Research On The Quality Inspection System Of Small Mechanical Parts Based On Machine Vision

In recent years,with the rapid development of intelligent manufacturing technology,machine vision technology,as one of its core technologies,has become very popular.Machine vision is a technology that replaces or supplements manual detection and measurement with digital cameras and image processing.With the advantages of high flexibility,adaptability,precision and non-contact,the technology is applied to various industries,realizing production automatic and improving production speed,output and quality.This paper mainly studies surface defect detection and dimensional measurement in applications of machine vision technology.Based on machine vision technology,magnetic core and micro-reduction gearboxes are the research objects.In-depth study of core surface defect detection and micro-reduction box gear size measurement.A method for surface defect detection and dimension measurement of small mechanical parts based on machine vision is proposed.It builds a small machine component quality inspection system based on machine vision.And has researched on many aspects such as system hardware selection,software selection,camera calibration and image processing.The research of magnetic core surface defect detection is mainly on surface scratch defect detection,and it proposes a new threshold segmentation method for this defect feature.In the research of the micro-reduction gear box inner hole and the tip circle radius measurement,a new minimum enclosing circle detection method is proposed for the geometric characteristics of the inner and outer contours.This project has used QT Creator5.6 and OpenCV hybrid programming under Windows7 system to develop the functional software and human-computer interface of the quality inspection system and carry out related algorithm simulation and system operation experiments.The experimental results prove that the quality inspection method of small mechanical parts proposed in this paper can complete surface defect detection and dimensional measurement requirements.