scholarly journals Development of an Artificial Intelligence Powered TIG Welding Algorithm for the Prediction of Bead Geometry for TIG Welding Processes using Hybrid Deep Learning

Metals ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 451
Author(s):  
Martin A. Kesse ◽  
Eric Buah ◽  
Heikki Handroos ◽  
Godwin K. Ayetor
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Deep Neural Network ◽  
Predictive Accuracy ◽  
Welding Process ◽  
Tig Welding ◽  
Bead Geometry ◽  
Bead Width ◽  
Modeling Tools ◽  
Welding Processes

Recent developments in artificial intelligence (AI) modeling tools allows for envisaging that AI will remove elements of human mechanical effort from welding operations. This paper contributes to this development by proposing an AI tungsten inert gas (TIG) welding algorithm that can assist human welders to select desirable end factors to achieve good weld quality in the welding process. To demonstrate its feasibility, the proposed model has been tested with data from 27 experiments using current, arc length and welding speed as control parameters to predict weld bead width. A fuzzy deep neural network, which is a combination of fuzzy logic and deep neural network approaches, is applied in the algorithm. Simulations were carried out on an experimental test dataset with the AI TIG welding algorithm. The results showed 92.59% predictive accuracy (25 out of 27 correct answers) as compared to the results from the experiment. The performance of the algorithm at this nascent stage demonstrates the feasibility of the proposed method. This performance shows that in future work, if its predictive accuracy is improved with human input and more data, it could achieve the level of accuracy that could support the human welder in the field to enhance efficiency in the welding process. The findings are useful for industries that are in the welding trade and serve as an educational tool.

scholarly journals Prediction of Bead Geometry with Changing Welding Speed Using Artificial Neural Network

Materials ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1494
Author(s):  
Ran Li ◽  
Manshu Dong ◽  
Hongming Gao
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Welding Speed ◽  
Gas Metal Arc Welding ◽  
Welding Process ◽  
Training Dataset ◽  
Welding Parameters ◽  
Bead Geometry ◽  
Bead Width ◽  
Artificial Neural

Bead size and shape are important considerations for industry design and quality detection. It is hard to deduce an appropriate mathematical model for predicting the bead geometry in a continually changing welding process due to the complex interrelationship between different welding parameters and the actual bead. In this paper, an artificial neural network model for predicting the bead geometry with changing welding speed was developed. The experiment was performed by a welding robot in gas metal arc welding process. The welding speed was stochastically changed during the welding process. By transient response tests, it was indicated that the changing welding speed had a spatial influence on bead geometry, which ranged from 10 mm backward to 22 mm forward with certain welding parameters. For this study, the input parameters of model were the spatial welding speed sequence, and the output parameters were bead width and reinforcement. The bead geometry was recognized by polynomial fitting of the profile coordinates, as measured by a structured laser light sensor. The results showed that the model with the structure of 33-6-2 had achieved high accuracy in both the training dataset and test dataset, which were 99% and 96%, respectively.

Infrared Sensing for On-Line Weld Geometry Monitoring and Control

1995 ◽  
Vol 117 (3) ◽  
pp. 323-330 ◽  
Author(s):  
P. Banerjee ◽  
S. Govardhan ◽  
H. C. Wikle ◽  
J. Y. Liu ◽  
B. A. Chin
Keyword(s):  
Plate Thickness ◽  
Welding Process ◽  
Temperature Gradients ◽  
Monitoring And Control ◽  
Depth Of Penetration ◽  
Bead Width ◽  
Weld Geometry ◽  
On Line ◽  
And Control ◽  
Welding Processes

This paper describes a method for on-line weld geometry monitoring and control using a single front-side infrared sensor. Variations in plate thickness, shielding gas composition and minor element content are known to cause weld geometry changes. These changes in the weld geometry can be distinctly detected from an analysis of temperature gradients computed from infrared data. Deviations in temperature gradients were used to control the bead width and depth of penetration during the welding process. The analytical techniques described in this paper have been used to control gas tungsten arc and gas metal arc welding processes.

