Surface Defect Detection Research And Development Of Industrial Products

With the development of machine vision, which is widely used in industrial production increasingly, especially in the detection of product defects. Automated detection of product defects will greatly improve the detection rate of the product, at the same time, due to the inherent drawbacks of manual inspection, the defect detection efficiency will be improved. The method of detect product’s inspection through machine vision reduces production costs while ensures product’s quality, ultimately, improves economic efficiency.Based on machine vision, this dissertation researches and develops one software, which is used to detect the product’s surface detects.Firstly, brief description and summary of the basic concepts and development status of the machine vision are shown. Secondly, the hardware system and software system of the detection system are designed and described in detail. The main equipments in the hardware system are introduced in detail, at the same time, functional analysis of the module in the software are shown. On this basis, combined with the principle of image location, real time image preprocessing and Blob analysis principles, the defect detection algorithm is designed and realized. Finally, the experiments demonstrate that the detection system can detect the surface defects of products timely and accurately.