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Evaluation of power sources and the effect of varying current in SMAW process

  • Vikas KumarEmail author
  • Manoj Kumar Parida
  • O. P. Verma
Original Article
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Abstract

Shielded metal arc welding (SMAW) is one of the most important welding process used in the industry for joining ferrous and nonferrous metals. In SMAW process random fluctuations in current and voltage takes place. Reliable acquisition of these variations during actual welding process and its subsequent analysis can be very useful to study different arc welding parameters. Now a day, the welding power sources have a provision of advance arc control to suitably adjust the welding parameters with minimum time delay and to set the right welding parameters during actual process. Hence, to study the exact behaviour of these modern power sources used for welding it is essential to acquire all the possible minute variations taking place while welding is in progress. In the present study, performance evaluation of six different welding power sources has been performed using probability density distributions (PDD) and self organized maps (SOM). Further the quantification of their performance has also been attempted and the final results were compared with the results obtained using existing techniques. The effect of varying input current on SMAW process has also been studied by acquiring the data at different current values (from 70 A to 120 A). In both the cases data acquisition was carried out at the rate of 100,000 samples/s for 20 s duration using a general purpose digital storage oscilloscope while welding is in progress. These welds were prepared using same type of welding electrode by the same welder employing the identical parameters. From the PDDs and self organized maps (SOM) generated using the data acquired, it is possible to evaluate the performances of the different welding power sources. Grading of the power sources based on PDD and SOM technique matched well with the grading obtained using visual examination of weld beads. Further using these analyses, it is also possible to differentiate various weld geometry. Results clearly indicated that the procedure presented here can be effectively used to assess the various SMAW parameters.

Keywords

Statistical analysis Artificial neural network analysis Shielded metal arc welding Arc power sources Process 

Notes

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Copyright information

© The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2019

Authors and Affiliations

  1. 1.School of Electronics EngineeringKalinga Institute of Industrial Technology, Deemed to be UniversityBhubaneswarIndia
  2. 2.Department of Instrumentation and Control EngineeringDr. B R Ambedkar National Institute of TechnologyJalandharIndia

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