重庆理工大学学报2024，Vol.38Issue(17)：210-217,8.DOI:10.3969/j.issn.1674-8425(z).2024.09.026
多算法融合的超临界W火焰炉水冷壁壁温预测模型研究
Study on wall temperature prediction model of supercritical W-shape flame boiler based on algorithms integration
摘要
Abstract
Addressing the water wall cracking in some thermal power plant under deep peak shaving conditions requires the monitoring of the temperature gradient between water wall tubes.This paper builds a predictive model based on PCA-SSA-LSTM algorithms integration to achieve effective prediction of outlet wall temperature near susceptible cracking tubes.First,to enhance the predictive performance of the model,17 input parameters are selected by wall temperature calculation theory,and PCA is employed for dimensionality reduction.Then,the SSA algorithm is adopted to optimize the hyperparameters of the PCA-LSTM prediction model,resulting in the optimal PCA-SSA-LSTM wall temperature prediction model.Comparison with other prediction models reveals a certain increase in the coefficient of determination (R2) for the model,along with varying degrees of reduction in root mean square error (RMSE) and mean absolute percentage error (MAPE).Application demonstrates the algorithms integration model effectively enhances the accuracy of predicting outlet wall temperatures for multiple tubes,serving as a supplement for the power plant' s DCS system to issue early alerts of critical wall temperatures,thereby reducing the risk of water wall cracking caused by large temperature differences between tubes.关键词
多算法融合/建模/超临界W火焰炉/水冷壁管/壁温预测Key words
algorithms integration/modeling/supercritical w-flame boiler/water-cooled wall tubes/wall temperature prediction分类
能源科技引用本文复制引用
殷金桥,钱进,邓传记,杨柳..多算法融合的超临界W火焰炉水冷壁壁温预测模型研究[J].重庆理工大学学报,2024,38(17):210-217,8.基金项目
贵州省科技支撑计划项目(20202Y040) （20202Y040）
国家电投集团贵州金元茶园发电有限责任公司科技项目(CPCEC-ZCB-13-2022-16-11) （CPCEC-ZCB-13-2022-16-11）
