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作 者:赵静[1] 朱龙 吴震宇 董菲[1] Zhao Jing;Zhu Long;Wu Zhenyu;Dong Fei(School of Electrical Engineering and Automation,Anhui University,Hefei 230601,Anhui,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:《光学学报》2023年第11期84-95,共12页Acta Optica Sinica
基 金:国家自然科学基金(51907001);安徽省自然科学基金(2208085ME143);安徽省教育厅重点项目(KJ2021A0009)。
摘 要:为解决直线电机动子位置测量中多帧图像位移叠加而产生的误差累积问题,提出一种加阈值变换基准图(TTBM)的机器视觉累积误差消减算法。首先,根据直线电机动子的一维刚体平动特点,生成并优选灰度变化更加平滑的一维散斑图像作为目标拍摄图。其次,采用相位相关算法(PCA)改进灰度梯度方法,对配准图像进行整像素平移后再计算亚像素位移,以增大基准图像与配准图像之间的位移测量范围。最后,提出自调整基准图方法,根据图像位移的测量范围设定基准图像变换阈值,降低位移叠加次数,减小累积误差,实现直线电机长行程精密位移测量。同时,研究了基准图像变换阈值对测量精度的影响,给出了基准图变换的最佳阈值选取范围。仿真和实验表明,所提方法可以有效地减小直线电机动子测量中叠加而产生的累积误差。Objective In the highprecisionlongstroke manufacturing system,precise servo control of a motor determines the machining accuracy during manufacturing.Moreover,the value of the motor subposition is an important signal in the motor feedback control system,which determines the control precision of the linear motor servo system.Therefore,analyzing the position measurement algorithm for a highprecisionlongstroke linear electric motor is crucial.Currently,the linear electromotor measurement based on a digital image is mostly a shortstroke measurement and cannot achieve longstroke precision measurement.However,with the continuous improvement of precision manufacturing requirements,the need for the accurate measurement of the displacement of longstroke linear electric motor becomes extremely urgent.Moreover,unlike the twoframe image measurement system in shortstroke measurement,longstroke measurement comprises a multiframe image measurement system.The number of frames increases as the measurement distance increases,resulting in problems related to error accumulation.The cumulative measurement error is the most important factor that affects the measurement accuracy of rectilinear distance displacement.Hence,to address the issue of error accumulation owing to the displacement superposition of multiple frames during the measurement of the linear electromotor subposition,an error reduction algorithm based on machine vision with a threshold transform reference map was proposed herein.Methods In this study,the phase correlation algorithm is used to obtain the whole pixel offset between two frames rapidly,and the corresponding distance of the registration image is translated to decrease the displacement deviation between the registration image and reference frame to<1 pixel.The gray gradient algorithm is used to measure the subpixel displacement of the translated image in a small range.To improve the measurement accuracy and range of adjacent frames,then,the reference map is set,and the displacement images at different moments
分 类 号:TH82[机械工程—仪器科学与技术]
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