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JCR 2016
جستجوی مقالات
جمعه 1 اسفند 1404
Iranian Journal of Materials Forming
، جلد ۸، شماره ۴، صفحات ۳۳-۴۵
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کلیدواژههای فارسی مقاله
عنوان انگلیسی
Parameter Optimization in Resistance Spot Welding of AISI 1060 Steel Using Adaptive Neural Fuzzy Inference System and Sensitivity Analysis
چکیده انگلیسی مقاله
Resistance spot welding process of AISI 1060 steel has been experimentally investigated by studying the effects of welding current, electrode force, welding cycle and cooling cycle on tensile-shear strength. Using the response surface methodology, experimental tests are performed. An adaptive neural-fuzzy inference system is applied to model and predict the behavior of tensile-shear strength. Additionally, the optimal parameters of adaptive neural-fuzzy inference systems are obtained by the gray wolf optimization algorithm. For modeling the process behavior, the results of experiments have been employed for training (70% of data) and testing (30% of data) of the inference system. The results show that the applied network has been very successful in predicting the tensile-shear strength and the coefficient of determination and mean absolute percentage error for the test section data are 0.96 and 6.02%, respectively. This indicates the considerable accuracy of the employed model in the approximation of the desired outputs. After that, the effect of each input parameter on tensile-shear strength is quantitatively evaluated with the Sobol sensitivity analysis method. The results show that the tensile-shear strength of the joint rises by increasing the welding current and welding cycle and also decreasing the electrode force and cooling cycle.
کلیدواژههای انگلیسی مقاله
Resistance spot welding, AISI 1060 steel, Adaptive neural-fuzzy inference system, Gray wolf optimization algorithm, Sobol sensitivity analysis method
نویسندگان مقاله
Mehdi Safari |
Department of Mechanical Engineering, Arak University of Technology, Arak, 38181-8411, Iran
Amir Hossein Rabiee |
Department of Mechanical Engineering, Arak University of Technology, Arak, 38181-8411, Iran
Vahid Tahmasbi |
Department of Mechanical Engineering, Arak University of Technology, Arak, 38181-8411, Iran
نشانی اینترنتی
https://ijmf.shirazu.ac.ir/article_6381_78aa9ef550b8dbfb77c017fd5d46943f.pdf
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