基于数据挖掘算法的垂直水冷壁壁温预测模型  

Prediction model of vertical water wall temperature using data mining algorithm

作　　者：吴戈杨 魏国华[2] 凌朝年 路丕思 WU Geyang;WEI Guohua;LING Chaonian;LU Pisi(Guangdong Datang International Leizhou Power Generation Co.,Ltd.,leizhou 524255,China;State Key Laboratory of Low-carbon Thermal Power Generation Technology and Equipments(Harbin Boiler Company Limited),Harbin 150046,China)

机构地区：[1]广东大唐国际雷州发电有限责任公司,广东雷州524255 [2]低碳热力发电技术与装备全国重点实验室(哈尔滨锅炉厂有限责任公司),黑龙江哈尔滨150046

出　　处：《锅炉制造》2023年第5期4-6,12,共4页Boiler Manufacturing

摘　　要：结合某电厂垂直水冷壁壁温频繁超温问题,采用垂直水冷壁壁温超温机理和门控神经网络算法(GRU)相融合的方法,建立壁温预测模型,采集电厂历史运行数据,经数据预处理生成数据集,统计与分析预测模型数据训练结果,确定研究与优化方向,提高预测模型的精度和鲁棒性。Combined with the frequent overtemperature problem of the vertical water wall in power plant,the overtemperature mechanism of vertical water wall and the gated neural network algorithm(GRU) are integrated to establish the prediction model,collect the historical operation data of power plant and perform data preprocessing,based on the statistics and analysis of data training results,develop further research and optimization direction to improve the accuracy and robustness of prediction model.

关 键 词：垂直水冷壁壁温超温 预测模型 数据挖掘 GRU 

分 类 号：TK227[动力工程及工程热物理—动力机械及工程]