Article(id=1211002411502670662, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1210998030828958715, articleNumber=null, orderNo=null, doi=10.19666/j.rlfd.202310166, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1696867200000, receivedDateStr=2023-10-10, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1766655074238, onlineDateStr=2025-12-25, pubDate=1706112000000, pubDateStr=2024-01-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1766655074238, onlineIssueDateStr=2025-12-25, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1766655074238, creator=13701087609, updateTime=1766655074238, updator=13701087609, issue=Issue{id=1210998030828958715, tenantId=1146029695717560320, journalId=1210938733613449225, year='2024', volume='53', issue='1', pageStart='1', pageEnd='196', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1766654029805, creator=13701087609, updateTime=1766734793553, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1211336778607366994, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1210998030828958715, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1211336778611561299, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1210998030828958715, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=24, endPage=37, ext={EN=ArticleExt(id=1211002414694536036, articleId=1211002411502670662, tenantId=1146029695717560320, journalId=1210938733613449225, language=EN, title=Research progress on online in-furnace monitoring techniques during high-alkali coal combustion based on spontaneous emission radiation analysis, columnId=1210998031487464445, journalTitle=Thermal Power Generation, columnName=High proportion combustion technology for high-alkali coal, runingTitle=null, highlight=null, articleAbstract=

High-alkali coal such as Zhundong coal has huge reserves in Xinjiang, in which rich alkali metal elements can easily lead to fouling and slagging problem on heating surface of the furnace, thus to decrease the safety of boiler. It is of great significance to develop efficient and clean combustion power generation technology for high-alkali coal to achieve the “double-carbon” goal. The research progress of the online monitoring technology in high-alkali coal combustion furnace based on spontaneous emission radiation analysis is summarized. The development trend and dynamics are discussed focusing on the research status and application of emission spectrum technology and spontaneous emission radiation imaging and image processing technology in high-alkali coal combustion monitoring. Emission spectroscopy can obtain the temperature and component concentration by processing the spectral radiation signal emitted by the flame at different wavelengths. Recently, it has been widely used to measure the combustion temperature and the gaseous alkali metal concentration in the industrial furnace and judge the slagging trend in the furnace qualitatively. Different from emission spectroscopy technology, spontaneous emission radiation imaging and image processing technology has the ability to analyze the spatial distribution of signals. The technology obtains the spontaneous radiation image in the furnace via CCD, CMOS and other surface array sensors. Based on image processing technology and thermal radiation imaging theory, the temperature distribution of the combustion field in three-dimensional space can be obtained combining with solving radiation inverse problem, which makes it possible to monitor the three-dimensional visual of slagging formation. In the future, monitoring of the fouling and slagging on the heating surface in two or three dimensions should be carried out based on emission spectroscopy technology, spontaneous emission radiation imaging and image processing technology. Combined with the distribution of parameters such as combustion temperature and gaseous alkali metal concentration in the furnace, a quantitative judgmental index of fouling and slagging on the heating surface of high-alkali coal combustion should be established to achieve the goal of online prediction of fouling and slagging on the heating surface.

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准东煤等高碱煤在新疆地区储量巨大,但其富含的碱金属元素极易导致炉膛受热面沾污、结渣等问题,会影响锅炉运行的安全性,研发高碱煤高效清洁燃烧发电技术对实现“双碳”目标有重要意义。总结了基于自发辐射分析的高碱煤燃烧炉内在线监测技术的研究进展,重点介绍了发射光谱技术、自发辐射图像处理及成像技术在高碱煤燃烧监测领域的研究现状及应用情况,进而对其发展趋势和动态进行探讨。发射光谱技术通过对火焰发出的不同波长光谱辐射信号进行处理获取温度与组分,近期,已广泛用于测量工业炉膛燃烧火焰温度和气相碱金属质量浓度,并基于此对炉内结渣趋势进行定性判断。自发辐射图像处理及成像技术具备信号空间分布的解析能力,利用CCD、CMOS等面阵传感器获取炉内自发辐射图像,基于图像处理与热辐射成像原理,结合辐射反问题求解方法,可以获得燃烧场在三维空间的温度分布以及二维壁温分布,使结渣的三维可视化监测成为可能。未来需基于发射光谱技术、自发辐射图像处理及成像技术对二维或者三维的受热面结渣沾污进行监测,结合炉内燃烧温度与气相碱金属质量浓度等参数分布,建立高碱煤燃烧受热面结渣沾污的定量判断指标,最终达到对受热面结渣沾污在线预测的目标。

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方顺利(1985),男,博士,高级工程师,主要研究方向为火电厂燃煤掺配烧系统开发、锅炉燃烧参数监测技术的开发应用,
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陈装(1965),男,高级工程师,主要从事火力发电厂生产管理工作,

