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| Online Monitoring Technology of Pontoon Motion Attitude Based on Edge-cloud Collaboration Computing |
| Received:May 23, 2023 Revised:June 29, 2023 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7643/issn.1672-9242.2023.09.015 |
| KeyWord:edge computing kalman filter pontoon IoT platform edge-cloud collaboration attitude monitoring |
| Author | Institution |
| XU Hao |
China Ship Scientific Research Center, Jiangsu Wuxi , China |
| REN Yan-xi |
Unit 32212, Beijing , China |
| ZHANG Tao |
China Ship Scientific Research Center, Jiangsu Wuxi , China;Taihu Laboratory of Deep Sea Technology and Science, Jiangsu Wuxi , China |
| WANG Xue-liang |
China Ship Scientific Research Center, Jiangsu Wuxi , China;Taihu Laboratory of Deep Sea Technology and Science, Jiangsu Wuxi , China |
| ZHU Quan-hua |
China Ship Scientific Research Center, Jiangsu Wuxi , China;Taihu Laboratory of Deep Sea Technology and Science, Jiangsu Wuxi , China |
| CHEN Guo-cai |
China Ship Scientific Research Center, Jiangsu Wuxi , China |
| ZHANG Pu |
China Ship Scientific Research Center, Jiangsu Wuxi , China;Taihu Laboratory of Deep Sea Technology and Science, Jiangsu Wuxi , China |
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| Abstract: |
| The work aims to solve the problem in synchronous monitoring of the motion attitude of multi-module floating bodies on the water surface in discrete and tandem states. Multiple edge computing nodes were used to collect structural attitude data at the same time based on edge-cloud collaboration technology, and transmit the data to the IoT platform in real time through 5G wireless technology for analysis and monitoring, so as to realize the rapid monitoring of target structural attitude. Firstly, according to the characteristics of attitude monitoring of temporary structures, the overall design architecture and operation logic of the attitude monitoring system were analyzed. Secondly, the functional modules of IoT platform software and edge computing nodes were analyzed and designed. Finally, the monitoring system was verified by real ship test. The monitoring system realized the edge acquisition and processing of multiple floating body attitude data, and the date could be transmitted to the IoT platform through the wireless network for storage and analysis. Under the same working condition, the attitude of adjacent pontoon bridges had consistency and correlation. The attitude change of the middle pontoon bridge was smaller under the traction condition, and the attitude change of the middle pontoon bridge under the jacking condition was bigger. This technology can monitor the attitude changes of multi-floating structures under different working conditions, which has certain practical value for synchronous monitoring and data fusion processing of multiple floats. |
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