基于数字孪生的船舶预测性维护系统

针对造船技术和需求的发展，使得船舶维护面临着成本不断上升的问题，提出面对高端复杂船舶采用数字孪生技术进行预测性维护。在研究了数字孪生预测性维护模型模型基础上，将其分为创建数字孪生体、数据获取、数据预处理、模型训练、故障预测与诊断和设备维护六个阶段，并分别介绍了各阶段的主要任务和技术。最后分析总结了进行数字孪生船舶预测性维护难点及发展路径。

Ship predictive maintenance system based on digital twins

In view of the development of shipbuilding technology and demand, ship maintenance is facing the problem of rising costs. It is proposed to use digital twin technology for predictive maintenance in the face of high-end complex ships. After studying the basics of the digital twin predictive maintenance model, it is divided into six stages of creating digital twins, data acquisition, data preprocessing, model training, fault prediction and diagnosis, and equipment maintenance, and introduces the main stages of each stage. Tasks and technology. Finally, it analyzes and summarizes the difficulties and future development of predictive maintenance of digital twin ships.