杨文虎,牛世斌,李翔,荣誉佳,王浩帆,方顺利,晋中华,马帅,舒朝晖

• 1:兰州铝业有限公司
• 2:西安热工研究院有限公司
• 3:华中科技大学能源与动力工程学院

摘要(Abstract)：

作为反映燃烧过程的重要参数，炉内温度分布关系到炉内燃烧过程的安全性、经济性和污染物排放的水平，对于研究锅炉控制和炉内燃烧过程具有十分重要的意义。辐射成像法由于时空分辨率高、现场容易实施等特点，适用于炉内温度场的重建。基于此，提出了一种基于光学层析的炉内温度场在线测量技术，采用深度学习与正则化算法相结合的重建算法来解决温度场重建过程中的病态问题。首先，根据设置的炉膛尺寸、介质辐射特性、CCD摄像机安装位置等参数建立辐射成像模型，通过正问题计算获得大量数据；然后，通过自动寻优算法找到合适的Tikhonov正则化参数构建训练数据集，同时评估解的精确性和稳定性；最后，建立深度神经网络模型预测最优的正则化参数，进而对温度场进行重建。结果表明，所提出的炉内温度场重建算法的误差小于5%，准确性较好。在加入测量误差后，重建误差仍在5%之内，表明该方法具有鲁棒性。同时，该方法计算效率较高，能满足温度场实时监测的要求。

关键词(KeyWords)： 燃煤锅炉;温度场;光学层析;在线测量;深度神经网络

Abstract:

Keywords:

