方顺利,晋中华,杨云,李翔,任世鹏,马帅,姚斌,王浩帆,张中晖,梅晟东,刘凯,陈新建,娄春,邹莹

• 1:西安热工研究院有限公司
• 2:西安交通大学
• 3:兰州铝业有限公司
• 4:华中科技大学煤燃烧与低碳利用全国重点实验室

摘要(Abstract)：

在火电机组参与深度调峰时，炉膛温度场的实时获取有助于电站锅炉控制和研究炉内燃烧过程，在智能发电的推进下，机器学习为实时获得炉膛温度场提供了重要手段。总结了声学法、吸收光谱层析成像法以及热辐射成像法这3种最常用的炉膛温度场在线监测技术的原理及应用，以及在锅炉炉膛测温应用中存在的优势及缺点。之后详细阐述了耦合机器学习与CFD的预测方法的原理，说明该方法在恶劣炉内环境中受到的影响较小，综述了该方法在燃烧火焰结构及参数和炉膛温度场的应用研究，表明了该方法应用于炉膛温度场的可行性，并可准确地预测获得炉膛温度场。最后对炉膛温度场在线监测技术和耦合机器学习与CFD的预测方法的未来发展趋势进行了分析，以便在电站智能化建设进程下，为实时快速获得更准确的炉膛温度场提供思路。

关键词(KeyWords)： 电站锅炉;炉膛温度场;在线监测;机器学习;预测

Abstract:

Keywords:

基金项目(Foundation): 国家重点研发计划项目（2022YFB4100703）~~

作者(Author): 方顺利,晋中华,杨云,李翔,任世鹏,马帅,姚斌,王浩帆,张中晖,梅晟东,刘凯,陈新建,娄春,邹莹

DOI: 10.19666/j.rlfd.202408174

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