICP)的图像位移测量方法,并采用深度学习算法优选出具有强鲁棒性的栅栏图像。首先,控制栅栏条纹的宽度标准差和平均灰度梯度,生成一系列栅栏条纹图像。其次,结合线性调频Z变换和FICP算法计算相邻目标图像的位移值。然后,用位移估计值的均值误差作为评价指标,用深度神经网络建立栅栏图像质量优选模型,筛选出具有强鲁棒性的非周期栅栏图像。最后,利用线扫描相机获取运动过程中的一维栅栏图像信号,并根据棋盘标靶法确定系统的标定系数,得到实际位移值。仿真和实验结果表明,优选出的非周期栅栏图像能有效提高测量精度,证明了本方法的正确性。To improve the accuracy,anti-interference and real-time performance of linear motor mover position measurement from the shooting target image,an image displacement measurement algorithm based on fine interpolation of correlation peak(FICP)is introduced in this paper,and a deep learning algorithm is used to select the fence image with strong robustness.First,the width standard deviation and average gray gradient of the fence fringe are controlled to generate a series of fence fringe images.Second,the displacement of adjacent target images is calculated by combining chirp Z transform and FICP algorithm.Then,the mean error of displacement estimation is used as the evaluation index,and deep neural network is used to establish the quality optimization model of fence image,and the aperiodic fence image with strong robustness is screened out.Finally,the one-dimensional fence image signal in the motion process is obtained by line-scanning camera,the calibration coefficient of the system is determined according to the chessboard target method,and the actual displacement value is obtained.Simulation and experimental results show that the optimized aperiodic fence image selected in this paper can effectively improve the measurement accuracy and prove the correctness of this method.

关 键 词：位置检测 栅栏图像 图像处理 相关峰精确内插算法 深度神经网络 

分 类 号：TP361[自动化与计算机技术—计算机系统结构]