Product Quality Inspection And Assembly Application Based On Machine Vision

At present,most of the product quality testing methods are manual quality testing.Due to the difficulty of manual quality inspection,it is easy to produce missed inspection or false inspection.With the maturity and development of machine vision technology,vision detection technology has the advantages of fast detection speed,high efficiency,good reliability,easy to achieve automatic detection and so on,and has a wide range of application prospects.In this paper,the quality inspection system of standard parts based on machine vision is studied.First of all,according to the requirements of standard parts product quality inspection,the overall design scheme and hardware selection of machine vision inspection system are completed,and the visual acquisition system is built;secondly,the Basler industrial camera calibration is completed in MATLAB software by using Zhang Zhengyou calibration method,and the camera internal parameters are obtained;then,the image is collected by taking the nut as the typical inspection object,and the image is corrected by using the camera internal parameters,The corrected image is transformed into gray-scale image,and then histogram equalization,filter denoising and threshold segmentation are carried out;thirdly,Sobel operator,Laplace operator and Canny operator are used to detect the edge of the image,which verifies that Canny operator is the optimal detection operator,and Canny operator is used to extract feature points for feature matching and detect nut quality.Finally,the feasibility and reliability of the detection system are verified by the product quality detection experiment on the production site,and the error of the workpiece quality detection parameters is controlled within a reasonable range,which lays a foundation for further product intelligent detection.