A study on using scanning acoustic microscopy and neural network techniques to evaluate the quality of resistance spot welding

2003 ◽  
Vol 22 (9-10) ◽  
pp. 727-732 ◽  
Author(s):  
Hsu-Tung Lee ◽  
Michael Wang ◽  
Roman Maev ◽  
Elena Maeva
Keyword(s):  
Neural Network ◽  
Resistance Spot Welding ◽  
Spot Welding ◽  
Acoustic Microscopy ◽  
Scanning Acoustic Microscopy ◽  
Resistance Spot

Analysis of Electromagnetic Inverse Model of Resistance Spot Welding

2010 ◽  
Vol 160-162 ◽  
pp. 974-979
Author(s):  
Nai Feng Fan ◽  
Zhen Luo ◽  
Yang Li ◽  
Wen Bo Xuan
Keyword(s):  
Resistance Spot Welding ◽  
Regularization Method ◽  
Spot Welding ◽  
Influence Factors ◽  
Great Influence ◽  
Welding Process ◽  
Inverse Model ◽  
Resistance Spot ◽  
Inversion Theory

Resistance spot welding (RSW) is an important welding process in modern industrial production, and the quality of welding nugget determines the strength of products to a large extent. Limited by the level of RSW quality monitor, however, RSW has rarely been applied to the fields with high welding quality requirements. Associated with the inversion theory, in this paper, an electromagnetic inverse model of RSW was established, and the analysis of influence factors, such as the layout of the probes, the discrete program and the regularization method, was implemented as well. The result shows that the layout of the probe and the regularization method has great influence on the model. When the probe is located at the y direction of x-axis or the x direction of y-axis and Conjugate Gradient method is selected, a much better outcome can be achieved.

Weld quality monitoring research in small scale resistance spot welding by dynamic resistance and neural network

Measurement ◽  
2017 ◽  
Vol 99 ◽  
pp. 120-127 ◽  
Author(s):  
Xiaodong Wan ◽  
Yuanxun Wang ◽  
Dawei Zhao ◽  
YongAn Huang ◽  
Zhouping Yin
Keyword(s):  
Neural Network ◽  
Resistance Spot Welding ◽  
Spot Welding ◽  
Quality Monitoring ◽  
Small Scale ◽  
Dynamic Resistance ◽  
Weld Quality ◽  
Resistance Spot ◽  
Scale Resistance

scholarly journals Resistance Spot Welding Optimization Based on Artificial Neural Network

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Thongchai Arunchai ◽  
Kawin Sonthipermpoon ◽  
Phisut Apichayakul ◽  
Kreangsak Tamee
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Shear Strength ◽  
Aluminum Alloy ◽  
Parameter Optimization ◽  
Resistance Spot Welding ◽  
Spot Welding ◽  
Tensile Shear Strength ◽  
Tensile Shear ◽  
Resistance Spot

Resistance Spot Welding (RSW) is processed by using aluminum alloy used in the automotive industry. The difficulty of RSW parameter setting leads to inconsistent quality between welds. The important RSW parameters are the welding current, electrode force, and welding time. An additional RSW parameter, that is, the electrical resistance of the aluminum alloy, which varies depending on the thickness of the material, is considered to be a necessary parameter. The parameters applied to the RSW process, with aluminum alloy, are sensitive to exact measurement. Parameter prediction by the use of an artificial neural network (ANN) as a tool in finding the parameter optimization was investigated. The ANN was designed and tested for predictive weld quality by using the input and output data in parameters and tensile shear strength of the aluminum alloy, respectively. The results of the tensile shear strength testing and the estimated parameter optimization are applied to the RSW process. The achieved results of the tensile shear strength output were mean squared error (MSE) and accuracy equal to 0.054 and 95%, respectively. This indicates that that the application of the ANN in welding machine control is highly successful in setting the welding parameters.

Research on Resistance Spot Welding of DP980 Dual Phase Steel

2013 ◽  
Vol 860-863 ◽  
pp. 780-783
Author(s):  
Qiao Bo Feng ◽  
Yun Feng Zhu ◽  
He Xin Zhao
Keyword(s):  
Resistance Spot Welding ◽  
Spot Welding ◽  
Dual Phase Steel ◽  
Welding Current ◽  
High Resistivity ◽  
Dual Phase ◽  
Welding Joint ◽  
Resistance Spot ◽  
Electrode Force

The process parameters and quality of resistance spot welding for DP980 dual phase steel were studied through the orthogonal experiment method, and the influence of welding current, welding time and electrode force on the strength of welding joint has been discussed. The results show that the welding current has the greatest influence on the quality of welding joint for DP980 dual phase steel, and it needs relatively lower welding current for the DP980 dual phase steel as it has high resistivity, and appropriate increasing of electrode force is a feasible way to avoid the defect of shrinkage and it improves the joint strength.

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