scholarly journals Experimental and Numerical Analysis on TIG Arc Welding of Stainless Steel Using RSM Approach

Metals ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1659
Author(s):  
Sasan Sattarpanah Karganroudi ◽  
Mahmoud Moradi ◽  
Milad Aghaee Attar ◽  
Seyed Alireza Rasouli ◽  
Majid Ghoreishi ◽  
...  
Keyword(s):  
Heat Flux ◽  
Stainless Steel ◽  
Welding Speed ◽  
Arc Welding ◽  
Welding Process ◽  
Weld Bead ◽  
Bead Geometry ◽  
Depth Of Penetration ◽  
Weld Bead Geometry ◽  
Bead Width

This study involves the validating of thermal analysis during TIG Arc welding of 1.4418 steel using finite element analyses (FEA) with experimental approaches. 3D heat transfer simulation of 1.4418 stainless steel TIG arc welding is implemented using ABAQUS software (6.14, ABAQUS Inc., Johnston, RI, USA), based on non-uniform Goldak’s Gaussian heat flux distribution, using additional DFLUX subroutine written in the FORTRAN (Formula Translation). The influences of the arc current and welding speed on the heat flux density, weld bead geometry, and temperature distribution at the transverse direction are analyzed by response surface methodology (RSM). Validating numerical simulation with experimental dimensions of weld bead geometry consists of width and depth of penetration with an average of 10% deviation has been performed. Results reveal that the suggested numerical model would be appropriate for the TIG arc welding process. According to the results, as the welding speed increases, the residence time of arc shortens correspondingly, bead width and depth of penetration decrease subsequently, whilst simultaneously, the current has the reverse effect. Finally, multi-objective optimization of the process is applied by Derringer’s desirability technique to achieve the proper weld. The optimum condition is obtained with 2.7 mm/s scanning speed and 120 A current to achieve full penetration weld with minimum fusion zone (FZ) and heat-affected zone (HAZ) width.

scholarly journals Weldability Investigation and Optimization of Process Variables for TIG-Welded Aluminium Alloy (AA 8006)

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
T. Sathish ◽  
S. Tharmalingam ◽  
V. Mohanavel ◽  
K. S. Ashraff Ali ◽  
Alagar Karthick ◽  
...  
Keyword(s):  
Experimental Design ◽  
Aluminium Alloy ◽  
Process Parameters ◽  
Surface Hardness ◽  
Weight Ratio ◽  
Welding Process ◽  
Tig Welding ◽  
Low Weight ◽  
Superior Corrosion Resistance ◽  
Welding Processes

Aluminium and its alloys play a significant role in engineering material applications due to its low weight ratio and superior corrosion resistance. The welding of aluminium alloy is challenging for the normal conventional arc welding processes. This research tries to resolve those issues by the Tungsten Inert Gas welding process. The TIG welding method is an easy, friendly process to perform welding. The widely applicable wrought aluminium AA8006 alloy, which was not considered for TIG welding in earlier studies, is considered in this investigation. For optimizing the number of experiments, the Taguchi experimental design of L9 orthogonal array type experimental design/plan was employed by considering major influencing process parameters like welding speed, base current, and peak current at three levels. The welded samples are included to investigate mechanical characterizations like surface hardness and strengths for standing tensile and impact loading. The results of the investigation on mechanical characterization of permanent joint of aluminium AA8006 alloy TIG welding were statistically analyzed and discussed. The 3D profilometric images of tensile-tested specimens were investigated, and they suggested optimized process parameters based on the result investigations.

