基于数字孪生的空气预热器预测性维护模式研究

Research on Predictive Maintenance Mode of Air Preheater Based on Digital Twin

【目的】为解决大型火电机组空气预热器传统预防性维护手段的弊端,提出了一种基于数字孪生预测性维护的一般模式,并基于数字孪生技术,构建空气预热器数字孪生系统。【方法】所提系统包括回转式空气预热器物理实体、实时数据采集与分析模块、数字孪生模型构建模块、热力参数状态监测、转子热场视频与热变形可视化及积灰预测模块;实时采集温度参数状态和视频数据,通过温度场、视频图像、漏风计算等模块,实现热力参数的计算并进行积灰的预测。同时,以3D组态画面实时显示数据,利用软件算法不断优化热力参数计算及积灰预测的准确度,实现吹灰策略自动优化。【结果】所提方案实现了空气预热器热力计算过程的状态监测与动态控制,解决现有电站中回转式空气预热器积灰因素影响火电机组安全可靠运行的问题。【结论】通过实际机组的工程测试,所提方案有效提高了火电机组空气预热器运行维护的效率,验证了所提方法的可行性,为后期智慧电厂系统的开发提供技术支撑。

[Objectives]In order to solve the shortcomings of the traditional preventive maintenance method of air preheater in large thermal power unit,a general mode of predictive maintenance based on digital twin was proposed,and the digital twin system of air preheater was constructed based on digital twin technology.[Methods]The proposed system included physical entity of rotary air preheater,real-time data acquisition and analysis module,digital twin model construction module,thermal parameter state monitoring,rotor thermal field video and thermal deformation visualization and ash accumulation prediction module.By the real-time acquisition of temperature parameter state and video data,and through the temperature field,video image,air leakage calculation and other modules,the calculation of thermal parameters and the prediction of ash accumulation were realized.At the same time,the 3D configuration screen was used to display data in real time,continuously optimize the accuracy of thermal parameter calculation and ash accumulation prediction,and realize the automatic optimization of soot-blowing strategy.[Results]The proposed scheme realizes the state monitoring and dynamic control of the thermal calculation process of the air preheater,and solves the problem that the ash accumulation factor of the rotary air preheater in the existing power station affects the safe and reliable operation of the thermal power unit.[Conclusions]Through engineering testing of actual units,the proposed scheme effectively improves the operation and maintenance efficiency of the air preheater of thermal power units,verifies the feasibility of the proposed method,and provides technical support for the development of smart power plant systems in future.