基于卡尔曼滤波-反问题模型的入河排口监管方法OA

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.