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作 者:丁海霞 李爱民[1] 刘传群 DING Haixia;LI Aimin;LIU Chuanqun(Key Laboratory of Industrial Ecology and Environmental Engineering,Ministry of Education,School of Environmental Science and Technology,Dalian University of Technology,Dalian 116024,China)
机构地区:[1]大连理工大学环境学院工业生态与环境工程教育部重点实验室,辽宁大连116024
出 处:《大连理工大学学报》2025年第3期235-242,共8页Journal of Dalian University of Technology
基 金:辽宁省兴辽英才计划资助项目(XLYC2008012).
摘 要:焚烧因其减容、减量及能源回收利用等优势而成为生活垃圾主要处理技术.为了解决生活垃圾焚烧过程控制中多个运行操作参数调节困难的问题,利用机器学习(ML)对垃圾焚烧过程中的运行操作参数和控制变量进行高精度非线性映射,达到根据控制变量要求来自动定量调节运行操作参数的目的.采用神经网络和模糊推理系统算法来构建拟合控制模型,基于Aspen Plus垃圾焚烧模拟数据的训练和验证,得出的最优模型为SC-ANFIS,此模型对垃圾进料量、空气供给量、氨水投加量和氢氧化钙溶液投加量预测结果的决定系数(R^(2))分别为0.8322、0.9965、0.9957和0.9994,平均绝对百分比误差(MAPE)分别为2.1330%、0.6835%、1.8782%和0.6400%.因此,该模型可应用于生活垃圾焚烧过程控制,提高垃圾焚烧控制精度及自动化程度.Incineration has become the main treatment technology of domestic waste because of its advantages in capacity reduction,quantity reduction,energy recycling and utilization.In order to solve the problem of difficult adjustment of multiple operating parameters in the process control of domestic waste incineration,machine learning(ML)is used to perform high-precision nonlinear mapping of operating parameters and control variables in the process of waste incineration,so as to achieve the purpose of automatically and quantitatively adjusting operating parameters according to the requirements of control variables.Neural network and fuzzy inference system algorithm are used to construct the fitting control model.Based on training and validation with the simulation data of waste incineration in Aspen Plus,the obtained optimal model is SC-ANFIS.The determination coefficients(R^(2))of the prediction results of waste feeding amount,air supply,ammonia water dosage and calcium hydroxide solution dosage are 0.8322,0.9965,0.9957 and 0.9994 respectively,and the mean absolute percentage errors(MAPE)are 2.1330%,0.6835%,1.8782%and 0.6400%respectively.Therefore,the model can be applied to the control of domestic waste incineration process to improve the accuracy and automation of waste incineration control.
分 类 号:X705[环境科学与工程—环境工程] TP181[自动化与计算机技术—控制理论与控制工程] TP183[自动化与计算机技术—控制科学与工程]
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