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Mover Position Detection for PMSLM Based on Line-Scanning Fence Pattern and Subpixel Polynomial Fitting Algorithm
IEEE/ASME Transactions on Mechatronics ( IF 6.1 ) Pub Date : 2019-11-11 , DOI: 10.1109/tmech.2019.2952667
Jing Zhao , Yang Zhou , Jiwen Zhao , Fei Dong , Xu Jiang , Kaige Gong

The article presents a rapid and precision position detection method for permanent magnet synchronous linear motors (PMSLM) based on digital image measurement and line-scanning photography. An exclusive fence pattern is designed as the target image for image measurement method, according to the motion feature of PMSLM. A line scan camera is installed on the mover to record image sequences instantaneously with the movement of linear motor, and from which the pixel displacement can be obtained using an image matching algorithm. To further improve the measurement accuracy, a subpixel polynomial fitting algorithm is proposed based on the line-scanning fence patterns. Finally, the displacement can be calculated according to system magnification parameters. Compared with the traditional image measurement method based on the area-array speckle pattern, both the cost and time delay of the proposed method are reduced greatly by employing line-scanning photography. The detection accuracy is also improved by four times. To improve the measurement robustness, an assessment index of fence pattern is proposed to optimize the fence image. The measurement error and robustness are analyzed in theory and simulation, and it demonstrates that the fence pattern shows stronger resistance to scanning deviation than speckle pattern. A mover position detection platform is established, and the experimental results show that the proposed method can achieve position estimation with average error of 0.005 mm under different working conditions.

中文翻译:

基于线扫描栅栏模式和亚像素多项式拟合算法的PMSLM移动器位置检测

本文提出了一种基于数字图像测量和线扫描摄影技术的快速,精确的永磁同步线性电动机位置检测方法。根据PMSLM的运动特征,将专用栅栏图案设计为图像测量方法的目标图像。在动子上安装了行扫描相机,以随线性电动机的运动即时记录图像序列,并可以使用图像匹配算法从中获得像素位移。为了进一步提高测量精度,提出了一种基于线扫描围栏图案的亚像素多项式拟合算法。最后,可以根据系统放大倍数计算位移。与基于区域阵列斑点图案的传统图像测量方法相比,通过使用线扫描摄影,所提出的方法的成本和时间延迟都大大降低了。检测精度也提高了四倍。为了提高测量的鲁棒性,提出了一种栅栏图案评估指标,以优化栅栏图像。对测量误差和鲁棒性进行了理论和仿真分析,结果表明栅栏图形比散斑图形对扫描偏差的抵抗力强。建立了动子位置检测平台,实验结果表明,该方法可以在不同的工作条件下实现位置估计,平均误差为0.005 mm。为了提高测量的鲁棒性,提出了一种栅栏图案的评估指标,以优化栅栏图像。对测量误差和鲁棒性进行了理论和仿真分析,结果表明栅栏图案比散斑图案具有更强的抗扫描偏差能力。建立了动子位置检测平台,实验结果表明,该方法可以在不同的工作条件下实现位置估计,平均误差为0.005 mm。为了提高测量的鲁棒性,提出了一种栅栏图案的评估指标,以优化栅栏图像。对测量误差和鲁棒性进行了理论和仿真分析,结果表明栅栏图案比散斑图案具有更强的抗扫描偏差能力。建立了动子位置检测平台,实验结果表明,该方法可以在不同的工作条件下实现位置估计,平均误差为0.005 mm。
更新日期:2020-04-22
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