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投稿时间：2023-02-24
投稿时间：2023-02-24
中文摘要: 针对燃煤电厂中煤粉细度难以测量的问题,提出了一种基于遗传算法优化最小二乘支持向量机(LSSVM)超参数的煤粉细度软测量方法。通过制粉系统特性试验,综合分析出影响磨煤机煤粉细度参数的主要因素。采用遗传算法优化支持向量机超参数方法构建煤粉细度软测量模型。将该方法用于特性试验,发现检验样本的均方根误差为1.7%,证明煤粉细度软测量方法有效,满足煤粉细度模型精确预测的需求。
Abstract:Aiming at the problem that it is difficult to measure pulverized coal fineness in coal-fired power plants,a soft measurement method of pulverized coal fineness based on genetic algorithm optimization of least square support vector machine super parameters is proosed in this paper.The main factors affecting pulverized coal fineness parameters of pulverized coal mill are analyzed comprehensively through the characteristic experiment of pulverized coal system.The soft sensor model of pulverized coal fineness is constructed by the superparameter method of support vector machine optimized by genetic algorithm.The method is applied to a practical case,and the root-mean-square error of the test sample is 1.7%,which proves the validity of the soft measurement method of pulverized coal fineness,and meets the demand of accurate prediction of pulverized coal fineness model.
keywords: coal fineness parameters optimization least squares support vector machine soft measurement
文章编号：20235008 中图分类号：TK37 文献标志码：
基金项目:
| Author Name | Affiliation | |
| ZHU Wanjin | National Energy Group Xuzhou Power Generation Co., Ltd., Xuzhou, Jiangsu 221100, China | 12069564@chnenergy.com.cn |
| YUE Junfeng | Jiangsu Fangtian Power Technology Co., Ltd., Nanjing, Jiangsu 211102, China |
引用文本：
朱万进,岳峻峰.基于GA-LSSVM直吹式制粉系统煤粉细度软测量[J].上海电力大学学报,2023,39(5):472-478.
ZHU Wanjin,YUE Junfeng.Soft Measurement of Pulverized Coal Fineness in Direct Blowing Pulverized System Based on GA-LSSVM[J].Journal of Shanghai University of Electric Power,2023,39(5):472-478.
朱万进,岳峻峰.基于GA-LSSVM直吹式制粉系统煤粉细度软测量[J].上海电力大学学报,2023,39(5):472-478.
ZHU Wanjin,YUE Junfeng.Soft Measurement of Pulverized Coal Fineness in Direct Blowing Pulverized System Based on GA-LSSVM[J].Journal of Shanghai University of Electric Power,2023,39(5):472-478.