为了提高放射性识别效果，保证集装箱运输的安全性与平稳性，研究物联网下船舶运输集装箱放射性监测技术。构建物联网下船舶运输集装箱放射性监测框架，无线终端采集模块通过NaI(T1)γ能谱仪、GPS/AIS接收模块采集存放于货舱的各集装箱放射性能谱数据等，利用Zigbee通信模块将各采集数据上传到船舶监控后台，采用三点重心平滑方法处理放射性能谱数据，获得1024个道址数据，再以32道址为一个数据采样间隔，将其划分为32组时间序列，作为LSMT网络的输入，实现船舶运输集装箱放射性监测。监测结果通过4G移动网络传输给岸基监控中心，结果表明，学习率为10-3时，LSTM网络性能最佳。通过放射性能谱数据可实现集装箱放射性监测，监测结果与实际相符，监测性能突出。
Research on radioactive monitoring technology for ship transport containers under the Internet of Things, improve the recognition effect of radioactive nuclides, and ensure the safety and stability of container transportation. Construct a radioactive monitoring framework for ship transport containers under the internet of things, with wireless terminal acquisition modules using NaI (T1) γ The energy spectrometer and GPS/AIS receiving module collect the radioactive energy spectrum data of each container stored in the ship's cargo hold, and use the Zigbee communication module to upload the collected data to the ship's monitoring background. After processing the radioactive energy spectrum data using the three-point center of gravity smoothing method, 1024 channel data are obtained. Then, with 32 channel addresses as a data sampling interval, they are divided into 32 sets of time series, which are used as inputs to the LSMT network, Realize radioactive monitoring of shipping containers, and the monitoring results are transmitted to the shore based monitoring center through a 4G mobile network. The experimental results show that when the learning rate is 10−3, the LSTM network has the best performance. Through radioactive spectrum data, container radioactivity monitoring can be achieved, and the monitoring results are consistent with the actual situation, with outstanding monitoring performance.
2023,45(18): 182-185 收稿日期：2023-05-16
DOI：10.3404/j.issn.1672-7649.2023.18.034
分类号：U662.9
基金项目：江苏省南通市科技计划项目（MSZ21007）；江苏省南通市科技计划项目（JCZ21072）
作者简介：胡慧慧(1983-),女,硕士,副教授,研究方向为交通运输及港口机械与智能控制
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