Optimization of Flux Cored Arc Welding Process Parameter Using Genetic and Memetic Algorithms

2013 ◽  
Vol 13 (4) ◽  
pp. 239-250 ◽  
Author(s):  
T. Kannan ◽  
N. Murugan ◽  
B. N. Sreeharan
Keyword(s):  
Arc Welding ◽  
Welding Process ◽  
Memetic Algorithms ◽  
Optimization Techniques ◽  
Low Carbon ◽  
Robotic Welding ◽  
Bead Width ◽  
Flux Cored Arc Welding ◽  
Arc Welding Process ◽  
Welding Processes

AbstractMost of the manufacturing enterprises indulge in the bonding of metals during the production process. This makes welding one of the most important processes in industries. Subsequently, due to the high usage of welding process, industrial engineers desire to optimize the parameters concerned to achieve the desired weld bead characteristics. This paper focuses on optimization of flux cored arc welding process parameters, which are used for deposition of duplex stainless steel on low carbon structural steel plates. Experiments were conducted based on central composite rotatable design and mathematical models were developed using multiple regression method. Further, optimization with objectives as minimizing percentage dilution, maximizing height of reinforcement and bead width was carried out using genetic algorithm and memetic algorithm. This problem was formulated as a multi objective, multivariable and non-linear programming problem. The algorithms were implemented using basic functions of C language making it highly reliable, adoptable, very user friendly and extendable to other welding processes such as GMAW, GTAW, robotic welding, etc. The adopted optimization techniques were further compared based on various computational factors.

A Study of Software Approach for Predicting Weld Bead Geometry in Shielded Metal Arc Welding (SMAW) Process

2014 ◽  
Vol 554 ◽  
pp. 386-390
Author(s):  
C.W. Mohd Noor ◽  
Manuhutu Ferry ◽  
W.B. Wan Nik
Keyword(s):  
Arc Welding ◽  
Welding Process ◽  
Weld Bead ◽  
Bead Geometry ◽  
Shielded Metal Arc Welding ◽  
Depth Of Penetration ◽  
Weld Bead Geometry ◽  
Bead Width ◽  
Real Process ◽  
Metal Arc Welding

The prediction of the optimal weld bead width is an important aspect in shielded metal arc welding (SMAW) process as it is related to the strength of the weld. This paper focuses on investigation of the development of the simple and accurate model for prediction of weld bead geometry. The experiment used welding current, arc length, welding speed, welding gap and electrode diameter as input parameters. While output parameters are bead width, depth of penetration and weld reinforcement. A number of 33 mild steel plate specimens had undergone the SMAW welding process. The experimental data was used to develop mathematical models using SPSS software. The actual and predicted values of the weld bead geometry are compared. The proposed models shows positive correlation to the real process.

scholarly journals Mechanical and Fatigue Strength Assessment of Friction Stir Welded Plates of Magnesium Alloy AZ31B

2018 ◽  
Vol 23 (1) ◽  
pp. 52-59
Author(s):  
Carlos Fernando Luna ◽  
Fernando Franco Arenas ◽  
Victor Ferrinho Pereira ◽  
Julián Arnaldo Ávila
Keyword(s):  
Fatigue Strength ◽  
Magnesium Alloy ◽  
Welding Process ◽  
Welding Parameters ◽  
Speed Ratio ◽  
Bead Width ◽  
Strength Assessment ◽  
Friction Stir ◽  
Magnesium Alloy Az31b ◽  
Welding Processes

Abstract Light-alloys play a significant role in saving weight in automotive and aerospace industries; however, a few joining methods guarantee mechanical and fatigue strengths for high performance application. Even conventional arc welding processes do not offer constant quality joints. Therefore, this study uses an alternative solid-state welding process, friction stir welding (FSW), to analyze post processing microstructures and assess mechanical and fatigue strength. Magnesium alloy AZ31B plates were welded using different welding parameters in a dedicated FSW machine. The effect of the spindle speed (ω) and welding speed (ν) on the microstructure, the tensile strength and fatigue were studied. The stirred zone (SZ) at the FS-welded joints presented a microstructure composed by homogeneous equiaxial grains, refined by dynamic recrystallization. A rise in grain size, weld bead width, tensile and fatigue strengths with the increase of speed ratio (ω/ν) were observed. Results of the fatigue and mechanical strength here presented outperformed results from welds made with conventional milling machines.

