基于SVD的MEMS微结构位移测量新算法

 为实现MEMS微结构周期运动过程中平面运动位移测量及其动态特性参数的高分辨力测量,本文针对频闪成像技术获得的微结构运动图像序列,提出一种基于相位相关技术与奇异值分解技术相结合的亚像素测量方法。该方法通过相位相关技术将图像的空间坐标转换为频域坐标的参数空间,然后通过奇异值分解技术处理得到的相关矩阵,最后利用最小二乘法线性拟合,得到物体水平位移的亚像素测量结果。实验结果表明,用该方法测量MEMS微结构平面运动位移能达到亚像素精度,从而提高测量结果的稳定性和减少测量误差。

A New Algorithm for MEMS Microstructure Amplitude Measurements Based on Singular Value Decomposition

In order to obtain the high resolution measurement dynamic parameters for Micro Electro Mechanical System (MEMS) microstructure, the microstructure of moving image sequence is acquired by using stroboscopic imaging technology. One kind method based on the phase correlation technique and Singular Value Decomposition (SVD) technique combining with sub-pixel measurement is proposed. By means of phase correlation, the method is able to transform the spatial coordinate of the images into the parameter space in frequency domain coordinates. And then through the SVD technique, a correlation matrix is gained. Finally using the least-squares fitting, the results of sub-pixel level displacement measurement are got. The experimental results indicate that with the method, the amplitude measurement of MEMS microstructure plane motion is able to reach at the precision of sub-pixel, and could effectively reduce uneven illumination effect on the measuring result, thereby increasing the stability of measurement results and reducing the measuring error.