Effect of laser parameters on melting ratio and temperature distribution in dissimilar laser welding of brass and SS 308 using the artificial neural network model
Source abstract
Abstract
In this study, according to the experimental results related to the dissimilar laser welding of brass-stainless steel 308, a performance approximation method called artificial neural network (ANN) was used. Welding speed, focal length, peak power, pulse width, and frequency were taken as input parameters, and temperature and melting ratio were considered as target characteristics. The ANN results were compared with the experimental results and the error percentage between them was obtained. Maximum relative errors were 9.63%, 10.55%, and 6.13% for brass alloy temperature, stainless steel, and melt ratio, respectively. Based on this comparison, the percentage of error between the experimental data and the ANN was at a reasonable level; so, this numerical method could be used with low time and cost. Also, by considering seven and five neurons in the hidden layer, the lowest mean squared error was obtained for temperature and melting ratio, respectively.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Welding Techniques and Residual Stresses · Additive Manufacturing Materials and Processes · Laser and Thermal Forming Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical and Power Engineering, Zhengzhou University 1 , Zhengzhou City, Henan 450001, China
North China University of Water Resources and Electric Power 2 , Zhengzhou, Henan 450008, China
Special Equipment Safety Inspection and Research Institute of Henan Province 3 , Zhengzhou, Henan 450008, China
Henan mining Crane Co., Ltd 4 , Xixiang, Henan 453400, China
Funding
key research and development and promotion special project of henan province
References (28)
Show source-provided references
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