Digital Twin-Based Vibration Monitoring of Plant Factory Transplanting Machine
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Published:2023-11-09
Issue:22
Volume:13
Page:12162
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ISSN:2076-3417
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Container-title:Applied Sciences
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language:en
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Short-container-title:Applied Sciences
Author:
Chen Kaikang12ORCID, Zhao Bo2, Zhang Yanli2, Zhou Liming2, Niu Kang2, Jin Xin3, Xu Bingbing3, Yuan Yanwei2, Zheng Yongjun1
Affiliation:
1. Department of Electrical and Mechanical Engineering, College of Engineering, China Agricultural University, Beijing 100089, China 2. National Key Laboratory of Agricultural Equipment Technology, Chinese Academy of Agricultural Mechanization Sciences, Beijing 100083, China 3. College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471003, China
Abstract
In response to the problem of bowl seedling detachment caused by the shaking of the transplanting machine in plant factories, this paper proposes a physical entity monitoring method for the digital twin (DT) plant factory transplanting system. The method is used to analyze the vibration signals of the transplanting machine under different operating conditions and explore the optimal working conditions. Firstly, a demand analysis for the physical entity of the DT plant factory transplanting system is conducted, focusing on practical applications. Then, an optimal deployment plan is designed based on the axiomatic design (AD) theory. Subsequently, a comparative analysis of the operating conditions of the plant factory transplanting equipment is carried out using data-driven approaches. Finally, the optimal working condition parameters are determined by comparing the modal vibration power spectral density of the transplanting equipment under different operating conditions. The results show that the maximum amplitude occurs in the Z-axis, with a magnitude of 2.1 m/s2. By comparing the cloud maps, it is evident that the vibration trends in the Z-axis and X-axis above the transplanting robotic arm are more pronounced compared to the Y-axis. This indicates that under the operating condition of transplanting 3000 plants per hour, a high transplanting efficiency can be maintained, and the vibration signals in the XYZ-axis above the transplanting robotic arm are relatively smooth, making them suitable for transplanting operations. This study combines digital twin technology to analyze the vibration signals of the plant factory transplanting machine under different operating conditions and explore the optimal working conditions. Compared to traditional monitoring platforms, this method facilitates the real-time visualization of different operating conditions of the transplanting machine in a virtual mapping, providing a more intuitive reflection of the equipment operation status.
Funder
The National Key Research and Development Program of China Sub-project
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Reference31 articles.
1. Plant factory technology lights up urban horticulture in the post-coronavirus world;Zhang;Hortic. Res.,2022 2. Digital twins in smart farming;Verdouw;Agric. Syst.,2021 3. Liu, Y., Mousavi, S., Pang, Z., Ni, Z., Karlsson, M., and Gong, S. (2022). Plant Factory: A New Playground of Industrial Communication and Computing. Sensors, 22. 4. Ebrahimi, A. (2019, January 2–14). Challenges of developing a digital twin model of renewable energy. Proceedings of the 28th IEEE International Symposium on Industrial Electronics (IEEE-ISIE), Vancouver, BC, Canada. 5. Introducing digital twins to agriculture;Pylianidis;Comput. Electron. Agric.,2021
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