New Method of Spherical Surface Defect Detection Based on Machine Vision-Reference-Cited by-同舟云学术

New Method of Spherical Surface Defect Detection Based on Machine Vision

Published:2011-07 Issue: Volume:295-297 Page:1274-1278
ISSN:1662-8985
Container-title:Advanced Materials Research
language:
Short-container-title:AMR

Author:

Yang Jian Xi¹,Zhang Fa Yu¹,Song Xiao Xia¹,Xu Hong Zhe¹

Affiliation:

1. Henan University of Science and Technology

Abstract

According to requirements of online steel ball surface defect inspection, the automatic detection method of spherical surface defect on the track has been posed. To ensure photographing of the whole steel ball surface, the six CCD video cameras are used in this system. To overcome steel ball surface reflection, the red LED light source is used, and then the real and clear images are got. The steel ball surface defect is recognized accurately by means of image recognition technology and image reconstruction technology etc. This method provides theoretical basis and technical support for ball defection and quality classification.

Publisher

Trans Tech Publications, Ltd.

Subject

General Engineering

Link

https://www.scientific.net/AMR.295-297.1274.pdf

Reference10 articles.

1. PanHong-Ping, DongShen, automatic detection and recognition of the ball's surface, China Mechanical Engineering, Vol. 12, No. 4, April (2001).

2. LiChun-Ying, The appearance of ball detection system based on image processing, Bearing, September (2005).

3. JiangXin-Miao, LiuXian-Li, WangPeng, steel ball surface defect detection research based on Image technology, Harbin University of Technology, Vol 11, No. 2, April (2006).

4. ZhangYan-Ping, the detector analysis of Steel Ball's Surface flaws, Vol . 28, No. 2(Supplement), june(2006).

5. WangPeng, WuChun-Ya, LiuDe-Li, LabVIEW based the texture analysis and testing of steel ball's surface defect image, Gyroscopy and navigation, Vol. 28, No. 4, April (2007).

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