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首页> 外文期刊>Mechanical systems and signal processing >Robust high precision multi-frame motion detection for PMLSMs' mover based on local upsampling moving least square method
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Robust high precision multi-frame motion detection for PMLSMs' mover based on local upsampling moving least square method

机译:基于本地上采样的PMLSMS的MMLSMS的高精度多帧运动检测是基于本地上采样的最小二乘法

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摘要

This paper studies a multi-frame visual sub-pixel measurement technique to achieve the precise positioning of the permanent magnet linear synchronous motor (PMLSM) rapidly. A new matrix multiplication discrete Fourier transform (DFT) upsampling moving least square (MLS) algorithm is proposed to improve the accuracy and robustness of PMLSM positioning. Firstly, a line-scan vision-based measurement system is designed, and an aperiodic sinusoidal fringe image is placed on the pedestal as target image. Secondly, the local upsampling cross-correlation curve of adjacent one-dimensional signals is calculated to obtain sub-pixel displacement using the matrix-multiplied DFT method. Finally, to further improve the displacement accuracy, the MLS method is applied. Simulation tests verify that the proposed method is superior to other algorithms in measurement accuracy, calculation efficiency and measurement range. The experiment results confirm the feasibility and validity of the proposed method for detecting the mover motion under different working environments.
机译:本文研究了多帧的视觉子像素测量技术,实现了永磁线性同步电动机(PMLSM)的精确定位。提出了一种新的矩阵乘法离散傅里叶变换(DFT)上采样移动最小二乘法(MLS)算法,以提高PMLSM定位的准确性和鲁棒性。首先,线扫描基于视觉的测量系统的设计,并且非周期性正弦条纹图像被放置在台座作为目标图像。其次,计算相邻一维信号的局部上采样互相关曲线,以使用矩阵乘以DFT方法获得子像素位移。最后,为了进一步提高位移精度,施加MLS方法。仿真试验验证所提出的方法优于其他测量精度,计算效率和测量范围的其他算法。实验结果证实了在不同工作环境下检测动力运动的所提出方法的可行性和有效性。

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