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figureFileSmall=KKR7z6ausrk1kURUIzBYaQ==, figureFileBig=EjeMtQlr75ORChCCBIMFng==, tableContent=null), ArticleFig(id=1211002428451852833, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=CN, label=图5, caption=液态排渣旋风燃烧试验炉发射光谱测量系统, figureFileSmall=KKR7z6ausrk1kURUIzBYaQ==, figureFileBig=EjeMtQlr75ORChCCBIMFng==, tableContent=null), ArticleFig(id=1211002428569293350, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=EN, label=Fig.6, caption=The temperature and gaseous Na mass concentration in slagging-type cyclone-fired test furnace, figureFileSmall=UunsN2XAhKYve8uyEmESeQ==, figureFileBig=jMGVzAvGqQvS/Mqmwvb0cg==, tableContent=null), ArticleFig(id=1211002428678345257, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=CN, label=图6, caption=液态排渣旋风试验炉内气相钠质量浓度和温度, figureFileSmall=UunsN2XAhKYve8uyEmESeQ==, figureFileBig=jMGVzAvGqQvS/Mqmwvb0cg==, tableContent=null), ArticleFig(id=1211002428779008557, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=EN, label=Fig.7, caption=Schematic diagram of the boiler and measuring points, figureFileSmall=8q24ZEjT2viqfqp/7aoKKA==, figureFileBig=w0cYhz3H+D9QMC7J7bE+5g==, tableContent=null), ArticleFig(id=1211002428883866162, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=CN, label=图7, caption=锅炉及测点示意, figureFileSmall=8q24ZEjT2viqfqp/7aoKKA==, figureFileBig=w0cYhz3H+D9QMC7J7bE+5g==, tableContent=null), ArticleFig(id=1211002428984529461, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=EN, label=Fig.8, caption=The on-line measurement system of temperature and gaseous sodium mass concentration in coal-fired furnace, figureFileSmall=s2r5zojso/V4uGroG4c1ZA==, figureFileBig=+QhjdFhAd7y0aRQIFb9Lvg==, tableContent=null), ArticleFig(id=1211002429072609850, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=CN, label=图8, caption=炉内燃烧温度\气相钠质量浓度在线监测系统, figureFileSmall=s2r5zojso/V4uGroG4c1ZA==, figureFileBig=+QhjdFhAd7y0aRQIFb9Lvg==, tableContent=null), ArticleFig(id=1211002429173273149, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=EN, label=Fig.9, caption=The 24-hour continuous monitoring data of temperature and gaseous sodium mass concentration in a 660 MW unit boiler, figureFileSmall=X9aI2o2pQFwdFZqw7Vg/kQ==, figureFileBig=hIithSZYmLQC7yLs0k5wsA==, tableContent=null), ArticleFig(id=1211002429265547842, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=CN, label=图9, caption=660 MW机组炉内温度/气相钠质量浓度24 h监测数据, figureFileSmall=X9aI2o2pQFwdFZqw7Vg/kQ==, figureFileBig=hIithSZYmLQC7yLs0k5wsA==, tableContent=null), ArticleFig(id=1211002430486090308, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=EN, label=Fig.10, caption=Interface of boiler prevention system coupling measurement of gaseous alkali metal in the furnace, figureFileSmall=Wr+kYB0IfNqpGSibVKpEmQ==, figureFileBig=YSTLVtGlKj52pXbm6kIJ4g==, tableContent=null), ArticleFig(id=1211002430578364998, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=CN, label=图10, caption=耦合炉内气相碱金属检测锅炉结渣预报系统界面, figureFileSmall=Wr+kYB0IfNqpGSibVKpEmQ==, figureFileBig=YSTLVtGlKj52pXbm6kIJ4g==, tableContent=null), ArticleFig(id=1211002430695805516, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=EN, label=Fig.11, caption=Spectral image detection system in opposed multi-burner gasifier, figureFileSmall=Kd4/4+ALU+labShKi25H8w==, figureFileBig=s26D1xvBrN08eSpRMTpvUw==, tableContent=null), ArticleFig(id=1211002430775497293, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=CN, label=图11, caption=多喷嘴对置式气化炉光谱图像检测系统, figureFileSmall=Kd4/4+ALU+labShKi25H8w==, figureFileBig=s26D1xvBrN08eSpRMTpvUw==, tableContent=null), ArticleFig(id=1211002430884549202, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=EN, label=Fig.12, caption=Infrared thermal image of superheater in a coal-fired boiler of 330 MW unit, figureFileSmall=nHfSgEuN4ao82d52D5dWJA==, figureFileBig=WQYoMpgSmwEcYnmXgxUKRg==, tableContent=null), ArticleFig(id=1211002430960046673, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=CN, label=图12, caption=330 MW机组燃煤锅炉过热器红外热图像, figureFileSmall=nHfSgEuN4ao82d52D5dWJA==, figureFileBig=WQYoMpgSmwEcYnmXgxUKRg==, tableContent=null), ArticleFig(id=1211002431014572625, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=EN, label=Fig.13, caption=Infrared thermal image of water wall in a coal-fired boiler of 330 MW unit, figureFileSmall=rlqkbp7bkjBuv2XqkNOO0w==, figureFileBig=SsAKKy4EXdGpJNJ2GoOuoA==, tableContent=null), ArticleFig(id=1211002431069098580, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=CN, label=图13, caption=330 MW机组燃煤锅炉水冷壁红外热图像, figureFileSmall=rlqkbp7bkjBuv2XqkNOO0w==, figureFileBig=SsAKKy4EXdGpJNJ2GoOuoA==, tableContent=null), ArticleFig(id=1211002431148790360, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=EN, label=Fig.14, caption=Schematic of wall temperature on-line monitoring system, figureFileSmall=wT2TucBGVYA+04EJLAyHOA==, figureFileBig=Zxitd9YWl2+K5CCQPAAmtg==, tableContent=null), ArticleFig(id=1211002431228482139, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=CN, label=图14, caption=壁面温度在线监测系统结构, figureFileSmall=wT2TucBGVYA+04EJLAyHOA==, figureFileBig=Zxitd9YWl2+K5CCQPAAmtg==, tableContent=null), ArticleFig(id=1211002431337534047, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=EN, label=Fig.15, caption=Principle of thermal radiative imaging technique in furnace, figureFileSmall=GzTmC/VuVJB4FP7dd0/tkg==, figureFileBig=l3k/CKD0imHBhVkPh7MYrg==, tableContent=null), ArticleFig(id=1211002431396254304, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=CN, label=图15, caption=炉内热辐射成像技术原理, figureFileSmall=GzTmC/VuVJB4FP7dd0/tkg==, figureFileBig=l3k/CKD0imHBhVkPh7MYrg==, tableContent=null), ArticleFig(id=1211002431463363171, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=EN, label=Fig.16, caption=The on-line monitored heat flux distribution of furnace wall in a coal-fired boiler of 200 MW unit, figureFileSmall=W5I3gHdRjZROBBIGiZ0v+A==, figureFileBig=sKi4iZjHOyz7oV2TYdhJzQ==, tableContent=null), ArticleFig(id=1211002431538860647, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=CN, label=图16, caption=200 MW燃煤机组锅炉壁面热流分布在线监测结果, figureFileSmall=W5I3gHdRjZROBBIGiZ0v+A==, figureFileBig=sKi4iZjHOyz7oV2TYdhJzQ==, tableContent=null), ArticleFig(id=1211002431664689769, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=EN, label=Fig.17, caption=Temperature distributions of tube surface in steam side of front wall in a boiler of 300 MW unit (℃), figureFileSmall=MtA7+zL80GH8LNR1lmqneA==, figureFileBig=lKET16uMr4Z44byO3/JHtg==, tableContent=null), ArticleFig(id=1211002431782130284, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=CN, label=图17, caption=300 MW燃煤机组锅炉前墙水冷壁管壁温度分布(℃), figureFileSmall=MtA7+zL80GH8LNR1lmqneA==, figureFileBig=lKET16uMr4Z44byO3/JHtg==, tableContent=null), ArticleFig(id=1211002431882793583, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=EN, label=Tab.1, caption=

Comparison of various on-line measurement systems

, figureFileSmall=null, figureFileBig=null, tableContent=
系统名称开发时间系统组成监测变量应用场景优点
煤气化炉光谱检测系统2014年光纤、光谱仪、光学探头、计算机等火焰温度煤粉气化炉精确度高、设备运行稳定、适用性好
立式旋风炉发射光谱检测系统2021年光谱仪、探头、光纤、计算机等火焰温度、气相钠盐质量浓度、辐射率100 kW立式旋风炉精确度高、设备便携、运行稳定、适用性好
液态排渣旋风燃烧试验炉发射光谱测量系统2022年光纤、准直透镜、平板电脑等碱金属质量浓度、火焰温度液态排渣旋风试验炉实时监测数据更新间隔短、灵敏度高、功耗低
炉内燃烧温度\气相钠质量浓度在线监测系统2022年光谱探头、工控机、通信线缆、在线监测软件等气相钠质量浓度、火焰温度660 MW准东煤发电机组锅炉稳定性好、光谱采样时间短、灵敏度高、响应时间快
耦合炉内气相碱金属检测的锅炉结渣预报系统2023年光学探头、信号线缆、控制盒、计算机系统、专用监测软件等碱金属质量浓度、火焰温度、结渣程度350 MW机组燃煤锅炉稳定好、光谱采样时间短、可在线对结渣趋势进行判断、系统操作简便
), ArticleFig(id=1211002431954096754, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=CN, label=表1, caption=

