Real-time top-face vision based control of weld pool size

被引:25
作者
Smith, JS [1 ]
Balfour, C [1 ]
机构
[1] Univ Liverpool, Dept Elect Engn & Elect, Liverpool, Merseyside, England
关键词
welding; inspection; automation; visual perception;
D O I
10.1108/01439910510600209
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Purpose - Top-face control of weld penetration in TIG welding is required for fully automated systems to overcome variations in the welding process and fixturing systems. Design/methodology/approach - This paper presents a system based upon based on the real-time vision measurement and control of the upper surface or "topface" weld pool size. The primary objective has been to demonstrate the feasibility of using vision-based image processing to provide measurements and the subsequent control of upper bead weld geometrical properties during the weld formation or molten phase and correlate this to the backface weld bead size. Findings - Vision based measurement of the upper surface of the weld pool can be used, in real-time, to control the weld pool size. This allows more uniform weld penetration to be achieved in the presence of disturbances. Research limitations/implications - The system requires that the pool edges can be accurately identified using a correlation method. This requires images with good contrast between the weld pool and the workpiece. Practical implications - The system is applicable to both continuous and pulsed TIG welding. Originality/value - A novel reference feature correlation-based image analysis algorithm has been developed that may be configured to operate with a number of different welding processes. The issues of system integration, i.e. interfacing the system with legacy welding equipment are also discussed.
引用
收藏
页码:334 / 340
页数:7
相关论文
共 12 条
[1]  
BALFOUR C, 2002, P 12 INT C COMP TECH
[2]  
BALFOUR C, 2000, P 10 INT C COMP TECH
[3]   Extracting weld penetration information in tungsten-inert gas welding [J].
Gao, J ;
Wu, C .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, 2002, 216 (02) :207-214
[4]   Prediction of welding parameters for pipeline welding using an intelligent system [J].
Kim, IS ;
Jeong, YJ ;
Lee, CW ;
Yarlagadda, PKDV .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2003, 22 (9-10) :713-719
[5]   Vision based neurofuzzy logic control of weld pool geometry [J].
Luo, H ;
Devanathan, R ;
Wang, J ;
Chen, X ;
Sun, Z .
SCIENCE AND TECHNOLOGY OF WELDING AND JOINING, 2002, 7 (05) :321-325
[6]  
Phillips C. L., 1995, DIGITAL CONTROL SYST
[7]  
*R BOSCH GMBH, 1991, CAN SPEC VERS 2 0
[8]  
SONKA M, 1999, IMAGE PROCESSING ANA, pCH5
[9]  
WEISKAMP J, 1994, DIGITIZE VIDEO, pCH2
[10]   Neurofuzzy model-based predictive control of weld fusion zone geometry [J].
Zhang, YM ;
Kovacevic, R .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 1998, 6 (03) :389-401