Research On Micro-vision For Displacement Measurement Of Micro-nano Motion Platforms

As mankind explores the microscopic field,the demand for precision measurement techniques at the micro and nano scale is increasing.Among these measurement methods,the combination of traditional measurement methods with high-performance algorithms for measurement has attracted the research of many scholars for its non-contact,high accuracy and wide range of applicable occasions.In order to be able to further improve the accuracy and efficiency of computer vision measurement methods,the aim of this thesis is to investigate high precision and high efficiency micro displacement measurement algorithms using micro-vision images,and to carry out research on micro displacement measurement methods for the micro-nano displacement output of piezoelectric ceramic displacement stages,using an electron microscope as the image sensing device to acquire micro-displacement images of micro-nano motion stages.The specific work carried out is as follows:First of all,the analysis of the composition of the microscopic vision measurement system is carried out according to the principle of computer vision measurement,and the selection of the experimental equipment of the system is carried out,and the principle of the measurement system is elaborated and the measurement accuracy of the measurement system is analysed.Then the acquisition method of image acquisition is described and the experimental system is built;the coordinate system conversion is carried out according to the optical principle and the mathematical matrix between the image space and the output of the micro-positioning platform is derived.Secondly,a new method of micro-nano motion measurement based on Hu moment matching combined with the center of gravity of the feature region is proposed for improving the accuracy of micro-vision measurement.In this paper,an image filtering algorithm is used for region feature enhancement,an improved segmentation algorithm is proposed for feature extraction,target region matching is performed in two images before and after the motion,the coordinates of the centre of gravity of the extracted feature region are calculated,and the pixel value of the coordinate shift is calculated by the unit pixel displacement coefficient to output the calculated displacement;the effectiveness of the method is verified by conducting displacement measurement experiments using the aforementioned method.Further,sub-pixel displacement measurements are performed on an integer pixel approach using digital image correlation principles.Several commonly used correlation coefficient functions are introduced for the images and the coefficient distributions are compared.The zero-mean normalised correlation function is selected by comparing the reliability and immunity to interference.A comparison of the computational accuracy,computational time and noise immunity of the surface fitting method,the grey-scale reconstruction method and the N-R method is carried out through theoretical analysis and simulation experiments,and the performance and characteristics of each algorithm are summarised.On this basis,the improvement of the sub-pixel displacement measurement method is carried out,and the improved algorithm of sub-pixel grey-scale surface based on Hermite interpolation is proposed.Simulation experiments on the measurement accuracy and noise immunity of the algorithm are also carried out for sub-pixel displacement measurement applications,verifying that its measurement accuracy can reach 0.01 pixel.Finally,experiments on the validity and feasibility of the above proposed method are carried out by collecting mechanical textures of the micro-displacement motion table,and the superiority of the method of this paper in terms of displacement accuracy and calculation efficiency is proved by comparison experiments with the laser interferometric displacement measurement system.