各在线监测系统比较

, figureFileSmall=null, figureFileBig=null, tableContent=
系统名称开发时间系统组成监测变量应用场景优点
煤气化炉光谱检测系统2014年光纤、光谱仪、光学探头、计算机等火焰温度煤粉气化炉精确度高、设备运行稳定、适用性好
立式旋风炉发射光谱检测系统2021年光谱仪、探头、光纤、计算机等火焰温度、气相钠盐质量浓度、辐射率100 kW立式旋风炉精确度高、设备便携、运行稳定、适用性好
液态排渣旋风燃烧试验炉发射光谱测量系统2022年光纤、准直透镜、平板电脑等碱金属质量浓度、火焰温度液态排渣旋风试验炉实时监测数据更新间隔短、灵敏度高、功耗低
炉内燃烧温度\气相钠质量浓度在线监测系统2022年光谱探头、工控机、通信线缆、在线监测软件等气相钠质量浓度、火焰温度660 MW准东煤发电机组锅炉稳定性好、光谱采样时间短、灵敏度高、响应时间快
耦合炉内气相碱金属检测的锅炉结渣预报系统2023年光学探头、信号线缆、控制盒、计算机系统、专用监测软件等碱金属质量浓度、火焰温度、结渣程度350 MW机组燃煤锅炉稳定好、光谱采样时间短、可在线对结渣趋势进行判断、系统操作简便
), ArticleFig(id=1211002432037982837, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=EN, label=Tab.2, caption=

Comparison of various wall temperature on-line measurement systems

, figureFileSmall=null, figureFileBig=null, tableContent=
系统名称开发时间系统组成监测变量应用场景优点
多喷嘴对置式气化炉光谱图像检测系统2018年高温内窥镜、带通滤色片、CCD相机、计算机、光纤、光谱仪、热电偶等火焰温度、碱金属原子光谱特征对置式多燃烧器气化炉系统简易,成本低,稳定性好,测量精度较高
Mckenna平面火焰燃烧器光谱图像检测系统2018年光谱仪、ICCD相机、带通滤波器、连续波激光器、光电二极管等光谱辐射强度图像、生物质燃烧颗粒中碱金属光谱特征Mckenna平面火焰燃烧器可定性分析单个粉状固体燃料颗粒的燃烧过程
一维炉内试件表面温度测量实验系统2011年热电偶、红外温度计、专用测量软件等壁面温度一维炉采用多分辨率小波消噪和辐射传递理论温度修正相结合的处理方法,有效提高系统辐射测温精度
锅炉受热面壁温分布直接监测2022年工业CCD相机、红外成像仪等壁面温度亚临界330 MW机组锅炉可对锅炉受热面壁温可视化监测,壁温测量结果能够准确反映机组工况变化
壁面温度在线监测系统2019年工业CCD相机、红外镜头、冷却装置、压力温度报警装置、计算机等壁面温度1 000 MW燃煤发电机组锅炉系统可在高温环境下维持正常工作温度,避免烟气颗粒物在镜头表面沉积,测量可靠稳定
), ArticleFig(id=1211002432138646135, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1211002411502670662, language=CN, label=表2, caption=

各壁面温度在线监测系统比较

, figureFileSmall=null, figureFileBig=null, tableContent=
系统名称开发时间系统组成监测变量应用场景优点
多喷嘴对置式气化炉光谱图像检测系统2018年高温内窥镜、带通滤色片、CCD相机、计算机、光纤、光谱仪、热电偶等火焰温度、碱金属原子光谱特征对置式多燃烧器气化炉系统简易,成本低,稳定性好,测量精度较高
Mckenna平面火焰燃烧器光谱图像检测系统2018年光谱仪、ICCD相机、带通滤波器、连续波激光器、光电二极管等光谱辐射强度图像、生物质燃烧颗粒中碱金属光谱特征Mckenna平面火焰燃烧器可定性分析单个粉状固体燃料颗粒的燃烧过程
一维炉内试件表面温度测量实验系统2011年热电偶、红外温度计、专用测量软件等壁面温度一维炉采用多分辨率小波消噪和辐射传递理论温度修正相结合的处理方法,有效提高系统辐射测温精度
锅炉受热面壁温分布直接监测2022年工业CCD相机、红外成像仪等壁面温度亚临界330 MW机组锅炉可对锅炉受热面壁温可视化监测,壁温测量结果能够准确反映机组工况变化
壁面温度在线监测系统2019年工业CCD相机、红外镜头、冷却装置、压力温度报警装置、计算机等壁面温度1 000 MW燃煤发电机组锅炉系统可在高温环境下维持正常工作温度,避免烟气颗粒物在镜头表面沉积,测量可靠稳定
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基于自发辐射分析的高碱煤燃烧炉内在线监测技术研究进展
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陈装 1 , 黄华汉 1 , 傅勇强 1 , 李华鸿 1 , 方顺利 2 , 王志超 2 , 陈端 3 , 张冲 3 , 王浩帆 3 , 马帅 3 , 姚斌 3 , 娄春 3
热力发电 | 高比例燃烧高碱煤技术专题 2024,53(1): 24-37
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热力发电 | 高比例燃烧高碱煤技术专题 2024, 53(1): 24-37
基于自发辐射分析的高碱煤燃烧炉内在线监测技术研究进展
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陈装1 , 黄华汉1, 傅勇强1, 李华鸿1, 方顺利2 , 王志超2, 陈端3, 张冲3, 王浩帆3, 马帅3, 姚斌3, 娄春3
作者信息
  • 1.湛江中粤能源有限公司,广东 湛江 524000
  • 2.西安热工研究院有限公司,陕西 西安 710054
  • 3.华中科技大学煤燃烧国家重点实验室,湖北 武汉 430074
  • 陈装(1965),男,高级工程师,主要从事火力发电厂生产管理工作,

通讯作者:

