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为了研究燃煤电站锅炉NOx排放特性,利用可视化火焰检测系统对燃煤锅炉燃烧火焰和温度场进行了测试研究。通过测量,由双色测温法计算得到了炉内温度场,采用数字图像处理技术提取了火焰图像特征参数,进而借助非线性偏最小二乘法建立了由炉内燃烧温度场及火焰图像特征参数来预测NOx排放量的模型。结果表明,所建模型预测值与实测值具有一致性,从而为燃煤锅炉通过燃烧调整,以降低NOx排放和提高锅炉效率提供了有效手段。
In order to study the NOx emission characteristics of coal-fired power station boiler, the flame and temperature field of coal-fired boiler were tested by visual flame detection system. Through the measurement, the temperature field in the furnace was calculated by the two-color temperature measurement method. The digital image processing technique was used to extract the characteristic parameters of the flame image, and then the non-linear partial least square method was used to establish the temperature field and flame image characteristic parameters Model to predict NOx emissions. The results show that the predicted value of the model is consistent with the measured value, which provides an effective means for the coal-fired boiler to reduce the NOx emission and improve the boiler efficiency by adjusting the combustion.