为实现远距离船舶电子故障分类检测、故障信息有序存储，设计基于RFID技术的船舶电子故障分类编目系统。电子故障信息采集层的无源RFID传感器标签管理模块，采集电子设备电路运行温度、电压与电流信号后，由网络层的船舶内网发送至电子故障分类编目层，此层分类编目模块的故障分类单元，使用基于SVM的船舶电子故障分类模型，将所采集电子设备电路运行信号作为分类样本，分类识别电子故障状态，并由编目单元以E-R表的方式，将分类结果编目存储于数据库单元数据库中。实验以船舶雷达设备为例，验证此系统可使用RFID技术，远距离检测分类此设备光电设备转换模块运行状态，分类结果无误，且故障信息有序存储，写入与读取耗时分别缩短1.5 s、2.0 s，应用价值显著。
To achieve remote electronic fault classification and detection of ships and orderly storage of fault information, a ship electronic fault classification and cataloging system based on RFID technology is designed. The passive RFID sensor label management module of the electronic fault information collection layer collects the operating temperature, voltage, and current signals of electronic equipment circuits, and sends them to the electronic fault classification and cataloging layer through the ship's internal network of the network layer. This layer classifies the fault classification unit of the cataloging module and uses the SVM based ship electronic fault classification model to classify and identify the electronic fault status by using the collected electronic equipment circuit operating signals as classification samples, And the cataloging unit stores the classification results in the database unit database in the form of an E-R table. Taking ship radar equipment as an example, the experiment verifies that this system can use RFID technology to remotely detect and classify the operation status of the photoelectric equipment conversion module of this equipment. The classification results are correct, and the fault information is stored in an orderly manner. The writing and reading time are shortened by 1.5 and 2.0 seconds respectively, indicating significant application value.
2023,45(13): 174-177 收稿日期：2023-03-02
DOI：10.3404/j.issn.1672-7649.2023.13.036
分类号：TN956
作者简介：刘亚飞(1981-)，男，硕士，讲师，主要研究方向为计算机应用
参考文献：
[1] 吴旭升, 杨刚, 孙盼, 等. 舰船电力电子设备测试性设计现状及技术分析[J]. 海军工程大学学报, 2021, 33(2): 14–18
WU Xusheng, YANG Gang, SUN Pan, et al. Analysis of status and technology of testability design for ship power and electronic equipment[J]. Journal of Naval University of Engineering, 2021, 33(2): 14–18
[2] 甘易明, 陈兆楠, 杨淑洁, 等. 中小型渔船通导设备集成系统设计[J]. 渔业现代化, 2020, 47(4): 53–59
[3] 张春林, 程文. 船舶行业设备维修智能管理平台应用实践[J]. 船海工程, 2020, 49(4): 42–45+49
[4] 斯园园. 基于“海洋石油301”船的智能化船岸一体数据管理[J]. 船海工程, 2023, 52(2): 20–24
[5] 贾书丽, 罗昊, 杨青. 无人船舶综合电力系统健康管理技术[J]. 中国造船, 2020, 61(S1): 191–197
[6] 王瑞涵, 陈辉, 管聪. 基于机器学习的船舶机舱设备状态监测方法[J]. 中国舰船研究, 2021, 16(1): 158–167
WANG Ruihan, CHEN Hui, GUAN Cong. Condition monitoring method for marine engine room equipment based on machine learning[J]. Chinese Journal of Ship Research, 2021, 16(1): 158–167
