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IEEE access : practical research, open solutions, v.7, 2019년, pp.177284 - 177296
Liu, Zhifeng (Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing, China) , Chen, Wei (Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing, China) , Zhang, Caixia (Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing, China) , Yang, Congbin (Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing, China) , Chu, Hongyan (Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing, China China<)
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When mechanical products work in complex environments, it is imperative to build an optimal maintenance strategy, based on accurate positioning of fault locations and prediction of fault conditions. Based on digital twinning technology, this paper proposes a “super-network-warning features&#x...
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