广东电力2025，Vol.38Issue(8)：12-18,7.DOI:10.3969/j.issn.1007-290X.2025.08.002
基于卡尔曼滤波器的锅炉氧量信号融合优化方法
Boiler Oxygen Signal Fusion Optimization Method Based on Kalman Filter
摘要
Abstract
The oxygen content measurement generally suffers from large numerical deviations at multiple signal points,inconsistent dynamic change trends,and poor credibility due to factors such as the on-site flue gas sampling position and flow field changes.Therefore,a multi-point signal fusion method based on Kalman filter is proposed to obtain oxygen content signals with higher accuracy and reliability.Firstly,the augmented state Kalman filter is used to estimate the dynamic deviation and denoise the oxygen content signals at the air preheater inlet and chimney inlet to eliminate the oxygen content deviation caused by air leakage;secondly,the distributed Kalman filter is used to further fuse the preliminary fusion signal with the furnace outlet oxygen content signal,which has the best real-time performance,to balance the dynamic response and accuracy.Field application verification shows that the fused oxygen content signal has the advantages of high accuracy and fast dynamic response speed.Under stable operating conditions,the variance of the fused oxygen signal is reduced to 0.011 from 0.20 at the furnace outlet and 0.25 at the air preheater inlet.During load-changing conditions,the equivalent inertial time of the fused oxygen signal relative to the chimney inlet signal is shortened by approximately 200 s,which significantly enhances the reliability of the oxygen content signal.关键词
火电厂/卡尔曼滤波/锅炉氧量/数据融合Key words
thermal power plant/Kalman filter/boiler oxygen/data fusion分类
信息技术与安全科学引用本文复制引用
赵国龙,田亮..基于卡尔曼滤波器的锅炉氧量信号融合优化方法[J].广东电力,2025,38(8):12-18,7.基金项目
国家重点研发计划项目(2022YFB4100400) （2022YFB4100400）
