Research on Key Technology of Cold-Rolled Aluminum Plate Surface Defect Detection System

2013 ◽  
Vol 433-435 ◽  
pp. 915-918 ◽  
Author(s):  
Hai Lun Zhang ◽  
Xing Guang Qi ◽  
Xiao Ting Li
Keyword(s):  
Defect Detection ◽  
Surface Defect ◽  
Detection System ◽  
Aluminum Plate ◽  
Aluminum Surface ◽  
Image Processing Algorithm ◽  
Key Technologies ◽  
Rolled Aluminum ◽  
Surface Defect Detection ◽  
Cold Rolled

This paper presents the research of several key technologies during the implementation of cold-rolling aluminum surface defect detection system, including the difficulty of achieving these key technologies and the improvement of image processing algorithm. Through the installation and commissioning on actual production line, summarize and analyze the requirements of the hardware and software design for highly reflective aluminum plate, to achieve the control of product quality at present.

Design and Implementation of the Cold-Rolled Aluminum Plate Surface On-Line Defect Detection System

2013 ◽  
Vol 712-715 ◽  
pp. 2323-2326
Author(s):  
Xing Guang Qi ◽  
Hai Lun Zhang ◽  
Xiao Ting Li
Keyword(s):  
High Speed ◽  
Surface Defects ◽  
Detection System ◽  
Aluminum Plate ◽  
Gigabit Ethernet ◽  
Accurate Detection ◽  
High Processing Speed ◽  
Rolled Aluminum ◽  
On Line ◽  
Cold Rolled

This paper presents an on-line surface defects detection system based on machine vision, which has high speed architecture and can perform high accurate detection for cold-rolled aluminum plate. The system consists of high speed camera and industrial personal computer (IPC) array which connected through Gigabit Ethernet, achieved seamless detection by redundant control. In order to acquire high processing speed, single IPC as processor receives from and deals with only one or two cameras' image. Experimental results show that the system with high accurate detection capability can satisfy the requirement of real time detection and find out the defects on the production line effectively.

Aluminum Surface-Defect Detection Based on Multi-Task Deep Learning

2020 ◽  
Vol 57 (10) ◽  
pp. 101501
Author(s):  
沈晓海 Shen Xiaohai ◽  
栗泽昊 Li Zehao ◽  
李敏 Li Min ◽  
徐晓龙 Xu Xiaolong ◽  
张学武 Zhang Xuewu
Keyword(s):  
Deep Learning ◽  
Defect Detection ◽  
Surface Defect ◽  
Aluminum Surface ◽  
Surface Defect Detection

The PCB Surface Defect Detection System Based on GPU Acceleration

2015 ◽  
Vol 713-715 ◽  
pp. 347-352
Author(s):  
Yu Liu ◽  
Si Zhe Li
Keyword(s):  
Defect Detection ◽  
Rapid Detection ◽  
Surface Defect ◽  
Printed Circuit Board ◽  
Detection System ◽  
Processing System ◽  
Circuit Board ◽  
Computing Platform ◽  
Surface Defect Detection ◽  
Time Requirements

Defective products are unavoidable in printed circuit board production process, so rapid detection and identificationmethods are badly in need of. PCB surface defect detection including a series of processing such as surface imagecapture, mixed noise filtering,images registering and so on, so it takes a lot of CPU time. To improve detection speed, based on GPU parallel computing platform, we designed a reasonable parallel processing system for PCB defect detectionto meet the need of real-time requirements of a production line. Experimental results show that parallel image processing algorithms based on GPU can achieve good results compared to the CPU-based serial algorithm (with speed up ratio up to8.34 in this paper),providing a new approachfor rapid detection of PCB surface defect.

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