基于机器视觉的板材表面缺陷自动检测 方法研究.docx

基于机器视觉的板材表面缺陷自动检测 方法研究 Artificial Intelligence and Robotics Research 人工智能与机器人研究, 2022, 8(3), 109-117 Published Online August 2022 in Hans. /journal/airr https:// /10.12677/airr.2022.83014 Research on Automatic Detection Method of Plate Surface Defects Based on Machine Vision Yuanmin Huang, Ming Yi, Man Yang, Yuqing Luo College of Mechanical and Electrical Engineering, Foshan Vocational and Technical College, Foshan Guangdong Received: Jul. 27th, 2022; accepted: Aug. 13th, 2022; published: Aug. 20th, 2022 Abstract The surface defect of wood sheet not only directly affects the appearance and quality of the prod-uct, but also is one of the important factors affecting the classification of wood sheet. The surface quality of wood sheets is an important index for evaluating the quality of wood sheets, and it can also reflect the rationality of processing methods. Because there are many kinds of surface defects, the size and appearance of the same kind of defects are also different. On the one hand, this detec-tion method is easy to be affected by human factors, which cannot avoid the occurrence of false detection and missed detection, thus affecting the quality of sheet metal; on the other hand, it wastes a lot of manpower and financial resources and improves the quality of sheet metal. This reduces the competitive advantage and wastes valuable forest resources. In this paper, an auto-matic inspection method for surface defects of sheet metal using industrial machine vision lan-guage is proposed. This method uses a new improved algorithm to solve the registration problem of sheet metal image. A hybrid intelligent model is established by synthesizing artificial neural network, fuzzy technology and genetic algorithm, and the surface defect detection of sheet metal is realized by using artificial neural network technology. At the same time, an automatic detection device for surface defects of sheet metal is designed, which can also be sorted according to product grade. This will greatly reduce production costs, reduce the human interference factors in product testing process, achieve a high degree of automation in product production, improve product quality, and can produce good social and economic benefits. Keywords Machine Vision, Defect Detection, Algorithm 基于机器视觉的板材表面缺陷自动检测 方法研究 黄远民，易铭，杨曼，罗瑜清 本文来源：网络收集与整理，如有侵权，请联系作者删除，谢谢！第3页 共3页第 3 页 共 3 页第 3 页 共 3 页第 3 页 共 3 页第 3 页 共 3 页第 3 页 共 3 页第 3 页 共 3 页第 3 页 共 3 页第 3 页 共 3 页第 3 页 共 3 页第 3 页 共 3 页。