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基于图像增强局部上采样SSD的直线电机动子非接触位置检测方法
引用本文:胡冬波,赵吉文,张晓虎.基于图像增强局部上采样SSD的直线电机动子非接触位置检测方法[J].控制与决策,2023,38(6):1629-1636.
作者姓名:胡冬波  赵吉文  张晓虎
作者单位:合肥工业大学 电气与自动化工程学院,合肥 230009
基金项目:国家自然科学基金重点项目(51837001).
摘    要:研究一种基于图像增强局部上采样平方差和(IE-LUSSD)的高精度亚像素检测算法,以提高直线电机动子位置检测对不同光照强度的抗干扰能力.首先,根据直线电机一维刚体平移的运动特点,设计一种基于线阵相机和非周期栅栏图像的动子位置检测系统,线阵相机固定在动子上并跟随动子移动采集信号序列;然后,通过灰度线性变换图像增强算法对采集到的信号序列进行预处理以增强图像信息;并通过SSD算法获取相邻信号序列间的整像素位移,为了进一步提高测量准确性,采用频率域矩阵乘法离散傅里叶变换对相邻信号间相关函数的峰值邻域进行上采样细化峰值曲线;最后通过搭建动子位置检测的实验平台验证所提出方法对不同光照条件的适应性.算法可以达到0.01 pixels的检测精度,动子的实际位置检测误差在0.025 mm以内.

关 键 词:直线电机  线阵相机  非接触位置检测  灰度线性变换  局部上采样平方差和  亚像素

Research on non-contact position detection method of linear motor mover based on image enhanced local upsampling SSD
HU Dong-bo,ZHAO Ji-wen,ZHANG Xiao-hu.Research on non-contact position detection method of linear motor mover based on image enhanced local upsampling SSD[J].Control and Decision,2023,38(6):1629-1636.
Authors:HU Dong-bo  ZHAO Ji-wen  ZHANG Xiao-hu
Affiliation:School of Electrical Engineering and Automation, Hefei University of Technology,Hefei 230009,China
Abstract:A high precision subpixel detection algorithm based on image enhanced local up-sampling sum-squared difference(IE-LUSSD) is studied to improve the anti-interference ability of linear motor position detection to different light intensity. Firstly, according to the motion characteristics of one-dimensional rigid body translation of linear motor, a motion position detection system based on line-scan camera and aperiodic fence image is designed. The line-scan camera is fixed on the mover and follows mover motion to collect signal sequences. Secondly, the gray-scale linear transform image enhancement algorithm is used to preprocess the collected signal sequences to enhance the image information. Then, SSD algorithm is adopted to obtain the integer-pixel displacement between adjacent signal sequences. In order to further improve the measurement accuracy, frequency domain matrix multiplication discrete Fourier transform is applied to up-sample the peak neighborhood of the correlation function of adjacent signals to refine the peak curve. Finally, the effectiveness of the method in different light conditions is verified by building an experimental platform for motion position detection. Detection accuracy of the proposed algorithm can reach 0.01 pixels and actual position detection error of the mover is within 0.025mm.
Keywords:
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