方顺利(1985),男,博士,高级工程师,主要研究方向为火电厂燃煤掺配烧系统开发、锅炉燃烧参数监测技术的开发应用,
Research progress on online in-furnace monitoring techniques during high-alkali coal combustion based on spontaneous emission radiation analysis
Zhuang CHEN1 , Huahan HUANG1, Yongqiang FU1, Huahong LI1, Shunli FANG2 , Zhichao WANG2, Duan CHEN3, Chong ZHANG3, Haofan WANG3, Shuai MA3, Bin YAO3, Chun LOU3
Affiliations
  • 1.Zhanjiang Zhongyue Energy Co., Ltd., Zhanjiang 524000, China
  • 2.Xi’an Thermal Power Research Institute Co., Ltd., Xi’an 710054, China
  • 3.State Key Laboratory of Coal Combustion, Huazhong University of Science and Technology, Wuhan 430074, China
出版时间: 2024-01-25 doi: 10.19666/j.rlfd.202310166
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准东煤等高碱煤在新疆地区储量巨大,但其富含的碱金属元素极易导致炉膛受热面沾污、结渣等问题,会影响锅炉运行的安全性,研发高碱煤高效清洁燃烧发电技术对实现“双碳”目标有重要意义。总结了基于自发辐射分析的高碱煤燃烧炉内在线监测技术的研究进展,重点介绍了发射光谱技术、自发辐射图像处理及成像技术在高碱煤燃烧监测领域的研究现状及应用情况,进而对其发展趋势和动态进行探讨。发射光谱技术通过对火焰发出的不同波长光谱辐射信号进行处理获取温度与组分,近期,已广泛用于测量工业炉膛燃烧火焰温度和气相碱金属质量浓度,并基于此对炉内结渣趋势进行定性判断。自发辐射图像处理及成像技术具备信号空间分布的解析能力,利用CCD、CMOS等面阵传感器获取炉内自发辐射图像,基于图像处理与热辐射成像原理,结合辐射反问题求解方法,可以获得燃烧场在三维空间的温度分布以及二维壁温分布,使结渣的三维可视化监测成为可能。未来需基于发射光谱技术、自发辐射图像处理及成像技术对二维或者三维的受热面结渣沾污进行监测,结合炉内燃烧温度与气相碱金属质量浓度等参数分布,建立高碱煤燃烧受热面结渣沾污的定量判断指标,最终达到对受热面结渣沾污在线预测的目标。

高碱燃料  /  自发辐射分析  /  火焰发射光谱  /  图像处理  /  热辐射成像

High-alkali coal such as Zhundong coal has huge reserves in Xinjiang, in which rich alkali metal elements can easily lead to fouling and slagging problem on heating surface of the furnace, thus to decrease the safety of boiler. It is of great significance to develop efficient and clean combustion power generation technology for high-alkali coal to achieve the “double-carbon” goal. The research progress of the online monitoring technology in high-alkali coal combustion furnace based on spontaneous emission radiation analysis is summarized. The development trend and dynamics are discussed focusing on the research status and application of emission spectrum technology and spontaneous emission radiation imaging and image processing technology in high-alkali coal combustion monitoring. Emission spectroscopy can obtain the temperature and component concentration by processing the spectral radiation signal emitted by the flame at different wavelengths. Recently, it has been widely used to measure the combustion temperature and the gaseous alkali metal concentration in the industrial furnace and judge the slagging trend in the furnace qualitatively. Different from emission spectroscopy technology, spontaneous emission radiation imaging and image processing technology has the ability to analyze the spatial distribution of signals. The technology obtains the spontaneous radiation image in the furnace via CCD, CMOS and other surface array sensors. Based on image processing technology and thermal radiation imaging theory, the temperature distribution of the combustion field in three-dimensional space can be obtained combining with solving radiation inverse problem, which makes it possible to monitor the three-dimensional visual of slagging formation. In the future, monitoring of the fouling and slagging on the heating surface in two or three dimensions should be carried out based on emission spectroscopy technology, spontaneous emission radiation imaging and image processing technology. Combined with the distribution of parameters such as combustion temperature and gaseous alkali metal concentration in the furnace, a quantitative judgmental index of fouling and slagging on the heating surface of high-alkali coal combustion should be established to achieve the goal of online prediction of fouling and slagging on the heating surface.

