Study On Automatic Detection Method Of Micro Defects On Ultra-Smooth Surface

With rapid development of precision manufacturing technology,the ultra-smooth surface characterized by nano level surface roughness has been widely applied in many fields such as military and scientific research.The quality of the ultra-smooth surface determines the performance of components while the surface defects can directly reduce components performance or even damage them.Therefore,it is urgent to propose an efficient detection method to meet the requirements of the ultra-smooth surface quality control.Aiming at the technical difficulties of ultra-smooth surface defects detecting such as small scale,random location and discreteness,the ultra-smooth surface micro-defect detecting system(USMDS)based on dark-field scattering imaging is proposed and improved.Meanwhile,the detecting methods of ultra-smooth surface defects are studied.The main research contents are as follows:The scattering characteristics of defects on the ultra-smooth surface are studied.Based on Mie scattering theory and BRDF,the scattering characteristics of micro defects on ultra-smooth surface are qualitatively studied.Based on the finite-difference time-domain(FDTD)algorithm,the electromagnetic field simulation of the far-field scattering characteristics of the defect area is carried out.According to the simulation results,several key factors affecting the scattering characteristics of the defect are analyzed and the theoretical basis of defect detection and measurement method of USMDS system is established.The automatic control method of USMDS system is studied.The spiral linear scanning detection model is constructed and based on the scanning detection algorithm,a reconstruction image mosaic calculation method is proposed to improve the description ability for defect shape and location information.This paper analyzes the influence of the main pose errors of the system on the scanning results and reconstructed images and puts forward the corresponding pose adjustment methods,so as to realize the correction of the main pose errors of the system and ensure the rationality and accuracy of the detection.The defect detection and processing algorithm of USMDS system is studied.In the aspect of image processing algorithm,a ghost image elimination method based on real image location is proposed to weaken the ghost image noise interference caused by transparent media samples and improve the stability of detection system.In the quantitative description of defects,a method of defect size measurement based on the characteristics of scattering light signal sequence is proposed.The edge feature point search algorithm based on wavelet threshold denoising and sliding window threshold is used to extract the scattering light signal sequence of defect area,and different types of defect size calculation and measurement are realized according to the geometric relationship.The content of this paper is verified by experiments.The experimental device of USMDS system is built to verify the proposed automatic control method.The results show that the proposed method can effectively control the main pose error range of the system.The experimental results of the defect detection and processing algorithm are verified.The ghost image elimination algorithm proposed in this paper is proved to have good noise reduction effect by virtue of the gray distribution characteristics of the image.The feasibility of the defect quantitative description method in this paper is verified.The results show that the measurement results of the method in this paper are basically consistent with the actual size of the defect and the measurement data of the optical microscope to verify the method The results show that the scanning control algorithm in this paper can effectively improve the detection efficiency,which is conducive to the realization of automatic and rapid scanning of small and medium-sized components surface.The detection system can realize the resolution and description of micron level defects and adapt to the detection requirements of ultra-smooth surface micro defects.The related work is summarized and the future research direction is prospected.