数字孪生技术在水厂设备预测性维护中的应用研究  

Research on the Application of Digital Twin Technology in Predictive Maintenance of Water Plant Equipment

作　　者：季慕州 JI Muzhou(ShangHai Municipal Engineering Design Institute(Group)Co.,Ltd.)

机构地区：[1]上海市政工程设计研究总院(集团)有限公司

出　　处：《中国建设信息化》2024年第4期47-51,共5页Informatization of China Construction

摘　　要：针对水厂设备维护管理难度大的问题,研究利用数字孪生技术构建数字模型,并在故障预测中引入自组织映射神经网络,对水厂设备进行预测性维护。通过BIM技术构建水厂设备数字孪生底座,利用传感器、通讯网络等实现设备状态和关键参数的集成展示与实时监测,并结合自组织映射神经网络创建故障预测模型,制定相应的维护方案,通过数字孪生驾驶舱进行综合展示,为管理者提供全面的决策支持。结果表明,基于数字孪生的预测性维护管理显著减少了设备故障停机时间和维护成本,提高了设备管理效率。Aiming at the difficulty of equipment maintenance and management in waterworks,this paper studies the use of digital twin technology to build a digital model,and introduces self-organizing mapping neural network into fault prediction to carry out predictive maintenance of waterworks equipment.Through BIM technology,the digital twin base of waterworks equipment is constructed,and the integrated display and real-time monitoring of equipment status and key parameters are realized by using sensors and communication networks.Combined with self-organizing mapping neural network,the fault prediction model is established,and the corresponding maintenance scheme is formulated.The digital twin cockpit is comprehensively displayed to provide comprehensive decision support for managers.The results show that the predictive maintenance management based on digital twins significantly reduces the downtime and maintenance cost of equipment,and improves the efficiency of equipment management.

关 键 词：数字孪生 水厂设备 BIM技术 自组织映射网络 预测性维护 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]