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Featured researches published by Yuanxun Wang.


Journal of Intelligent Manufacturing | 2014

Multi-objective optimal design of small scale resistance spot welding process with principal component analysis and response surface methodology

Dawei Zhao; Yuanxun Wang; Suning Sheng; Zongguo Lin

This paper investigates the effects of welding parameters on the welding quality and optimizes them in the small scale resistance spot welding (SSRSW) process. Experiments are carried out on the basis of response surface methodology technique with different levels of welding parameters of spot welded titanium alloy sheets. Multiple quality characteristics, namely signal-to-noise (S/N) ratios of weld nugget diameter, penetration rate, tensile shear load and the failure energy, are converted into an independent quality index using principal component analysis. The mathematical model correlating process parameters and their interactions with the welding quality is established and discussed. And then this model is used to select the optimum process parameters to obtain the desired welding quality. The verification test results demonstrate that the method presented in this paper to optimize the welding parameters and enhance the welding performance is effective and feasible in the SSRSW process.


Science and Technology of Welding and Joining | 2011

Effects of welding parameters on mechanical properties and microstructure of resistance spot welded DP600 joints

Peng Zhang; Jiang-Jiao Xie; Yuanxun Wang; Jianqiao Chen

Abstract This paper experimentally investigates the effects of welding parameters including electrode force, welding current and welding time on the mechanical properties and microstructure of resistance spot welded DP600 joints. The experimental results show that there exists an optimum value for each set of welding parameters that can maximise the mechanical properties and welding nugget size. The welding nugget size is a key factor controlling the mechanical properties of resistance spot welded DP600 joints; there is a relationship among welding nugget size, tensile shear load and failure energy. A larger welding nugget size leads to a greater probability of pullout failure. In addition, welding parameters also affect the microstructure, grain size, crack initiation and microhardness of resistance spot welded DP600 joints.


Science and Technology of Welding and Joining | 2016

Quality evaluation in small-scale resistance spot welding by electrode voltage recognition

Xiaodong Wan; Yuanxun Wang; Dawei Zhao

This study focuses on weld quality evaluation by electrode voltage in small-scale resistance spot welding of titanium alloy. Voltage curve could be divided into four stages based on the variation characteristic. The single voltage peak was detected as combined effects of increasing bulk material resistivity and nugget size. Variations of voltage curve shape, voltage peak and failure load were more sensitive to welding current than electrode force. A generalised regression neural network was proposed to evaluate weld quality using features extracted from voltage signal. A discrete Hopfield neural network was also applied for electrode voltage recognition. The recognised voltage patterns were found effective in identifying different quality levels. A real-time and on-line quality monitoring system could be developed.


Advanced Materials Research | 2011

Prediction Control Method of Spot Welded Nugget Size Based on Finite Element Analysis of Thermo-Electricity Transient

Hu Cai; Peng Zhang; Yuanxun Wang

Dual-phase steel is a type of sheet material newly developed to adapt to the lightweight and safety needs of vehicle. In this paper, 1.7 mm thick dual-phase steel DP600 was taken as the object of study, its resistance spot welding performance characteristics and welding mechanism was studied in detail. The thermoelectricity transient process of welding was simulated with the finite element software and the experiment under corresponding welding parameters. It’s found that, under proper current circumstances, the simulated nugget size and the experimental result is in good agreement except the large current, the simulated deformation morphology and experimental result can be consistent, which indicates the good accuracy of analysis on resistance spot welding mechanism of dual-phase steel DP600. According to the results, the specific method and theoretical basis about nugget size and welding deformation predictive control was discussed, created the mutual relations between the resistance spot welding performance characteristics and welding mechanism of dual-phase steel DP600. The study effort has practical significance in comprehensively understanding the resistances spot welding mechanism of dual-phase steel, as well as in application and quality control of duplex steel in automotive body welding.


Journal of Materials Processing Technology | 2007

Finite element analysis for the mechanical features of resistance spot welding process

Zhigang Hou; Ill-Soo Kim; Yuanxun Wang; Chunzhi Li; Chuanyao Chen


Journal of Materials Processing Technology | 2014

Modelling the effect of welding current on resistance spot welding of DP600 steel

Xiaodong Wan; Yuanxun Wang; Peng Zhang


Ndt & E International | 2013

An effective quality assessment method for small scale resistance spot welding based on process parameters

Dawei Zhao; Yuanxun Wang; Zongguo Lin; Suning Sheng


Materials & Design | 2013

Effects of electrode force on microstructure and mechanical behavior of the resistance spot welded DP600 joint

Dawei Zhao; Yuanxun Wang; Liuyi Zhang; Peng Zhang


The International Journal of Advanced Manufacturing Technology | 2016

Quality monitoring based on dynamic resistance and principal component analysis in small scale resistance spot welding process

Xiaodong Wan; Yuanxun Wang; Dawei Zhao


Measurement | 2013

Real time monitoring weld quality of small scale resistance spot welding for titanium alloy

Dawei Zhao; Yuanxun Wang; Suning Sheng; Zongguo Lin

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Dawei Zhao

Huazhong University of Science and Technology

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Xiaodong Wan

Huazhong University of Science and Technology

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Peng Zhang

Huazhong University of Science and Technology

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Chuanyao Chen

Huazhong University of Science and Technology

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Zhigang Hou

Huazhong University of Science and Technology

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YongAn Huang

Huazhong University of Science and Technology

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C. C. Yin

Huazhong University of Science and Technology

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Cuixia Fang

Huazhong University of Science and Technology

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Hong Ping Hu

Huazhong University of Science and Technology

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