Cloud-fog-edge collaborative digital twin manufacturing system simulation process and dynamic disturbance response method

被引：0
|
作者：
Meng Q. [1 ,2 ,3 ]
Hu T. [1 ,2 ,3 ]
Ma S. [1 ,2 ,3 ]
机构：
[1] School of Mechanical Engineering, Shandong University, Jinan
[2] Key Laboratory of High-Efficiency and Clean Mechanical Manufacture, Shangdong University, Ministry of Education, Jinan
[3] National Demonstration Center for Experimental Mechanical Engineering Education, Jinan
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2023年 / 29卷 / 06期
基金：
中国国家自然科学基金;
关键词：
cloud-fog-edge collaboration; convolution neural network; digitaltwin; disturbance identification;
D O I：
10.13196/j.cims.2023.06.017
中图分类号：
学科分类号：
摘要：
Modeling and simulation has become one of the core technologies in manufacturing industry. However, the existing simulation technology is insufficient for the dynamic response of the manufacturing process. Digital twin provides a solution for dynamic mapping of the simulation system to manufacturing process. At present, there arc still existing the following problems: (1) it is difficult to recognize dynamic disturbances in the process of equipment operation, and the training process of disturbance identification model is limited by computing and data resources, which is time-consuming; (2) data utilized for identification of dynamic disturbance and update of constraints arc offline or semi-offline, which can not meet the requirements of real-time response. To solve the above problems, a method for responding to dynamic disturbances in digital twin manufacturing simulation process based on cloud-fog-edge collaboration was proposed. In the cloud, a universal model was trained by public data sets, and a personalized model further was trained by edge data to improve the accuracy of disturbance recognition. In the fog, the personalized model was deployed to ensure the speed of disturbance recognition, while the recognized disturbance wasupdatedtothe digitaltwinsimulation model.Intheedgeend, real-timesignals werecolected and uploaded to thefog end.Theexperimentalresults showedthatthe disturbance constraint updating mechanism could accurately updatethe disturbanceand makeaquick responsetothe disturbance during operation. © 2023 CIMS. All rights reserved.
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页码：1996 / 2005
页数：9
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