high-alkali fuel  /  analysis of spontaneous emission radiation  /  flame emission spectroscopy  /  image processing  /  thermal radiation imaging
陈装, 黄华汉, 傅勇强, 李华鸿, 方顺利, 王志超, 陈端, 张冲, 王浩帆, 马帅, 姚斌, 娄春. 基于自发辐射分析的高碱煤燃烧炉内在线监测技术研究进展. 热力发电, 2024 , 53 (1) : 24 -37 . DOI: 10.19666/j.rlfd.202310166
Zhuang CHEN, Huahan HUANG, Yongqiang FU, Huahong LI, Shunli FANG, Zhichao WANG, Duan CHEN, Chong ZHANG, Haofan WANG, Shuai MA, Bin YAO, Chun LOU. Research progress on online in-furnace monitoring techniques during high-alkali coal combustion based on spontaneous emission radiation analysis[J]. Thermal Power Generation, 2024 , 53 (1) : 24 -37 . DOI: 10.19666/j.rlfd.202310166
高碱煤中钠(Na)、钾(K)等碱金属元素含量偏高,在燃烧过程极易挥发成气态,所形成的气相碱金属化合物遇到温度稍低的受热面管壁即凝结在管壁上形成白色薄灰层,进而黏结飞灰并继续形成黏结物使灰层增厚,导致锅炉炉膛严重结渣,受热面严重沾污,管壁超温等问题频发[1-2]。我国高碱煤主要储藏于新疆的准东、哈密等地区,有上万亿吨,煤电是其主要利用途径。研发针对高碱煤的高效清洁燃烧发电技术,可为“双碳”目标的实现及新型电力系统的构建提供重要科技支撑[3-5]
高碱煤燃烧产生的气相钠、钾以及局部火焰温度、气氛是造成高温受热面结渣及超温的关键因素。针对这些因素的在线监测技术,目前研究可分为基于探针取样的接触式取样分析技术,基于激光的主动式检测技术,以及基于燃烧自发辐射的被动式检测技术[6-12]。例如:基于探针取样的接触式取样分析技术方面,浙江大学根据表面电离法设计了一种探测器探针,对准东煤燃烧时所产生烟气中的气相碱金属进行在线监测,并得到随温度变化时气相钠释放率,证明了将该技术应用于高碱煤燃烧炉中气相碱金属含量在线监测的可行性。基于激光的主动式检测技术方面[6],澳大利亚阿德莱德大学、瑞典隆德大学、清华大学、浙江大学等[6]采用激光诱导荧光光谱(PLIF)、激光诱导击穿光谱(LIBS)、差分吸收光谱(DAOS)等技术得到了煤颗粒在实验室燃烧器上燃烧释放的气相钠质量浓度;采用基于声波的声学层析技术、基于激光的可调二极管吸收光谱技术(TDLAS)测量炉内横截面的二维温度分布、CO气体组分[7]。但煤粉炉燃烧空间尺寸较大,燃烧火焰中颗粒和气体介质自身释放出强烈的光热辐射,且测量环境恶劣,导致激光信号易被干扰、阻挡,光路复杂难以布置。被动式诊断技术不采用任何外加光源,通过采集、分析燃烧过程中产生的光、热等自发辐射信号即可开展检测,其具有对环境要求较低、系统紧凑且易于实施、信息转换环节少且相对易于标定等优点[8]。在基于燃烧自发辐射的被动式检测技术方面,英国利兹大学、华中科技大学、西安热工研究院有限公司等[9]采用基于燃烧自发辐射分析的发射光谱法(FES),实时测量炉内局部区域的气相钠、钾质量浓度及火焰温度,并开展了实验室燃烧器、中试燃烧装置、大型电站锅炉内燃烧火焰中气相碱金属的在线监测。华中科技大学基于燃烧自发辐射分析提出了炉内热辐射成像技术,实现了大型炉膛内燃烧三维温度场可视化测量,并应用于火电、冶金、石化行业[10-12]
随着全烧高碱煤技术研究的推进,基于燃烧自发辐射分析的在线监测技术仍面临诸多的问题和挑战。基于燃烧自发辐射的发射光谱技术仍存在未考虑在监测中光学厚度对标定结果的影响;标定方法中存在检测范围较低,无法对被测火焰沿空间分布的燃烧信息实施检测等问题;自发辐射图像处理技术光谱分辨率较低,无法充分利用光谱检测信息。目前,迫切需要分析高碱煤燃烧锅炉内碱金属质量浓度、火焰温度、局部气氛造成高温受热面结渣及超温的影响规律,并开发煤粉炉受热面结渣及超温的安全管控系统,这对高碱煤燃烧炉内碱金属迁移转化特性监测、受热面积灰结渣监测、炉内燃烧三维可视化监测提出了更高的要求。对此,本文综述基于燃烧自发辐射分析的发射光谱技术、自发辐射图像处理及成像技术用于高碱燃料燃烧监测的研究及应用现状,进而对其发展趋势和动态进行探讨。
发射光谱技术是对不同波长下火焰发出的光谱辐射信号进行处理,获取温度、组分等信息并用于燃烧分析与诊断,已广泛用于测量燃烧火焰温度和化学发光信号。针对煤粉炉内高碱煤碱金属迁移转化特性监测,发射光谱技术主要用于同时检测温度及气相钠、钾质量浓度等。
根据原子光谱理论,高温下碱金属元素在特定波长下发出的谱线强度与气相碱金属质量浓度及温度有关[13]。英国利兹大学Jones等人[14]基于该原理对柳木等生物质颗粒燃烧火焰中钾元素发射光谱进行了定量观测,分析了挥发分燃烧、焦炭燃烧以及成灰3个过程中气相碱金属的释放特性;随后,Mason等人[15-16]基于发射光谱法测得的生物质燃烧过程中气相钾释放曲线建立了钾元素释放模型,可用于预测气相钾的释放。桂欣扬[17]、韩雨佳等[18]测量了实验室煤粉射流火焰气相钠的光谱强度,用于表征钠的相对释放量,进而分析了风温、给粉、煤种对气相钠释放的影响。郭庆华等[19]开展了多喷嘴对置式气化炉内火焰发射光谱研究,分析了水煤浆、柴油火焰K和Na的辐射特性及其受原料碱金属含量、火焰温度的影响程度。
近年来,娄春等[20-22]提出了从火焰自发射光谱中同时获得火焰温度和气相钠、钾等碱金属质量浓度的测量方法。首先,从光谱仪获取的高碱燃料燃烧火焰光谱强度I分布中,精确分离出火焰热辐射自发射的连续光谱IC及碱金属受激发射的特征谱线(INaIK等)[23],即I=IC+INa+IK;再用多波长法从火焰热辐射连续光谱中计算火焰温度[24],并依据耦合温度、辐射强度的气相碱金属质量浓度标定曲线,从钠、钾特征谱线强度中获得相应的气相碱金属质量浓度[25]图1为高碱燃料燃烧火焰发射光谱检测系统[10]。该方法已用于实验室燃烧器进行准东煤、生物质、城市固体废弃物颗粒燃烧过程中火焰温度和气相碱金属质量浓度的在线测量及释放特性研究[26-31]
