基于数字孪生的火电厂设备状态监测与故障诊断研究

Research on equipment condition monitoring and fault diagnosis of thermal power plants based on digital twin

  • 摘要: 为提升火电厂运维管理的智能化与精细化水平,提出一种基于数字孪生平台的设备状态监测与故障诊断方法。该方法以高精度三维模型为物理载体,深度融合内在数理模型与多源异构数据,构建了贯穿电厂全生命周期的虚拟现实映射体系,通过对可视化查询、动态呈现、模型驱动的故障诊断及三维联动定位等关键技术的研究与实现,形成了从数据集成、状态监测到故障诊断的完整应用闭环。

     

    Abstract: In order to enhance the intelligence and refinement level of operation and maintenance management in thermal power plants, this paper proposes a device status monitoring and fault diagnosis method based on a digital twin platform. This method uses high-precision 3D models as physical carriers, deeply integrates internal mathematical models with multi-source heterogeneous data, and constructs a virtual reality mapping system that runs through the entire life cycle of the power plant. Through the research and implementation of key technologies such as visual query, dynamic presentation, model driven fault diagnosis, and 3D linkage positioning, a complete application loop from data integration, status monitoring to fault diagnosis is formed.

     

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