摘要
以750t/d大型生活垃圾焚烧炉为对象,提出了一种基于支持向量机的大型生活垃圾焚烧炉排炉运行参数预测模型。该模型以实际焚烧炉状态参数作为输入变量,对焚烧炉运行控制过程中最主要的4个参数,包括燃烧炉排速度、燃尽炉排速度、一次风机变频控制柜输出频率、二次风机变频控制柜输出频率进行目标预测。结果发现,通过对原始分布式控制系统数据采用ReliefF算法辅以人为筛选进行降维,获取与目标参数相关的特征变量,可以有效实现以上4个目标参数的预测,预测精度分别为:95.64%、99.61%、95.07%、97.09%,基本满足焚烧炉控制精度要求,从而为大型垃圾焚烧炉排炉的自动运行奠定基础。
This paper took the 750 t/d large-scale domestic waste incinerator as the object,and proposed a prediction model for operating parameters of large-scale domestic waste incineration grate furnace based on support vector machine(SVM).The model took the actual incinerator state parameters as input variables to predict the 4 most important parameters in the process of incinerator operation control,including the combustion grate speed,the burn-out grate speed,the output frequency of the primary fan frequency conversion control cabinet and the output frequency of the secondary fan frequency conversion control cabinet.The results show that by using the ReliefF algorithm with artificial screening on the original DCS data to reduce the dimensionality,and obtaining the feature variables related to the target parameters,the prediction for the above four target parameters can be effectively achieved.The prediction accuracy is 95.64%,99.61%,95.07%,97.09%,which basically meets the incinerator control accuracy requirements,thereby laying the foundation for the automatic operation of the large-scale waste incineration grate furnace.
作者
姜明男
汪守康
何俊捷
白力
杜海亮
王松
黄群星
JIANG Mingnan;WANG Shoukang;HE Junjie;BAI Li;DU Hailiang;WANG Song;HUANG Qunxing(State Key Laboratory of Clean Energy Utilization(Zhejiang University),Hangzhou 310027,Zhejiang Province,China;Shanghai SUS Environment Co.,Ltd.,Qingpu District,Shanghai 201703,China;Alibaba Cloud Computing Co.,Ltd.,Hangzhou 311100,Zhejiang Province,China)
出处
《中国电机工程学报》
EI
CSCD
北大核心
2022年第1期221-228,共8页
Proceedings of the CSEE
基金
国家重点研发计划项目(2018YFC1901300)
阿里巴巴-浙江大学前沿技术联合研究中心支持项目。
关键词
炉排炉
运行参数
支持向量机
分类
预测
grate furnace
operating parameters
support vector machine
classification
prediction