Software Design For Defect Detection Of Spherical Optical Elements

Optical element is the most basic unit in optical system.Its quality directly affects the performance of optical system.As one of the important factors to measure its quality,the etiology of surface defects has attracted much attention.Surface defects on optical components are extremely damaging to optical systems,and can even cause system paralysis in high-energy laser systems.At present,the research on defect detection was mainly concentrated in the field of planar components,while spherical detection was relatively less because of its high technical difficulty.This thesis introduced several common defect detection principles,the software development environment and key technologies used in the development process.A surface defect detection system of spherical optical elements based on microscopic dark field scattering imaging was built on,and a supporting software was developed by using various development platforms.The detection process from image acquisition,image stitching to defect type identification and information extraction were realized.In this thesis,the upper computer software of the defect detection system was developed by using VC++ and MFC,and the communication between the computer and the hardware of the system was realized.The single-chip microcomputer was used as the lower computer,and the software of the lower computer was compiled with Keil C51 to control the rotary table and the swing table,and realized the sub-image acquisition by circular scanning.In view of the powerful image processing function of MATLAB,the program of image processing part of this software was compiled by MATLAB,and then converted into DLL dynamic link library file,which was called by C++ program,realized the image processing functions of sub-image classification,stitching and defect information extraction,and the commonly used edge detection algorithms and image filtering algorithms were compared by experiments to select the more suitable algorithm for defect image processing,which improved the image edge continuity and the effect of filtering and denoising.Finally,the defect pixel calibration was completed with electron microscope,and the relationship between the number of defect pixels and the actual size was obtained.Set up the experimental platform to complete the experiment,the experimental results showed that the detection system and its software can effectively identify surface defects and extract defect information,and the measurement accuracy was sufficient for practical application needs.