基金项目(Foundation): 国家重点研发计划项目（2024YFB4104804）~~

作者(Author): 杨文虎,牛世斌,李翔,荣誉佳,王浩帆,方顺利,晋中华,马帅,舒朝晖

DOI: 10.19666/j.rlfd.202504058

参考文献(References)：

• [1]周怀春.炉内火焰可视化检测原理与技术[M].北京:科学出版社, 2005:1.ZHOU Huaichun. Principles and techniques of in-furnace flame visualization detection[M]. Beijing:Science Press,2005:1.
• [2] BALLESTER J, GARC??A-ARMINGOL T. Diagnostic techniques for the monitoring and control of practical flames[J]. Progress in Energy and Combustion Science,2010, 36:375-411.
• [3]娄春.工程燃烧诊断学[M].北京:中国电力出版社,2016:1.LOU Chun. Engineering combustion diagnostics[M].Beijing:China Electric Power Press, 2016:1.
• [4] KONG Q, JIANG G S, LIU Y C, et al. 3D high-quality temperature-field reconstruction method in furnace based on acoustic tomography[J]. Applied Thermal Engineering, 2020, 179:115693.
• [5]张雅琪,王飞,崔海滨.基于固定波长法吸收光谱技术的CO2温度测量[J].激光与光电子学进展, 2019,56(19):278-283.ZHANG Yaqi, WANG Fei, CUI Haibin. Application of TDLAS to the measurement of temperature and concentration of gas components in a power station boiler furnace temperature measurement of carbon dioxide using fixed-wavelength absorption spectroscopy technique[J].Laser&Optoelectronics Progress, 2019, 56(19):278-283.
• [6]胡逸凡,刘勇.基于光学相干层析的三维温度测量技术[J].光学与光电技术, 2023, 21(5):91-98.HU Yifan, LIU Yong. Three-dimensional temperature measurement technology based on optical coherence tomography[J]. Optics&Optoelectronic Technology,2023, 21(5):91-98.
• [7] LOU C, ZHOU H C. Deduction of the two-dimensional distribution of temperature in a cross section of a boiler furnace from images of flame radiation[J]. Combustion and Flame, 2005, 143:97-105.
• [8] LIU D, YAN J H, WANG F, et al. Experimental reconstructions of flame temperature distributions in laboratory-scale and large-scale pulverized-coal fired furnaces by inverse radiation analysis[J]. Fuel, 2012, 93:397-403.
• [9]娄春,张鲁栋,蒲旸,等.基于自发辐射分析的被动式燃烧诊断技术研究进展[J].实验流体力学, 2021,35(1):1-17.LOU Chun, ZHANG Ludong, PU Yang, et al. Research advances in passive techniques for combustion diagnostics based on analysis of spontaneous emission radiation[J]. Journal of Experiments in Fluid Mechanic,2021, 35(1):1-17.
• [10]廖鹏昊,汪玉琴,李佳文,等.燃烧喷焰的红外辐射特性分析[J].光学与光电技术, 2024, 22(2):122-130.LIAO Penghao, WANG Yuqin, LI Jiawen, et al. Analysis of infrared radiation characteristics of combustion flames[J]. Optics&Optoelectronic Technology, 2024,22(2):122-130.
• [11]夏守之,朱新旺,姚琦琦.热辐射率对火焰温度测量精度影响的研究[J].光学与光电技术, 2008, 34(5):72-75.XIA Shouzhi, ZHU Xinwang, YAO Qiqi. Measuring accuracy of the flame temperature based on combustion emissivity[J]. Optics&Optoelectronic Technology, 2008,34(5):72-75.
• [12]闫慧博,唐广通,李路江,等.热辐射成像法测量大型炉膛内三维温度场的算法新进展[J].洁净煤技术,2022, 28(5):97-108.YAN Huibo, TANG Guangtong, LI Lujiang, et al. New progress of algorithm for three-dimensional temperature field in large scale furnace measured by thermal radiative imaging[J]. Clean Coal Technology, 2022, 28(5):97-108.
• [13]周怀春,李框宇,安元,等.燃煤电站锅炉及工业窑炉三维燃烧温度分布监测研究进展[J].洁净煤技术,2022, 28(10):1-15.ZHOU Huaichun, LI Kuangyu, AN Yuan, et al. Research progress of measuring three-dimensional temperature distributions in coal-fired boilers and industrial furnaces[J]. Clean Coal Technology, 2022, 28(10):1-15.
• [14]方顺利,晋中华,杨云,等.面向深度调峰和智能发电的炉膛温度场在线监测及预测综述[J].热力发电,2025, 54(4):13-23.FANG Shunli, JIN Zhonghua, YANG Yun, et al. Review of furnace temperature field online monitoring and prediction for deep peaking and smart power generation[J]. Thermal Power Generation, 2025, 54(4):13-23.
• [15]郭子申,董美蓉,叶托,等.基于k近邻和数值模拟的锅炉炉膛温度场在线重建[J].工业炉, 2021, 43(6):1-5.GUO Zishen, DONG Meirong, YE Tuo, et al.Reconstruction of furnace temperature field based on knearest neighbor and numerical simulation[J]. Industrial Furnace, 2021, 43(6):1-5.
• [16]唐广通,许烨烽,闫慧博,等.基于深度学习与热辐射成像耦合的炉内温度场在线测量[J].动力工程学报,2022, 42(10):960-966.TANG Guangtong, XU Yefeng, YAN Huibo, et al.Research of on-line measurement of temperature field in furnaces based on deep learning coupled thermal radiative imaging[J]. Journal of Chinese Society of Power Engineering, 2022, 42(10):960-966.
• [17] XUE W Y, TANG Z H, CAO S X, et al. A novel online method incorporating computational fluid dynamics simulations and neural networks for reconstructing temperature field distributions in coal-fired boilers[J].Energy, 2024, 286:129568.
• [18]任世鹏,安元,娄春,等.融合深度学习算法的炉内燃烧温度场分布在线重建[J].化工进展, 2025, 44(2):301-310.REN Shipeng, AN Yuan, LOU Chun, et al. Online reconstruction of combustion temperature field distribution in furnace by integrating deep learning algorithm[J]. Chemical Industry and Engineering Progress, 2025, 44(2):301-310.