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The alkali metals released during combustion of high alkali coals can easily lead to fouling and slagging of the heated surfaces of the furnace, affecting the safety of boiler operation, and it is significant to carry out the research of the slagging trend prediction. In this paper, a system for dynamic prediction of slagging trends in the furnace was developed by combining the slagging trend discrimination method based on ash composition analysis with flame emission spectroscopy. Firstly, a flame emission spectroscopy system was installed on the boiler to measure the gas phase alkali metal concentration in the furnace, and then a slagging trends test was carried out in the furnace exit area to obtain the deposition trend of the ash samples. Finally, a dynamic predictive system for predicting slagging in the furnace was developed and applied to the boiler by combining the slagging discriminating trends based on ash composition analysis of different coal samples and online monitoring of gas-phase Na concentrations, which can reflect the monitoring results of each parameter under the current combustion conditions in real-time, indicate the slagging trend in the current combustion state, thus enabling combustion adjustment instructions to prevent severe slagging.

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高碱煤在燃烧过程中释放的碱金属导致炉膛受热面的沾污、结渣问题，影响锅炉运行的安全性，开展炉内结渣趋势的判断研究具有重要意义。采用煤灰成分分析的结渣趋势判别方法与火焰发射光谱技术结合，在锅炉上安装了一套火焰发射光谱系统用于检测炉内气相碱金属质量浓度，使用气冷式取样枪在炉膛出口区域开展结渣试验以获得沉积样的沉积趋势。根据在线监测结果，开发了一种动态预测炉内沾污结渣预报系统。试验结果表明，系统能够实时反映燃烧工况下各参数的监测结果，可以对当前燃烧状态下的结渣趋势进行提示，为预防结渣和进行燃烧调整提供参考。

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黄书益（1969），女，硕士，高级工程师，主要研究方向为ICT、数据分析和人工智能算法及企业数字化转型和智慧电厂建设。

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黄书益（1969），女，硕士，高级工程师，主要研究方向为ICT、数据分析和人工智能算法及企业数字化转型和智慧电厂建设。

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