An investigation into an intelligent system for predicting bead geometry in GMA welding process

Kim, I.S.; Son, Joon-Sik; Park, C.E.; Kim, I.J.; Kim, H.H.

doi:10.1016/j.jmatprotec.2004.04.415

Cited by 74 publications

(28 citation statements)

References 5 publications

(7 reference statements)

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“…Many efforts have been carried out development of various algorithms in the modelling of arc welding process [9,10]. McGlone and Chadwick [11] have reported a mathematical analysis correlating process variables and bead geometry for the submerged arc welding of square edge close butts.…”

Section: Introductionmentioning

confidence: 99%

The effect of process parameters on penetration in gas metal arc welding processes

2007

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Section: Introductionmentioning

confidence: 99%

The effect of process parameters on penetration in gas metal arc welding processes

2007

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“…Genetic Algorithms (GA) techniques, inspired in biological evolution, can be integrated with ANN (Sreedhar et al, 2012) in order to determine optimal input parameters to get high quality dilution of materials in GMAW process (Baskoro et al, 2009;Kim et al, 2005).…”

Section: Ann and Genetic Algorithmsmentioning

confidence: 99%

Revisión De Técnicas De Sistemas De Visión Artificial Para La Inspección De Procesos De Soldadura Tipo Gmaw

García

Plata

Quintero

2017

RCTA

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Resumen: El proceso de soldadura GMAW es ampliamente estudiado debido a su alta productividad y bajo costo. En este trabajo se han revisado las investigaciones orientadas a la inspección del proceso de GMAW a través de sistemas de visión artificial con el objetivo de establecer los principales elementos utilizados en estos sistemas destacando dos categorías: métodos computacionales (software y algoritmos generales), materiales y modelos matemáticos (métodos estadísticos y numéricos). Estas categorías se traslapan en el estudio y se han utilizado para evaluar el costo en términos de recursos humanos y recursos económicos. Las investigaciones revisadas se desarrollaron en la última década, con la excepción de algunas investigaciones que desempeñaron un papel principal en el desarrollo de los sistemas de inspección de los procesos GMAW. Finalmente, se han destacado los posibles campos de investigación para aquellos que intentan explorar sistemas de visión artificial para inspección de procesos GMAW.Palabras clave: GMAW, soldadura, visión artificial, inspección. Abstract:The GMAW welding process is widely studied due to its high productivity and low cost. In this paper we have reviewed the research oriented to the inspection of the GMAW process through artificial vision systems to classify them and establish the main elements used in these systems highlighting three categories: technology (hardware), computational methods (software and general algorithms) And mathematical models (statistical and numerical methods). These categories overlap in the document and have been used to assess the cost in terms of human resources and economic resources. The reviewed research was developed over the last decade, with the exception of some research that played a major role in the development of GMAW process inspection systems. Finally, potential research fields for those attempting to explore artificial visual systems for inspection of GMAW processes have been highlighted.

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“…In the GTAW process, as the input of heat and mass to the fusion zone are not coupled, the relationship between the welding Keywords: genetic algorithm; process parameters; gas tungsten arc welding; austenitic stainless steel; weld-bead geometry process parameters and the weld-bead geometry are complex. Many researchers successfully correlated large number of welding process variables with weld characteristics through statistical regression or neural network methods [2][3][4][5][6][7][8]. However, neural network models can only predict the weld bead geometry for a given set of input process variables, whereas the welding engineers need to find out the process variables that would produce the target weld bead geometry.…”

Section: Introductionmentioning

confidence: 99%

Optimising process parameters for gas tungsten arc welding of an austenitic stainless steel using genetic algorithm

Vasudevan

Kuppuswamy

Bhaduri

2010

Trans Indian Inst Met

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Automated Gas Tungsten Arc Welding (GTAW) with filler wire addition using a wire feeder is a candidate process for welding of 316LN austenitic stainless steel, which is the major structural material for the Indian 500 MWe Fast Breeder Reactors. In GTAW, the quality of the weld is characterized by the weld-bead geometry as it influences the mechanical properties and its performance during service. This paper discusses the development of computational model using genetic algorithm for determining the optimum/near-optimum GTAW process parameters for obtaining the target weld-bead profile during automatic welding of 316LN stainless steel. Using the experimental data generated on the influence of process variables on weld-bead geometry, regression models correlating the weld-bead shape parameters with the process parameters were developed for determining the objective function in genetic algorithm. Close agreement was achieved between the target weld-bead profile and the model-computed weld-bead profile. This study has shown that use of genetic algorithm is an appropriate methodology for optimising process parameters to obtain target weld-bead profile in GTAW with wire feeder of 316LN stainless steel.

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An investigation into an intelligent system for predicting bead geometry in GMA welding process

Cited by 74 publications

References 5 publications

The effect of process parameters on penetration in gas metal arc welding processes

The effect of process parameters on penetration in gas metal arc welding processes

Revisión De Técnicas De Sistemas De Visión Artificial Para La Inspección De Procesos De Soldadura Tipo Gmaw

Optimising process parameters for gas tungsten arc welding of an austenitic stainless steel using genetic algorithm

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