图2给出了基于燃烧自发辐射分析的发射光谱法(FES)和光学诊断技术(LIBS)2种方法测得的五彩湾准东煤颗粒在平面火焰上燃烧时气相碱金属质量浓度随燃烧时间的变化曲线[22]。FES方法通入燃烧器的燃料气体甲烷和空气的流量分别为1.5、35.0 L/min,以提供稳定的燃烧环境,以便携式光谱系统为核心来检测准东煤燃烧时气相Na的释放。LIBS方法通入燃烧器的燃料气体甲烷和空气的流量分别为0.59、7.06 L/min,以LIBS系统为核心来检测气相Na质量浓度,测量结果a和b数据分别来自文献[32]和文献[33]。由于2次测量不是同时进行,且燃用的准东煤煤质成分以及实验环境略有不同,导致2个气相Na质量浓度测量曲线会有所偏差。由图2可见,2种方法均能识别挥发分燃烧、焦炭燃烧、成灰3个阶段的钠释放。在挥发分和焦炭阶段,气相钠的释放受温度和热辐射的影响较大;成灰阶段,灰分中的硅元素可抑制气相钠的释放。LIBS与FES方法相比:基于激光的光学诊断技术更加复杂,在工业应用中测量环境恶劣,激光信号易被干扰、阻挡,光路复杂难以布置;而FES方法对环境要求不高,系统紧凑且易于实施,信息转换环节少且相对易于标定,这为中试及工业燃烧装置中开展气相钠在线监测奠定了基础。
发射光谱技术很早就用于中试装置及工业炉膛内温度的测量。针对炉内碱金属的检测,加拿大自然资源部能源技术中心研究人员在1台0.3 MW中试煤气化炉上安装了光学探头,其检测系统结构如图3所示[33]。将炉内光信号引入1台波长200~800 nm的可见光光谱仪,采用多波长法计算炉内温度,同时还获得了钠光谱强度随氧量、煤量和蒸汽流量的变化。试验结果证明[34],发射光谱技术用于煤气化性能测试的可行性,煤气化炉光谱检测系统由光学探头将光信号传输到光谱仪上并由光谱仪进行采样,响应时间为1~2 s,采用多波长法对650~710 nm波长范围内3个测点的温度进行计算,得出温度与相应测点热电偶测得温度偏差分别为2.7%、2.1%、2.7%,检测精度较高。
近年来,发射光谱技术被用于在线测量液态排渣旋风炉内气相碱金属质量浓度[35-39],以检验旋风炉渣膜对高碱煤燃烧产生气相碱金属的吸附情况,从而降低进入炉膛内的气相碱金属质量浓度,以减少锅炉高温受热面发生严重沾污的可能性。张向宇等[35-36]提出了一种基于主成分分析和辐射率多项式拟合的光谱分析方法(图4),从1台100 kW立式旋风炉获得的光谱数据中同时反演火焰温度、辐射率和气相钠质量浓度,发现在旋风炉尾部碱金属由气相向固相迁移,在旋风筒中3个不同测点位置处通过发射光谱技术测得的温度与热电偶测得温度误差分别为2.77%、1.36%、1.95%,检测精度较高。
华中科技大学开发了一套便携式发射光谱检测系统,由光纤光谱仪、平板电脑及专用处理软件组成,检测系统响应时间为1~2 s,先后用于20 MW液态排渣旋风燃烧试验炉及300 MW燃煤发电机组液态排渣炉内温度及气相碱金属质量浓度的同时检测[37-38]。液态排渣旋风燃烧试验炉发射光谱测量系统结构如图5所示。对于编号为FK和HSQ的2种准东煤分别在1 100、1 300 K和1 200、1 400 K工况温度下进行检测,检测结果如图6所示[37]
图6可见,HSQ煤燃烧过程中释放的气相钠质量浓度高于FK煤。一是因为HSQ煤中钠质量浓度最高,燃烧过程中释放量较大;二是FK煤中硅和铝元素质量浓度较高,在高温条件下气相水溶性钠会直接与硅、铝反应生成不可溶的硅铝酸盐,而不溶性硅铝酸盐主要留在液渣中,释放到烟气中的气相碱金属钠相对较少。同时,FK煤和HSQ煤燃烧火焰中气相钠质量浓度与旋风筒出口温度的变化呈正相关。
用同样的便携式设备测量了300 MW燃煤发电机组塔式液态排渣炉双U型燃烧室内多个位置的局部温度及气相钠质量浓度[38],测点位置如图7所示。测量结果表明:炉内气相钠质量浓度分布不均匀,结合气相钠质量浓度和灰渣样中钠质量浓度建立了碱金属迁移转化的闭环分析路径,在旋风燃烧方式下,随着火焰气相钠质量浓度的增加,飞灰和液渣中钠质量浓度均增大,但钠元素更多的是向飞灰中迁移[37]
蒲旸等[38-39]研发了1套炉内燃烧温度\气相钠质量浓度在线监测系统并应用于准东煤发电机组锅炉,连续在线测量炉内局部温度及气相钠质量浓度。炉内燃烧温度\气相钠质量浓度在线监测系统如图8所示[39]
在线监测系统包括安装在锅炉折焰角下方的光谱探头、放置在集控室内的工控机及自行开发的在线监测软件。炉内燃烧温度\气相钠质量浓度在线监测系统的相应时间小于3 s,光谱探头的检测范围为300~1 000 nm,光谱分辨率为0.5~0.7 nm,光谱采样时间小于1 s,工作温度为–10~50 ℃。该系统通过黑体炉对燃烧火焰温度精度进行检定,测得温度与实验给定温度相对误差不超过1%,测量效果较好;再将雾化标准钠溶液送入火焰中,由在线监测系统对气相Na质量浓度进行检测以验证系统气相Na质量浓度检测精度,结果表明测量误差小于1.5%,测量精度较高。
图9给出了在线监测系统获得的660 MW准东煤发电机组锅炉内24 h连续测量结果及与机组负荷、给粉量、总风量的对比[39]。由图9可见,整体上气相钠质量浓度和温度与机组运行参数呈明显的正相关性。随着入炉煤量的增加,炉内钠总质量增加;温度的提高促进气相钠的释放,更多钠以气相形式存在。在线监测结果有助于控制屏底烟温以及判断进入上部炉膛区域内气相钠量,以缓解上部炉膛的过热器、再热器管壁的沾污结渣。
有研究者基于炉内温度\气相钠质量浓度监测结果,结合灰成分分析法[40-41],通过结渣实验建立归一化气相钠质量浓度和煤灰中Na2O含量的定量关系,进而考虑气相碱金属释放、受热面结渣是随时间的动态过程,提出了一种结渣在线指数,用于对炉内结渣趋势进行判断[40]。在DCS中开发了锅炉结渣预报系统画面,通过计算结渣在线指数,得到不同区域受热面结渣趋势的判断,指导燃煤发电机组运行人员采取燃烧调整、吹灰等结渣防控操作。耦合炉内气相碱金属检测锅炉结渣预报系统界面如图10所示[40]
各项技术比较见表1。基于燃烧自发辐射的发射光谱技术设备简易,易于携带,价格低廉,对环境要求较低,可同时检测火焰中物质燃烧的状态和信息,如火焰温度、灰度、辐射能等变化规律,适合大型工业现场应用。与自发辐射成像技术、自发辐射图像处理技术2种技术相比,基于燃烧自发辐射的发射光谱技术设备不用伸入炉膛内部即可测量,无需考虑耐高温、防沾污结焦等因素,维护成本较低,同时,还可以对火焰中释放的气相碱金属质量浓度进行监测,如Na、K等。但是基于燃烧自发辐射的发射光谱技术是通过光谱仪来对火焰上某一点或某一区域沿视线方向发出的光谱信息进行检测,无法对被测火焰沿空间分布的燃烧信息实施检测,空间维数的不足制约了其对燃烧空间多维温度分布的检测。在今后研究中,可以将火焰自辐射光谱检测方法与图像处理等技术相结合,用于火焰温度的检测及碱金属质量浓度检测。同时,发射光谱技术未考虑在监测中光学厚度对标定结果的影响,标定方法中存在检测范围较低等问题。如果能得到碱金属谱线辐射强度和温度以及光学厚度之间的关系,可以提高检测结果的精度。
发射光谱技术接受信号来自炉内某区域沿视线方向累积的自发辐射信息,不具备信号在空间分布的解析能力。随着半导体技术的发展,CCD、CMOS等面阵传感器被用于获取炉内自发辐射图像,对图像信号进行处理,获得的检测结果具有二维空间的分辨率。根据热辐射成像原理,燃烧火焰图像可表征三维空间中局部燃烧介质和壁面发出的热辐射经过介质吸收、散射及壁面吸收、反射后到达面阵传感器上形成的二维分布,结合辐射反问题求解方法,还可获得燃烧场在三维空间的温度分布。针对高碱煤炉内气相碱金属、受热面积灰结渣监测及燃烧三维可视化监测,自发辐射图像处理及成像技术也得到了较多应用。
