Laser Welding Weld Bead Uniformity Control Using Molten Pool Temperature by Closed Loop Adaptive PID
Article Sidebar
Main Article Content
Abstract
Laser welding offers significant benefits, including a high energy input rate that results in a fully penetrated weld seam. However, the quality of the weld may be compromised when joining workpieces with inconsistent thickness.This research proposes a control methodfor the laser welding process of low carbon steel (AISI 1018) with thicknesses ranging from 0.5 to 1.0 millimeters.This study utilizes infrared camera imaging to analyze the average temperature in the molten pool andthen sends this data to an Adaptive PID control system. This system regulates the average temperature, which serves as a primary input variable to control the welding power, by using gain kp = 0.003–0.0075, ki = 0.0002 – 0.0005 and kd = 0.003 – 0.021 thereby ensuring a correlation with the thickness of the workpieces. The study found that the Adaptive PID control system for laser welding effectively maintain the average temperature in the molten pool withan accuracy of ±3 °C from the setpoint. As a result, the weld seams demonstrate consistency and complete penetration.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The content and information in articles published in the Journal of Advanced Development in Engineering and Science are the opinions and responsibility of the article's author. The journal editors do not need to agree or share any responsibility.
Articles, information, content, etc. that are published in the Journal of Advanced Development in Engineering and Science are copyrighted by the Journal of Advanced Development in Engineering and Science. If any person or organization wishes to publish all or any part of it or to do anything. Only prior written permission from the Journal of Advanced Development in Engineering and Science is required.
References
Chen, G. et al. (2013). Research on Key Influence Factorsof Laser Overlap Welding of Automobile Body Galvanized Steel. Optics & Laser Technology, 45, 726-733.
Hong, K. & Shin, Y. (2017). Prospects of Laser Welding Technology in the Automotive Industry: A Review. Journal of Materials Processing Technology, 245, 46-69.
Pritschow, G. & Haug, K. (1998). Robust Laser-Stripe Sensor for Automated Weld-Seam Tracking in the Shipbuilding Industry. The 24th Annual Conference of the IEEE (p.1236-1241). 31 August – 4 September, 1998, Aachen, Germany.
Abderrazak, K., et al. (2009). Nd:YAG Laser Welding of AZ91 Magnesium Alloy for Aerospace Industries. Metallurgical and Material Transactions B, 40, 54-61.
Pariona, M., et al. (2012). Yb Fiber Laser Beam Effects on the Surface Modification of Al–Fe Aerospace Alloy Obtaining Weld Filet Structures, Low Fine Porosity and Corrosion Resistance. Surface and Coatings Technology, 206(8-9), 2293-2301.
Harman, G. & Albers, J. (1977). The Ultrasonic Welding Mechanism as Applied to Aluminum and Gold-Wire Bonding in Microelectronics. IEEE Transactions on Parts, Hybrids, and Packaging, 13(4), 406-412.
Arnold, G. (2009). Laser Micro Manufacturing: Fast and Reliable Solutions for Joining, Drilling and Structuring. Laser Technik Journal, 6(1), 16-29.
Tapia, G. & Elwany, A. (2014). A Review on Process Monitoring and Control in Metal-Basedadditive Manufacturing. Journal of Manufacturing Science and Engineering, 136(6), 060801.
Golubev, V., et al. (2010). Diagnostics of Laser Radiance Penetration into Material by Multi - Channel Pyrometer. In 2010 International Conference on Advanced Optoelectronic and Laser (p.182-194). 10 September – 14 September, 2010, Sevastopol, Ukraine.
Bertrand, P., et al. (2000). Application of Near Infrared Pyrometry for Continuous Nd:YAG Laser Welding of Stainless Steel. Applied Surface Science, 168(1-4), 182-185.
Wippo, V., et al. (2012). Evaluation of Apyrometric - based Temperature Measuring Process for the Laser Transmission Welding. Physics Procedia, 39, 128-136.
Kohler, H., et al. (2015). Contact-Less Temperature Measurement and Control with Applications to Laser Cladding. Welding in the World, 60, 1-9.
Wang, C., et al. (2020). Application of Sensing Techniques and Artificial Intelligence-based Methods to Laser Welding Real - time Monitoring: A Critical Review of Recent Literature. Journal of Manufacturing Systems, 57, 1-18.
Speka, M., et al. (2008). The Infrared Thermography Control of the Laser Welding of Amorphous Polymers. NDT & International, 41(3), 178-183.
Weberpals, J., et al. (2011). Utilisation of thermal radiation for process monitoring. Physics Procedia, 12, 704-711.
Qian, S., et al. (2018). Adaptive PID controller based on Q-learning algorithm. CAAI Transaction on Intelligence Technology, 3(4), 235-244.
Ziegler, J. G. & Nichols, N. B. (1942). Optimum Setting for Automatic Controllers. Transaction of the ASME, 64, 759-768.
