【摘要】 针对水泥烧成过程的资源浪费以及难以建立有效数学机理模型的问题,提出一种基于水泥工业烧成系统动态能耗优化方法。该方法利用卷积神经网络构建了烧成系统电耗与煤耗的目标函数,利用差分进化算法对运行指标进行反向求解,得到符合当前工况的较优的运行指标。由于实际生产工况会随着时间变化,所以将未来时刻的运行指标与电耗、煤耗保存下来,再次输入神经网络中进行训练,并通过当前时刻的实际运行指标值确定运行指标的约束范围,使优化值可以满足实际运行指标的调整要求。该方法实现了水泥烧成过程动态能耗的目标优化,有效地降低了水泥烧成过程的能源消耗。更多还原

【Abstract】 Aiming at the problem of resource waste in the process of cement firing and the difficulty of establishing an effective mathematical mechanism model, a dynamic energy optimization method based on the cement industry firing system was proposed. The method used the convolutional neural network to construct the objective function of power consumption and coal consumption of the firing system. The differential evolution algorithm was used to solve the control parameters in reverse, and the better operating index was obtained according to the current working conditions. Since the actual production conditions will change with time, the operating indicators and power consumption and coal consumption in the future will be saved, and then input into the neural network for training, and the constraint range will be determined by the actual running index value at the current time. The optimization value can meet the actual operation index adjustment requirements. Furthermore, the goal optimization of the dynamic energy consumption state of the cement firing process was realized. It effectively reduces the energy consumption of cement firing process.更多还原