煤粉炉是由炉壁表面及其包围的颗粒、气体介质构成的三维空间系统。炉内发出的自发辐射覆盖了紫外-可见光-红外的宽波段范围。可见光和近红外的波段范围包含炉内颗粒(如碳烟和焦炭)以及炉膛壁面发出的类似于黑体辐射的连续光谱;红外波段范围包含炉内气体(如二氧化碳和水蒸气等发出的带状光谱);紫外和可见光波段范围包含炉内燃烧过程中自由基(OH、CH和C2等)化学发光发出的线状光谱;炉内碱金属元素(钠和钾等)受高温激发发出的线状光谱,位于可见光波段。结合具有不同光谱响应波段的面阵传感器,可以获得炉内自发辐射在某个宽波段内的图像,也可以在面阵传感器前加单色滤色片来获得单个波长或者窄波段内的光谱辐射图像。
1)光谱图像检测
华东理工大学于广锁团队[42-45]针对煤气化、燃烧炉内碱金属光谱辐射特性开展了检测研究。多喷嘴对置式气化炉光谱图像检测系统如图11所示[42]
该检测系统在1台多喷嘴对置式气化炉实验炉顶部安装了光学内窥镜,采用高分辨率CCD相机结合带通滤色片(580、590、600、760、770、780 nm)分别获取炉内Na、K的发射光谱强度图像(主要集中于撞击区域中心)。结果显示:水煤浆火焰的碱金属光谱强度及分布面积明显高于柴油火焰,其主要取决于原料碱金属的含量以及火焰的温度[39]。对于煤粉颗粒在可视化滴管炉内燃烧过程,采用波长400~1 000 nm的线阵EM-CCD高光谱相机同时获取煤颗粒下落燃烧时沿炉膛轴线上125个波长的光谱图像,光谱分辨率约为1.021 nm,相机捕捉煤粉颗粒燃烧光谱信号的测量时间为50 ms,其曝光时间设置为10 ms,可以获得5个不同燃烧时刻下位于可见光波段590、770 nm处Na和K特征谱线[40]。检测结果表明:1)Na和K的特征谱线强度随含氧量的增加而增加,O2/N2气氛下的谱线强度高于O2/CO2气氛,且与火焰温度呈正相关[41];2)单颗粒煤粉燃烧中碱金属在火焰外层释放强度较大[42]。此外,瑞典隆德大学翁武斌等[43-48]也是采用加滤色片的ICCD增强型电荷耦合器件相机获取了生物质颗粒在Mckenna平面火焰燃烧器上燃烧的光谱辐射强度图像。Mckenna平面火焰燃烧器由1个不锈钢圆筒组成,该圆筒包裹着直径为60 mm的水冷青铜多孔烧结基体。通过2个质量流量控制器向燃烧器中心孔处输入燃料气体,冷却水通过铜管输送至燃烧器,燃烧器上方内径为70 mm、高度500 mm、厚度2 mm的优质熔融石英,限制气体流动,避免夹带环境空气,同时提供光学通道。结果表明,Na、K信号在燃烧过程中持续存在,且在挥发分燃烧阶段结束前与CH、C2的信号变化相同。
2)监测炉内受热面壁温
自发辐射图像处理技术还被用于直接监测炉内受热面壁温,从而对炉内积灰结渣情况进行判断。基于红外图像处理及标定的测温仪器常被用于固体表面温度测量[8],但高温下炉内燃烧火焰中的颗粒及气体介质也会在红外波段发出强烈热辐射,叠加在炉膛受热面发出的红外辐射上对壁温检测结果带来较大影响,甚至会完全遮挡来自壁面的红外热辐射信号。对此,美国FLIR公司采用锑化铟(InSb)面阵传感器及滤光片仅获取3.80~4.05 μm波长范围的红外热图像,试图滤掉火焰热辐射实现“穿透火焰”监测炉膛受热面温度,从而判断受热面氧化、结渣情况。美国Advanced Energy公司则是采用3.9 μm滤光技术配合中波红外图像探测器,试图“透过火焰”观察锅炉、熔炉、窑炉或焚化炉内的情况。但从实际应用效果来看,这种方式只适合于监测燃气锅炉或者燃煤锅炉折焰角以上过热器、再热器区域的管壁温度,330 MW机组燃煤锅炉过热器红外热图像如图12所示[49];而对于燃煤锅炉折焰角以下燃烧火焰区域的水冷壁受热面则难以清晰观测,所得到的红外热图像中受燃烧火焰辐射的影响较大,该锅炉水冷壁红外热图像如图13所示[49]。其原因是煤粉炉内燃烧生成的焦炭、碳烟、飞灰等颗粒物在高温下发出的热辐射在红外波段仍然有很强的信号,采用滤光片虽然能过滤掉炉内气体的红外热辐射,但不能完全消除颗粒的热辐射影响。
针对如何消除烟气、颗粒对炉内壁温测量的影响,国内学者做了深入的理论分析及试验研究[48-53]。清华大学段源远等[48]通过对一维炉实验台内不锈钢平板表面温度辐射法进行测量探究,发现红外温度计上的显示温度与管壁实际温度存在差异,可以采用小波消噪和温度修正相结合的数据处理方法来提高辐射测温精度。西安热工研究院有限公司张向宇等[49]则提出同时获取炉内燃烧的可见光图像及红外热图像,通过辐射成像计算方法求解探测器接收的火焰辐射和壁面辐射份额,再从红外热辐射图像中扣除火焰辐射,进而测量出炉膛壁面温度分布。东南大学许传龙团队[50-53]采用源项多流法对烟气遮蔽下壁面的红外测温进行了模拟,计算出不同探测角度下进入探测器的能量以及测量的温度,研究了烟气厚度、温度等因素对红外测温结果的影响规律,提出了利用反演方法修正红外测温的思路,并基于中心波长为10 μm的红外相机建立了一套壁面温度在线监测系统。壁面温度在线监测系统结构如图14所示[53]
自发辐射图像处理技术基于三维燃烧火焰发出的光投影至面阵图像传感器上形成图像,有助于得到火焰温度等参数的二维分布。自发辐射图像处理技术可以获得炉内自发辐射在某个宽波段内的图像,也可以获得单个波长或者窄波段内的光谱辐射图像,并能直接检测炉膛受热面温度进而对受热面的沾污结渣情况进行监测,且设备操作简易,运行状态稳定,易于实施。
但是自发辐射图像处理技术在工业应用中需要将设备伸入到炉膛中,要求设备具有较高的耐高温、防沾污结焦等性能,且需要用面阵传感器,与基于燃烧自发辐射的发射光谱技术相比,设备昂贵,成本较高。同时,自发辐射图像处理技术虽然能提供具有空间分布的图像检测信息,但光谱分辨率较低,未来可将能够提供包含空间和光谱信息的多/高光谱成像设备应用于技术中,图像和光谱相结合,有助于实现同时测量火焰中温度与多种组分体积分数分布。表2为各壁面温度在线监测系统比较。
煤粉炉内燃烧过程存在明显的三维空间分布特性,受热面结渣、超温是炉膛三维空间中二维炉壁表面发生的现象,与炉内三维分布特性密切相关。因此,具备炉内三维空间解析能力的实时测量技术,有助于对锅炉受热面结渣及超温进行准确预测及全面管控。现有技术中,声学层析技术、可调二极管激光吸收光谱技术(TDLAS)以及热辐射成像技术可实现大型炉膛内三维温度场可视化监测[11]。其中,声学层析可实现燃煤锅炉内横截面的二维温度分布测量。TDLAS可用于大型炉膛出口横截面的二维温度分布及CO等气体质量浓度测量。周怀春等[12]提出的热辐射成像技术通过解析三维空间中耦合燃烧介质发射、吸收、散射和炉膛壁面发射、吸收、反射的热辐射成像光束传输过程(图15[10-12],实现了大型炉膛内燃烧三维温度场可视化测量,并应用于火电、冶金、石化行业[12]
