通过自然水域的周期性实验，对水文、自然条件、检测频率与船舶吃水深度数据检测精度的关系进行验证，解决了数据采集的准确性、稳定性和复用性技术难题。基于浮式平台动态补偿、传感器集群组网、船舶实时位置信息推演算法等关键技术，研发了基于复杂水域环境的动态船舶吃水检测系统，实现船舶航行状态吃水数据自动检测及采集，为船舶吃水深度数据的检测、监测技术的推广应用奠定了基础。
Through periodic experiments in areas of natural water, the relationships between the hydrology, natural conditions, detection frequency and detection accuracy of ship draft depth data were verified, and technical problems of accuracy, stability and re-usability of data collection were solved. Based on key techniques such as dynamic compensation the floating platform, the sensor network cluster, the ship real-time location information inference algorithm, the dynamic ship draft detection system for complex water environment was developed. The system can meet demands of the automatic detection and data sampling for ship draft dept data detection. Besides, the system can provide foundations for application of ship draft depth monitoring technology.
2022,44(8): 182-185 收稿日期：2022-01-10
DOI：10.3404/j.issn.1672-7649.2022.08.039
分类号：U653
作者简介：陈轩(1967-),男,高级工程师,主要从事工程项目管理工作
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