【摘 要】
：
根据飞灰质量浓度与烟气速度的计算式建立了以易测取量为输入参数的磨损预测数学模型,通过测取预测模型的输入参数,对受热面的磨损量进行预测,并将其表示为过量空气系数与飞
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根据飞灰质量浓度与烟气速度的计算式建立了以易测取量为输入参数的磨损预测数学模型,通过测取预测模型的输入参数,对受热面的磨损量进行预测,并将其表示为过量空气系数与飞灰细度的函数.结果表明:过量空气系数和飞灰细度对磨损量影响显著;控制过量空气系数与煤粉细度,可以有效地降低磨损量;结合输入参数的在线测量,该模型亦可作为锅炉对流管束磨损的监测模型.
According to the calculation formula of mass concentration of fly ash and flue gas velocity, a mathematical model of wear prediction based on easy measurement is established. By measuring the input parameters of prediction model, the wear quantity of heated surface is predicted and expressed as As the function of excess air ratio and fly ash fineness.The results show that excess air ratio and fly ash fineness have a significant impact on the wear volume.Controlling the excess air ratio and coal fineness can effectively reduce the wear volume.According to the input parameters On-line measurement, the model can also be used as boiler convection tube bundle wear monitoring model.
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