与声学层析技术、可调二极管激光吸收光谱技术以及热辐射成像技术3种技术相比,基于燃烧自发辐射分析的热辐射成像技术具有成像过程响应快、三维空间中测量结果的时空分辨率高、系统简易且便于实施等特点,其在高碱煤燃烧炉内三维温度场在线监测中具有明显优势。火焰中心位置在部分程度上反映炉内燃烧工况是否正常,基于炉内燃烧温度场在三维空间分布,通过重心计算法可同时确定火焰中心在炉膛水平及垂直方向的位置。实际应用火焰中心位置监测的结果表明:四角切圆燃烧锅炉内火焰水平中心偏离炉膛横截面几何中心时,会造成火焰刷墙、燃烧不稳定,严重时会引发炉膛灭火事故[54];W型火焰锅炉内的火焰垂直中心上升时,会导致炉膛上部温度过高,缩短煤粉充分燃尽时间,也会让飞灰中的碳含量及减温水量增加[55]
炉内热辐射成像过程中已把炉膛三维空间及二维壁面分别离散为mn个单元。考虑单元质量流动带来热焓交换的炉内辐射换热,根据空间及壁面单元的能量平衡(式(1)、式(2))可建立炉内三维温度分布与炉膛容积热负荷分布、壁面辐射热流分布的定量关系式[56]
E1+hout=E2+hin+Qs
E3+Qnet=E4
式中:E1为空间单元发出的辐射能量;hout为因质量流动离开空间单元的焓;E2为空间单元吸收的所有单元发出的辐射能量;hin为因质量流动进入空间单元的焓;Qs为空间单元燃烧反应释放的热量(即局部热负荷);E3为壁面单元发出的辐射能量;Qnet为进入壁面单元的辐射净热量(即壁面辐射热流);E4为壁面单元吸收的所有单元发出的辐射能量。
在获得炉内三维温度场结果后,可进一步实现炉膛水冷壁辐射热流分布、炉内燃烧放热量分布及炉内容积热负荷分布的在线监测。200 MW机组燃煤锅炉壁面热流分布在线监测结果如图16所示[8]
利用炉膛水冷壁二维表面辐射热流分布为边界条件,可以从热力过程机理出发建立锅炉蒸发系统分布参数动态模型。该模型能够反映在蒸发受热面上壁面汽水侧的管壁温度、质量流速等热力参数动态分布,以及汽包压力、水位等动态变化[57]图17给出了1台300 MW燃煤机组锅炉前墙水冷壁在2个负荷工况下的汽水侧管壁温度分布[58]。与热流分布对比可以看出:在相同工况下壁温分布与热流分布的相似度很高,壁面上高热流区域也会有高壁面温度。由此可知,在通常工况下炉内烟气状况是影响壁面温度分布的根本因素,而锅炉内部过程对壁面温度分布基本没有影响[58]。运行人员可根据各个壁面辐射热流、汽水侧壁温分布变化,判断水冷壁超温、结渣甚至爆管的可能性,进而采取相应措施。
自发辐射成像技术与基于燃烧自发辐射的发射光谱技术,自发辐射图像处理技术2种技术相比,可对炉内三维温度场进行监测,并且成像过程响应快,三维空间中测量结果的时空分辨率高,系统简易且便于实施。但是自发辐射成像技术也需将设备伸入到炉膛中,对设备耐高温、预防沾污结焦等要求较高,且需用面阵传感器,成本较高。
自发辐射成像技术可以达到千万级像素,可是如何有效充分利用千万级像素光谱检测信息,依然有待研究。同时,燃烧介质非均匀分布也会对温度重建产生影响。未来可以将以人工神经网络开展机器深度学习的方法与自发辐射成像技术高度结合,进而求解具有不适定性的热辐射反问题,从而提高检测的分辨率及精度[59]
1)发射光谱技术可获取温度、组分等参数用于燃烧诊断,已建立耦合温度、辐射强度的气相碱金属质量浓度标定曲线,并被用于实验室燃烧器上开展准东煤、生物质、城市固体废弃物颗粒燃烧过程中火焰温度和气相碱金属质量浓度的在线测量及释放特性研究。另外,发射光谱技术已应用于0.3 MW煤气化炉、20.0 MW液态排渣旋风炉等中试实验炉内,便携式与在线式的炉内燃烧温度\气相钠质量浓度监测系统已被应用于300、660 MW机组燃用准东煤锅炉。
2)自发辐射图像处理及成像技术基于CCD、CMOS等面阵传感器获取炉内自发辐射图像,具备信号在空间分布的解析能力。不同响应波段或加单色滤色片的面阵传感器,可获得单个波长或窄波段内的光谱辐射图像。自发辐射图像处理技术被使用于监测Mckenna平面火焰燃烧器、多喷嘴对置式气化炉、实验炉内的光谱辐射强度图像,同时被应用于直接监测炉内受热面壁温以判断炉内积灰结渣情况,其目的在于消除烟气、颗粒对炉内壁温测量的影响。辐射成像技术将三维炉膛与二维壁面集散为多个单元,根据能量平衡建立炉内三维温度分布与炉膛容积热负荷分布、壁面辐射热流分布的定量关系,目前被应用于300 MW机组。
3)基于发射光谱技术、自发辐射图像处理及成像技术对二维或者三维的受热面结渣沾污进行监测,结合炉内的燃烧温度与气相碱金属质量浓度等参数分布,建立高碱煤燃烧受热面结渣沾污的定量判断指标,最终实现对受热面结渣沾污在线预测,为“双碳”目标实现做出贡献。另外,基于燃烧自发辐射的被动式诊断技术被测参数耦合因素较多,对于燃烧过程中含碱金属元素中间组分的测量手段较少,信号后续分析复杂。未来需深入研究耦合因素解耦,尽可能获得更多的燃烧参数和中间组分,并进一步发展获取光谱、图像成像器件及软件,提升光谱、图像信号处理算法,加强对射光谱技术、自发辐射图像处理及成像技术的组合应用,提升在线监测技术在工业应用中的普适性和可靠性。
  • 中国华能集团有限公司总部科技项目(HNKJ22-H34)
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2024年第53卷第1期
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doi: 10.19666/j.rlfd.202310166
  • 接收时间:2023-10-10
  • 首发时间:2025-12-25
  • 出版时间:2024-01-25
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  • 收稿日期:2023-10-10
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Science and Technology Project of China Huaneng Group Co., Ltd.(HNKJ22-H34)
中国华能集团有限公司总部科技项目(HNKJ22-H34)
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    1.湛江中粤能源有限公司,广东 湛江 524000
    2.西安热工研究院有限公司,陕西 西安 710054
    3.华中科技大学煤燃烧国家重点实验室,湖北 武汉 430074

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方顺利(1985),男,博士,高级工程师,主要研究方向为火电厂燃煤掺配烧系统开发、锅炉燃烧参数监测技术的开发应用,
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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