公开(公告)号：US12187633B2

公开(公告)日：2025-01-07

申请号：US16551297

申请日：2019-08-26

Applicant: BEIJING UNIVERSITY OF TECHNOLOGY

Inventor： Hong-Gui Han ,  Ying-Xu Wang ,  Shu-Jun Wu ,  Min Guo

IPC: C02F3/00 ,  B01D65/08 ,  C02F3/12 ,  G01N17/00

Abstract: To solve problems of frequent occurrence and great harm of membrane fouling during MBR wastewater treatment process, the invention proposes a membrane fouling intelligent early warning method to realize online and accurate early warning of membrane fouling. This early warning method achieves accurate prediction of water permeability by constructing soft-computing model based on recurrent fuzzy neural network. The intelligent early warning of membrane fouling is achieved by the comprehensive evaluation method, which solves the problem that membrane fouling is difficult to be early warning in the MBR wastewater treatment process, improves the pretreatment ability of membrane fouling, reduces the damage caused by membrane fouling, ensures the safe operation of MBR wastewater treatment process, and promotes efficient and stable operation of MBR wastewater treatment plant.

公开(公告)号：US20240425397A1

公开(公告)日：2024-12-26

申请号：US18827659

申请日：2024-09-06

Applicant: BEIJING UNIVERSITY OF TECHNOLOGY

Inventor： Hong-Gui Han ,  Lin-lin Zhang ,  Jun-Fei Qiao

IPC: C02F3/00 ,  C02F1/00 ,  C02F3/30

Abstract: A data-knowledge driven multi-objective optimal control method for municipal wastewater treatment process belongs to the field of wastewater treatment. To balance the energy consumption and effluent quality, a data driven multi-objective optimization model, including energy consumption model and effluent quality model are established to obtain the nonlinear relationship along energy consumption, effluent quality and manipulated variables. Meanwhile, a multi-objective particle swarm optimization algorithm, based on evolutionary knowledge, is proposed to optimize the set-points of nitrate nitrogen and dissolved oxygen. Moreover, the proportional integral differential (PID) controller is designed to track the set-points. Then the effluent quality can be improved and the energy consumption can be reduced.

公开(公告)号：US20210395120A1

公开(公告)日：2021-12-23

申请号：US17334535

申请日：2021-05-28

Applicant: BEIJING UNIVERSITY OF TECHNOLOGY

Inventor： Hong-Gui Han ,  Lin-lin Zhang ,  Jun-Fei Qiao

IPC: C02F3/00 ,  C02F3/30 ,  G05B19/042

Abstract: A data-knowledge driven multi-objective optimal control method for municipal wastewater treatment process belongs to the field of wastewater treatment. To balance the energy consumption and effluent quality, a data driven multi-objective optimization model, including energy consumption model and effluent quality model are established to obtain the nonlinear relationship along energy consumption, effluent quality and manipulated variables. Meanwhile, a multi-objective particle swarm optimization algorithm, based on evolutionary knowledge, is proposed to optimize the set-points of nitrate nitrogen and dissolved oxygen. Moreover, the proportional integral differential (PID) controller is designed to track the set-points. Then the effluent quality can be improved and the energy consumption can be reduced.