Control of weld penetration is currently one of the most important and crucial research issues in the area of welding. The weld pool can provide accurate and instantaneous information about the weld penetration, however, the establishment and confirmation of the correlation between weld pool and weld penetration require numerous accurate measurements and suitable geometrical modeling of weld pool. A normalized model is proposed to characterize the weld pool two-dimensionally. More than 6,000 weld pools are measured from experiments using a developed real-time weld pool sensing system. A data analysis shows that the weld penetration is correlated with the weld pool which is specified by the three characteristic parameters proposed in the study. However, the correlation is nonlinear. To approximate the complicated nonlinearity, neural networks are used. Comparative modeling trails show that the weld penetration can be more accurately calculated if the adjacent weld pools are also used. This implies that the correlation between the weld penetration and weld pool is dynamic. Hence, an on-line nonlinear dynamic estimation system is developed to estimate the weld penetration.
Skip Nav Destination
Article navigation
November 1997
Research Papers
Dynamic Estimation of Full Penetration Using Geometry of Adjacent Weld Pools
Y. M. Zhang,
Y. M. Zhang
Welding Research and Development Laboratory, Center for Robotics and Manufacturing Systems and Department of Mechanical Engineering, University of Kentucky, Lexington, Kentucky
Search for other works by this author on:
L. Li,
L. Li
Welding Research and Development Laboratory, Center for Robotics and Manufacturing Systems and Department of Mechanical Engineering, University of Kentucky, Lexington, Kentucky
Search for other works by this author on:
R. Kovacevic
R. Kovacevic
Southern Methodist University, Dallas, Texas
Search for other works by this author on:
Y. M. Zhang
Welding Research and Development Laboratory, Center for Robotics and Manufacturing Systems and Department of Mechanical Engineering, University of Kentucky, Lexington, Kentucky
L. Li
Welding Research and Development Laboratory, Center for Robotics and Manufacturing Systems and Department of Mechanical Engineering, University of Kentucky, Lexington, Kentucky
R. Kovacevic
Southern Methodist University, Dallas, Texas
J. Manuf. Sci. Eng. Nov 1997, 119(4A): 631-643 (13 pages)
Published Online: November 1, 1997
Article history
Received:
August 1, 1995
Revised:
July 1, 1996
Online:
January 17, 2008
Citation
Zhang, Y. M., Li, L., and Kovacevic, R. (November 1, 1997). "Dynamic Estimation of Full Penetration Using Geometry of Adjacent Weld Pools." ASME. J. Manuf. Sci. Eng. November 1997; 119(4A): 631–643. https://doi.org/10.1115/1.2831197
Download citation file:
Get Email Alerts
Multi-pass laser polishing of as-built DED surfaces
J. Manuf. Sci. Eng
Classification of Chip-Level Defect Types in Wafer Bin Maps Using Only Wafer-Level Labels
J. Manuf. Sci. Eng (July 2024)
Few-Shot Classification of Wafer Bin Maps Using Transfer Learning and Ensemble Learning
J. Manuf. Sci. Eng (July 2024)
Effects of Antifoaming Agents on Manufacturing Silver Dendrites Through Fluoride-Assisted Galvanic Replacement Reaction
J. Manuf. Sci. Eng (June 2024)
Related Articles
Ultrasonic Welding of Magnesium–Titanium Dissimilar Metals: A Study on Influences of Welding Parameters on Mechanical Property by Experimentation and Artificial Neural Network
J. Manuf. Sci. Eng (March,2017)
Distributed-Parameter Modeling for Geometry Control of Manufacturing Processes With Material Deposition
J. Dyn. Sys., Meas., Control (March,2000)
Rapid Estimate of Wind Turbine Energy Loss Due to Blade Leading Edge Delamination Using Artificial Neural Networks
J. Turbomach (July,2020)
Thermal Mechanical Modeling of the Plunge Stage During Friction-Stir Welding of Dissimilar Al 6061 to TRIP 780 Steel
J. Manuf. Sci. Eng (October,2015)
Related Proceedings Papers
Related Chapters
Motion Analysis for Multilayer Sheets
Ultrasonic Welding of Lithium-Ion Batteries
Modeling and Simulation of Coal Gas Concentration Prediction Based on the BP Neural Network
International Symposium on Information Engineering and Electronic Commerce, 3rd (IEEC 2011)
Modeling of Ion Exchange Process Using Time Delayed Neural Networks
International Conference on Mechanical and Electrical Technology, 3rd, (ICMET-China 2011), Volumes 1–3