Research On The Displacement Measurement Method Of Screen Rotated Imaging With Improved Laser Triangulation

As a unique measurement method,laser triangulation can measure displacement,thickness,angular position and other information.Because of its non-contact,simple structure,anti-interference,and high measurement accuracy,it is widely used in modern industrial measurement.This article introduces the principle of laser triangulation to measure displacement,which is characterized by the intersection of the axis of the light source,the principal plane of the lens and the imaging screen at one point,which meets the Scheimpflug condition.The shortage of laser triangulation measurement of displacement is analyzed,and a displacement measurement method is proposed to improve the rotation imaging of the laser triangulation screen.This method requires that the measured surface,the principal plane of the lens and the imaging screen meet at a point,which is called the improved Scheimpflug condition;it proves that there is a clear imaging position through screen rotation;the expression for the rotation point of the screen rotation is derived,by The expression shows that when the displacement of the measured object changes,the position of the rotation point is fixed,which is called a fixed point;it is deduced that when the screen rotates through the fixed point to obtain a clear imaging position,it just satisfies the improved Scheimpflug condition.According to the selected parameters,a measuring device is designed,manufactured and installed.The measuring device includes a camera bias mechanism,a light source adjustment mechanism,a lens adjustment mechanism and an imaging surface adjustment mechanism.Based on VS2010 and OpenCV,an improved interactive interface for laser triangulation screen rotation imaging displacement measurement is designed to realize real-time image storage,image reading,image denoising processing,elliptical spot feature value and RGB pixel value acquisition,clear imaging position estimation algorithm,and System model calibration and verification functions.Through the analysis of the reason for the formation of the speckle image background and edge noise,a method based on the speckle image subtraction is adopted to achieve the denoising of the speckle image background.On this basis,an algorithm for removing edge noise based on the frequency of edge pixels is proposed.Experimental results show that the proposed algorithm is effective and feasible for edge denoising.For the background and edge denoised speckle images,a measurement model for estimating the clear imaging position based on the pixel values of the three RGB channels is fitted and compared.A method for estimating the clear imaging position based on the G channel pixel value of the sequence speckle image is proposed.Method,the experimental results show that the measurement model of the G channel pixel value to estimate the clear imaging position has good accuracy in calculating the object displacement change,which preliminarily verifies the correctness and feasibility of the proposed method.