基于cGAN的工业加热炉温度场预测方法  

TEMPERATURE FIELD PREDICTION ME-THOD OF INDUSTRIAL HEATING FURNACE BASED ON CGAN

作　　者：刘景明 王艳丽 王婷 Liu Jingming;Wang Yanli;Wang Ting(Equipment Research Institute of SINOPEC(Tianjin)Petrochemical Co.,LTD.,Tianjin,300271)

机构地区：[1]中石化(天津)石油化工有限公司装备研究院,天津300271

出　　处：《石油化工设备技术》2024年第4期20-24,I0001,I0002,共7页Petrochemical Equipment Technology

摘　　要：工业加热炉燃烧过程不稳定,可能会在随机位置出现局部超温,导致炉管损耗和破坏。由于加热炉设备庞大,难以对有关物理量进行在线测量,为此,文章提出在标准工业炉加热炉模型上建立基于条件生成对抗网络的数字孪生模型,通过该模型预测加热炉温度场,并利用Unity3D软件实现可视化,帮助工作人员进行燃烧优化。实验结果表明,cGAN网络架构能够完成温度场预测的工作,在测试集上约80%的节点计算得到的温度绝对误差值在炉内最高温度的1%以下,具有良好的应用前景。The combustion process of industrial heating furnace is unstable and local over-temperature may occur at random locations,leading to furnace tube loss and damage.Since the heating furnace equipment is huge,it is difficult to measure the relevant physical quantity online.Therefore,this paper proposes to build a digital twin model based on the condition generation adversary-network on the standard industrial furnace heating model through which the temperature field of the heating furnace is predicted and the Unity 3D software is used for visualization to help the staff to optimize the combustion.The experimental results show that the cGAN network architecture can predict the temperature field,and the absolute error value of the temperature calculated at about 80% of the nodes within the test set is below 1% of the maximum temperature of the furnace,which is promising for the application.

关 键 词：在线预测 三维温度场 工业加热炉 cGAN Unity3D可视化 

分 类 号：TQ054[化学工程]