同济大学学报（自然科学版）2026，Vol.54Issue(4)：544-553,10.DOI:10.11908/j.issn.0253-374x.25001
基于卡尔曼滤波-反问题模型的入河排口监管方法
A Monitoring Method for Outfalls Along River Based on Kalman Filter-inverse Problem Model
摘要
Abstract
The supervision of underwater outfalls along the river is challenging in improving the quality and efficiency of urban wastewater treatment.In response to the high cost and poor real-time performance of current techniques such as manual inspections and geophysical imaging techniques in the monitoring of outfalls,the mathematical model of the inverse problem was established by coupling the hydrodynamic model and the Markov Chain-Monte Carlo algorithm,and the Kalman filter strategy was introduced to inversely estimate the dynamic discharge rates of the outfalls based on online water level and flow monitoring information.The results indicated that this inverse problem model can effectively invert the dynamic variation of outfall drainage,with an inversion error below 10%and save nearly half of the calculation time compared with the Markov Chain-Monte Carlo algorithm without introducing Kalman filter.Based on this mathematical model,an online monitoring system could be integrated to achieve effective dynamic supervision of the outfalls,thereby providing technical foundation for developing an intelligent outfall monitoring system with the support of the online monitoring technology.关键词
入河排口/反问题/水动力模型/卡尔曼滤波/贝叶斯优化算法Key words
outfall/inverse problem/hydrodynamic model/Kalman filter/Bayesian optimization algorithm分类
资源环境引用本文复制引用
贾子琛,王万琼,彭寿海,李雅晴,赵志超,尹海龙..基于卡尔曼滤波-反问题模型的入河排口监管方法[J].同济大学学报（自然科学版）,2026,54(4):544-553,10.基金项目
中国长江三峡集团科研项目(GCZX-202403181) （GCZX-202403181）
国家重点研发计划(2021YFC3200703) （2021YFC3200703）
