摘要
针对液压油泵车试验台传统健康监测方法依赖周期性物理检查和维护、信息化程度低、生产效率不足等问题,提出了一种基于数字孪生的液压油泵车试验台监测系统应用开发架构。该架构集数据、模型和通信于一体,旨在提升设备的预测性维护水平和运行效率。通过构建设备数字孪生虚拟模型,利用TCP/IP协议和统一JSON数据包格式,实现物理设备与虚拟模型之间的实时数据交互与融合。在此基础上,系统能够对液压油泵车试验台进行模拟仿真、数值预测、故障诊断和预警,从而优化设备运行状态。试验结果表明,该系统能够实现液压油泵车实现的健康监测和故障诊断,在航空试验台应用方面有着广阔的前景。
Aiming to address the limitations of traditional health monitoring methods of hydraulic oil pump truck testbed,such as reliance on periodic physical inspections and maintenance,low levels of informatization,and insufficient production efficiency,an application development architecture for a hydraulic oil pump truck monitoring system was proposed based on digital twin technology.This architecture integrates data,models,and communication to improved the predictive maintenance level and operational efficiency of the equipment.The research enabled real-time data interaction and fusion between the physical equipment and the virtual model by constructing a digital twin virtual model of the equipment and utilizing the TCP/IP protocol and a unified JSON packet format.On this basis,the system could perform simulation,numerical prediction,fault diagnosis,and early warning for the hydraulic oil pump truck testbed,thereby optimizing the equipment’s operation status.Test results show that the system is able to perform health monitoring and fault diagnosis for the hydraulic oil pump truck,showing broad prospects in the application of aviation testbed.
作者
王坤
王共冬
WANG Kun;WANG Gongdong(College of Aerospace Engineering,Shenyang Aerospace University,Shenyang 110136,China)
出处
《沈阳航空航天大学学报》
2025年第6期46-54,共9页
Journal of Shenyang Aerospace University
基金
国家自然科学基金(项目编号:52374393)
辽宁省重点研发计划项目(项目编号:2023JH2,101300234)。
关键词
数字孪生
液压油泵车试验台
监测系统
健康监测
数值预测
digital twin
hydraulic oil pump truck testbed
monitoring system
health monitoring
numerical prediction
