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Dive into the research topics where Dawei Zhao is active.

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Featured researches published by Dawei Zhao.


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 | 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.


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


Materials & Design | 2014

Process analysis and optimization for failure energy of spot welded titanium alloy

Dawei Zhao; Yuanxun Wang; Xiaodong Wang; Xuenong Wang; Fa Chen; Dongjie Liang


The International Journal of Advanced Manufacturing Technology | 2016

Multi-response optimization in small scale resistance spot welding of titanium alloy by principal component analysis and genetic algorithm

Xiaodong Wan; Yuanxun Wang; Dawei Zhao


Measurement | 2017

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

Xiaodong Wan; Yuanxun Wang; Dawei Zhao; YongAn Huang; Zhouping Yin


Isij International | 2013

Quality Monitoring Research of Small Scale Resistance Spot Welding Based on Voltage Signal

Dawei Zhao; Yuanxun Wang; Zongguo Lin; Suning Sheng

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Yuanxun Wang

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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Liuyi Zhang

Huazhong University of Science and Technology

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YongAn Huang

Huazhong University of Science and Technology

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Zhouping Yin

Huazhong University of Science and Technology

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