A review of heat source and resulting temperature distribution in arc welding

被引:9
作者
Das, Ankit [1 ]
Kumar, Arvind [2 ]
Shankhwar, Kalpana [3 ]
Gubeljak, Nenad [4 ]
机构
[1] Natl Taiwan Univ, Dept Biomechatron Engn, Taipei 10617, Taiwan
[2] Indian Inst Technol Kanpur, Dept Mech Engn, Kanpur 208016, Uttar Pradesh, India
[3] Natl Taiwan Univ, Dept Mech Engn, Taipei 10617, Taiwan
[4] Univ Maribor, Fac Mech Engn, Smetanova Ulica 17, Maribor 2000, Slovenia
关键词
Arc welding; Thermal behaviour; Heat source; Temperature distribution and measurement; Image processing; Machine learning; RESPONSE-SURFACE METHODOLOGY; MACHINE VISION MEASUREMENT; FINITE-ELEMENT-ANALYSIS; TRANSIENT TEMPERATURE; PLASMA-ARC; GAS TUNGSTEN; REGRESSION-ANALYSIS; NUMERICAL-ANALYSIS; PROCESS PARAMETERS; SOURCE MODEL;
D O I
10.1007/s10973-022-11589-w
中图分类号
O414.1 [热力学];
学科分类号
摘要
Thermal analysis is one of the cardinal studies essential for arc welding processes. Thermal field and temperature distribution in arc welds affect the quality of welds as they govern the microstructural and thermo-mechanical properties. Therefore, thorough understanding of the thermal behaviour in arc welds is an absolute necessity. Significant efforts have been made in the past to determine the temperature field associated with arc welding. However, for accurate determination of the temperature field/distribution, it is necessary to understand the heat source which influences the temperature distribution in welds. Rosenthal reported the first concept of modelling the heat source, which was then improvised and new models have been instituted through the years. This review article summarizes a collective study made on the heat source and the resulting temperature distribution in arc welds. Numerous methods have been developed to conduct transient temperature distribution studies on arc welds. Analytical approaches with constant material properties, numerical approaches with variable material properties, infrared imaging systems, machine vision systems with soft computing, etc. have been developed to facilitate understanding of transient temperature in arc welds. We first summarize heat source studies followed by literatures on various techniques and methods devoted to transient temperature investigations. Eventually, latest methods used for thermal studies, such as image processing, machine learning and intelligent systems are summarized and discussed.
引用
收藏
页码:12975 / 13010
页数:36
相关论文
共 150 条
[1]   THERMAL-STRESSES IN A SUBMERGED-ARC WELDED JOINT CONSIDERING PHASE-TRANSFORMATIONS [J].
ANDERSSON, BAB .
JOURNAL OF ENGINEERING MATERIALS AND TECHNOLOGY-TRANSACTIONS OF THE ASME, 1978, 100 (04) :356-362
[2]   Development of a three-dimensional heat-transfer model for the gas tungsten are welding process using the finite element method coupled with a genetic algorithm-based identification of uncertain input parameters [J].
Bag, S. ;
De, A. .
METALLURGICAL AND MATERIALS TRANSACTIONS A-PHYSICAL METALLURGY AND MATERIALS SCIENCE, 2008, 39A (11) :2698-2710
[3]   Sensing of the weld penetration at the beginning. of pulsed gas metal arc welding [J].
Bai, Pengfei ;
Wang, Zhijiang ;
Hu, Shengsun ;
Ma, Shangwen ;
Liang, Ying .
JOURNAL OF MANUFACTURING PROCESSES, 2017, 28 :343-350
[4]   Residual stress effects on fatigue life of welded structures using LEFM [J].
Barsoum, Z. ;
Barsoum, I. .
ENGINEERING FAILURE ANALYSIS, 2009, 16 (01) :449-467
[5]   Optimization of different welding processes using statistical and numerical approaches - A reference guide [J].
Benyounis, K. Y. ;
Olabi, A. G. .
ADVANCES IN ENGINEERING SOFTWARE, 2008, 39 (06) :483-496
[6]   Thermomechanical finite element analysis and experimental investigation of single-pass single-sided submerged arc welding of C-Mn steel plates [J].
Biswas, P. ;
Mandal, N. R. .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, 2010, 224 (B4) :627-639
[7]   TRANSIENT TEMPERATURE DISTRIBUTION IN ARC-WELDING OF FINITE THICKNESS PLATES [J].
BOO, KS ;
CHO, HS .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, 1990, 204 (03) :175-183
[8]   Welding penetration prediction with passive vision system [J].
Chen, Zongyao ;
Chen, Jian ;
Feng, Zhili .
JOURNAL OF MANUFACTURING PROCESSES, 2018, 36 :224-230
[9]   Detecting dynamic development of weld pool using machine learning from innovative composite images for adaptive welding [J].
Cheng, Yongchao ;
Wang, Qiyue ;
Jiao, Wenhua ;
Yu, Rui ;
Chen, Shujun ;
Zhang, YuMing ;
Xiao, Jun .
JOURNAL OF MANUFACTURING PROCESSES, 2020, 56 :908-915
[10]  
Christensen N., 1965, BRIT WELD J, V12, P5623