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蓄热式加热炉是通过蓄热室热交换的高温空气燃烧技术,利用纯高炉煤气为燃料,具有高效烟气余热回收、低污染排放等优点,在工业生产中应用越来越广泛。由于蓄热式加热炉采用左右两侧空气、煤气交替切换燃烧,在切换期间其温度对象处于非控状态,切换周期为3～5min,常规的双交叉限幅燃烧控制策略巳不再适用。本文运用神经网络方法在线建立当前工况下温度控制平衡工作点,在此基础上通过模糊控制策略实现蓄热式加热炉温度控制,实际应用结果表明这种控制策略有效解决了蓄热式加热炉切换燃烧控制问题。
Regenerative furnace is a high temperature air combustion technology through the heat exchange of regenerator, using pure blast furnace gas as fuel, with the advantages of high efficiency flue gas waste heat recovery, low emission and other advantages, more and more widely used in industrial production. Because the regenerative heating furnace uses the left and right air and the gas alternates the combustion, the temperature object is in an uncontrolled state during switching, and the switching period is 3 to 5 minutes. The conventional double cross-limiting limiting combustion control strategy no longer applies. In this paper, the temperature control equilibrium working point under current conditions is established online using neural network method. Based on this, the temperature control of regenerative heating furnace is realized by fuzzy control strategy. The practical application shows that this control strategy can effectively solve the problems of regenerative heating furnace Switch to combustion control problem.