D
Dawei Zhao
Researcher at Huazhong University of Science and Technology
Publications - 20
Citations - 366
Dawei Zhao is an academic researcher from Huazhong University of Science and Technology. The author has contributed to research in topics: Spot welding & Welding. The author has an hindex of 11, co-authored 16 publications receiving 284 citations. Previous affiliations of Dawei Zhao include Linyi University.
Papers
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Journal ArticleDOI
Weld quality monitoring research in small scale resistance spot welding by dynamic resistance and neural network
TL;DR: In this paper, an efficient quality monitoring system in small scale resistance spot welding based on dynamic resistance was developed, where the dynamic resistance variation was related to weld nugget formation process.
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Multi-objective optimal design of small scale resistance spot welding process with principal component analysis and response surface methodology
TL;DR: The verification test results demonstrate that the method presented to optimize the welding parameters and enhance the welding performance is effective and feasible in the small scale resistance spot welding (SSRSW) process.
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Modeling and process analysis of resistance spot welded DP600 joints based on regression analysis
TL;DR: In this paper, the relationship between welding process parameters (welding time, welding current and electrode force) and the nugget diameter of resistance spot welded dual-phase steel DP600 with a thickness of 1.7mm was obtained by means of nonlinear stepwise regression analysis.
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A comparison of two types of neural network for weld quality prediction in small scale resistance spot welding
TL;DR: In this paper, an effective quality monitoring system in small scale resistance spot welding of titanium alloy was developed, where the measured electrical signals were interpreted in combination with the nugget development.
Journal ArticleDOI
Quality monitoring based on dynamic resistance and principal component analysis in small scale resistance spot welding process
TL;DR: In this article, a back propagation neural network model was proposed to simultaneously predict the nugget size and failure load in small-scale resistance spot welding of titanium alloy, which is used for real-time and online quality monitoring purpose.