Modeling and Analysis of the Weld Bead Geometry in Submerged Arc Welding by Using Adaptive Neurofuzzy Inference System

Akkaş, Nuri; Karayel, Durmuş; Özkan, Sinan Serdar; Oğur, Ahmet; Topal, Bayram

doi:10.1155/2013/473495

Cited by 22 publications

(8 citation statements)

References 19 publications

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“…The analysed documents work mainly in horizontal or flat welding and obtain static models that use algorithms of artificial intelligence. The algorithms of artificial intelligence (represented by artificial neural networks [2,6,[42][43][44][45][46], fuzzy logic [47][48][49] and their combinations) are the most used to estimate the weld bead geometry and represent 28% of the works found in the literature. Image processing and statistical techniques such as multiple regression analysis, least squares [43,50,51] or factorial design [52] are also frequently used.…”

Section: Estimation Of the Weld Bead Depthmentioning

confidence: 99%

Measurement and estimation of the weld bead geometry in arc welding processes: the last 50 years of development

Bestard

Alfaro

2018

J Braz. Soc. Mech. Sci. Eng.

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The arc welding process is widely used in industry, but the automatic control is limited by the difficulty in the process for measuring the principal magnitudes and to close the control loop. Adverse environmental conditions make use of conventional measurement systems difficult for obtaining information of the weld bead geometry. Under these conditions, indirect sensing techniques are a good option. Different sensing and estimation techniques are used, but few researchers are focusing on the flat welding position. The theory and practice prove that the dynamic models are the best representation to control the welding process, but most studies are performed with static models. This work is a review of the algorithms and sensing techniques used for collecting values of the arc welding process that allow the measurement or estimation of the weld bead geometry. Special attention is given to sensor fusion techniques due to its promising future in the welding process. Discussed in this text are the papers, patents, thesis and other documents found on the theme. It shows a summary of their evolution over the last 50 years.

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Section: Estimation Of the Weld Bead Depthmentioning

confidence: 99%

Measurement and estimation of the weld bead geometry in arc welding processes: the last 50 years of development

Bestard

Alfaro

2018

J Braz. Soc. Mech. Sci. Eng.

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“…However, the welding joints are often the weakest links in assemblies [9]. The quality of the weld depends on the bead geometry [10], metallurgical and mechanical characteristics [11], chemical composition [12], and input parameters such as voltage, current, electrode type, flux and gas type, welding position, travel speed, and others [4] making the task of finding the best parameters quite challenging [13]. If the welding parameters are not correctly chosen, they can lead to welded joints with high levels of residual stresses [14,15], geometric distortions [16], and discontinuities [17,18].…”

Section: Introductionmentioning

confidence: 99%

Parametric Optimization of the GMAW Welding Process in Thin Thickness of Austenitic Stainless Steel by Taguchi Method

et al. 2021

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In the present work, an analysis of different welding parameters was carried out on the welding of stainless-steel thin thickness tubes by the Gas Metal Arc Welding (GMAW) process. The influence of three main parameters, welding voltage, movement angle, and welding current in the quality of the welds, was studied through a specifically designed experimental process based on the establishment of three different levels of values for each of these parameters. Weld quality is evaluated using destructive testing (macrographic analysis). Specifically, the width and root penetration of the weld bead were measured; however, some samples have been disregarded due to welding defects outside the permissible range or caused by excessive melting of the base metals. Data are interpreted, discussed, and analyzed using the Taguchi method and ANOVA analysis. From the analysis of variance, it was possible to identify the most influential parameter, the welding voltage, with a contribution of 43.55% for the welding penetration and 75.26% for the bead width, which should be considered in the designs of automatic welding processes to improve the quality of final welds.

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“…The research revealed that the optimisation of hard facing welding conditions can both result in improved properties and reduce the cost of manufacture. Akkas et al (2013) developed the models correlating the welding process parameters with the bead geometry of the welds. To correlate the above, ANN and neuro-fuzzy system approachs were used.…”

Section: Introductionmentioning

confidence: 99%

Optimal design of flux for submerged arc weld properties based on RSM coupled with GRA and PCA

Singh¹,

Khan²,

Siddiquee³

et al. 2020

IJMTM

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This paper presents an effective approach for the selection of flux for optimised mechanical properties of low carbon steel welds. The weld is mainly characterised by impact strength, ultimate tensile strength, percentage elongation and hardness. Since the mechanical performance is measured by multiple performance characteristics, the grey relational analysis is used to determine the optimal combination of flux for mechanical properties. Moreover, principal component analysis has been used to evaluate the weighting values for various performance characteristics so that their relative importance can be properly considered. Fluxes were designed using RSM and have been developed through agglomeration technique. By analysing the grey relational grade, it is found that both the impact strength and ultimate tensile strength have the same weightage. The results of confirmation test obtained using this approach show that the GRA coupled with PCA can be effectively used for optimisation of flux for mechanical performance characteristics.

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Modeling and Analysis of the Weld Bead Geometry in Submerged Arc Welding by Using Adaptive Neurofuzzy Inference System

Cited by 22 publications

References 19 publications

Measurement and estimation of the weld bead geometry in arc welding processes: the last 50 years of development

Measurement and estimation of the weld bead geometry in arc welding processes: the last 50 years of development

Parametric Optimization of the GMAW Welding Process in Thin Thickness of Austenitic Stainless Steel by Taguchi Method

Optimal design of flux for submerged arc weld properties based on RSM coupled with GRA and PCA

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