scholarly journals Artificial Intelligence Segmented Dynamic Video Images for Continuity Analysis in the Detection of Severe Cardiovascular Disease

2021 ◽  
Vol 14 ◽  
Author(s):  
Xi Zhu ◽  
Wei Xia ◽  
Zhuqing Bao ◽  
Yaohui Zhong ◽  
Yu Fang ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Cardiovascular Diseases ◽  
High Risk ◽  
Sudden Cardiac Death ◽  
Sudden Death ◽  
Cardiac Death ◽  
Deep Neural Network ◽  
Video Image ◽  
Bundle Branch Block

In this paper, an artificial intelligence segmented dynamic video image based on the process of intensive cardiovascular and cerebrovascular disease monitoring is deeply investigated, and a sparse automatic coding deep neural network with a four layers stack structure is designed to automatically extract the deep features of the segmented dynamic video image shot, and six categories of normal, atrial premature, ventricular premature, right bundle branch block, left bundle branch block, and pacing are achieved through hierarchical training and optimization. Accurate recognition of heartbeats with an average accuracy of 99.5%. It provides technical assistance for the intelligent prediction of high-risk cardiovascular diseases like ventricular fibrillation. An intelligent prediction algorithm for sudden cardiac death based on the echolocation network was proposed. By designing an echolocation network with a multilayer serial structure, an intelligent distinction between sudden cardiac death signal and non-sudden death signal was realized, and the signal was predicted 5 min before sudden death occurred, with an average prediction accuracy of 94.32%. Using the self-learning capability of stack sparse auto-coding network, a large amount of label-free data is designed to train the stack sparse auto-coding deep neural network to automatically extract deep representations of plaque features. A small amount of labeled data then introduced to micro-train the entire network. Through the automatic analysis of the fiber cap thickness in the plaques, the automatic identification of thin fiber cap-like vulnerable plaques was achieved, and the average overlap of vulnerable regions reached 87%. The overall time for the automatic plaque and vulnerable plaque recognition algorithm was 0.54 s. It provides theoretical support for accurate diagnosis and endogenous analysis of high-risk cardiovascular diseases.

scholarly journals The Effect of Laser Beam Wobbling Mode on Weld Bead Geometry of Tailor Welded Blanks

2020 ◽  
Vol 3 (1) ◽  
pp. 282-290
Author(s):  
Celalettin Yuce
Keyword(s):  
Laser Beam ◽  
Production Efficiency ◽  
The Body ◽  
Weld Bead ◽  
Bead Geometry ◽  
Weld Bead Geometry ◽  
Bead Width ◽  
Body In White ◽  
Welding Processes ◽  
Beam Oscillation

As a higher weight leads to increased fuel consumption for the automobile industry, the body in white must be lighter to compensate for the weight of additional components. Therefore, tailored blanks are used, which reinforce the body in white only in areas where a higher strength or stiffness is necessary. The applicability of laser welding processes with its numerous advantages, such as low heat input and production efficiency, is often limited when joining imperfect edges steel sheets due to small gap bridging ability. To overcome this limit, recent developments in the laser industry have introduced a novel method to wider the applications of lasers through the utilization of fast beam oscillation techniques, also known as laser beam wobbling. In this study, the effects of the four different amplitudes (0.5 mm, 1 mm, 1.5 mm and 2 mm) of circular laser beam oscillation patterns on the weld bead geometry and microhardness distribution were investigated. The results revealed that the weld bead width increased with the increase of wobble amplitude. Moreover, the tensile strengths of the welded blanks were higher than the AHSS base metal for all amplitude levels.

Sign in / Sign up

Export Citation Format

Share Document