CN109976187A - The sewage management platform for being optimized based on biochemical wastewater treatment and being finely aerated - Google Patents
The sewage management platform for being optimized based on biochemical wastewater treatment and being finely aerated Download PDFInfo
- Publication number
- CN109976187A CN109976187A CN201910153344.9A CN201910153344A CN109976187A CN 109976187 A CN109976187 A CN 109976187A CN 201910153344 A CN201910153344 A CN 201910153344A CN 109976187 A CN109976187 A CN 109976187A
- Authority
- CN
- China
- Prior art keywords
- module
- sewage
- data
- parameter
- prediction
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F7/00—Aeration of stretches of water
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B17/00—Systems involving the use of models or simulators of said systems
- G05B17/02—Systems involving the use of models or simulators of said systems electric
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
- Y02W10/00—Technologies for wastewater treatment
- Y02W10/10—Biological treatment of water, waste water, or sewage
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Life Sciences & Earth Sciences (AREA)
- Hydrology & Water Resources (AREA)
- Environmental & Geological Engineering (AREA)
- Water Supply & Treatment (AREA)
- Chemical & Material Sciences (AREA)
- Organic Chemistry (AREA)
- Activated Sludge Processes (AREA)
Abstract
The present invention relates to technical field of sewage, specially a kind of sewage management platform optimized based on biochemical wastewater treatment and be finely aerated, including data reception module, database, prediction module, model building module, model parameter setting module, model correction module, process modeling library, prediction scheme analog module, decision-making module and control module.Data reception module is used to receive the parameter information that each sewage treatment plant uploads, and database is used for parameter information；Prediction module is used to predict the variation tendency of each state parameter of sewage；Process modeling inventory contains the process modeling of each sewage treatment plant；Prediction scheme analog module is used for sewage treatment plant the progress prediction scheme simulation of the case where under the action of external disturbance and generates control program model.It is provided by the invention based on biochemical wastewater treatment optimize with the sewage management platform that is finely aerated, can Optimizing Process Parameters, realize the fine-grained management of sewage treatment process, reduce the power consumption for the treatment of process.
Description
Technical field
It is specially a kind of to be optimized based on biochemical wastewater treatment and be finely aerated the present invention relates to technical field of sewage
Sewage management platform.
Background technique
Biological treatment is the sewage disposal technology widely used at present, and process is a complicated biochemical process,
There is also many optimization spaces to expose especially in terms of aeration control during biochemical treatment for existing sewage disposal system
Gas is most heavy in a very important link and the almost all of sewage plant using biological treatment in sewage treatment
The energy consumption link wanted is come from sewage treatment plant's power consumption of some country, and aeration occupies the 50-70% of total power consumption, so
Aerating system is the key link of the energy-saving operation of entire sewage plant.
The aeration control in China is started late, and what many sewage plants used is still that manual operation is combined with automatic monitoring
Mode.Domestic aeration control method mainly has artificial aeration control, semi-automatic aeration control and Full-automatic aeration control at present
System.Manual operation mainly adjusts blower air quantity according to measurement dissolved oxygen concentration and effluent quality, under this operation, stablizes
Property is poor, usually up to standard as far as possible in order to be discharged, aeration quantity can bigger than normal and labor intensity it is big.Even if semi-automatic aeration control is realized
The acquisition and transmission of data, but still remain the big problem of labor intensity.Full-automatic aeration control is future development
Trend, and Full-automatic aeration control at present still has that aeration is not accurate, power consumption is high, be easy to cause the waste of resource.
Summary of the invention
The invention is intended to provide a kind of sewage management platform optimized based on biochemical wastewater treatment and be finely aerated, Neng Gouyou
Change technological parameter, realizes the fine-grained management of sewage treatment process, reduce the power consumption for the treatment of process.
In order to solve the above-mentioned technical problem, the application provides the following technical solutions:
The sewage management platform for being optimized based on biochemical wastewater treatment and being finely aerated, comprising:
Data reception module, the parameter information uploaded for receiving each sewage treatment plant, the parameter information includes water
Prime number evidence and water data；
Database, the database are used to store the parameter current information and history parameters letter of each sewage treatment plant
It ceases, is also stored with prediction related data in the database；
Prediction module, the prediction module are used for according to parameter current information, historical parameter information and prediction dependency number
It is predicted according to the variation tendency of each state parameter of the sewage to each sewage treatment plant and generates prediction result；
Process modeling library, the process modeling inventory contain the process modeling of each sewage treatment plant；
Prediction scheme analog module, the prediction scheme analog module are used for the process modeling according to sewage treatment plant to sewage treatment plant
Prediction scheme analog result is simulated and generated to the prediction scheme for carrying out external disturbance, and the prediction scheme analog module is also used to be simulated according to prediction scheme and tie
The process modeling of fruit and sewage treatment plant generates control program model；
Decision-making module, the decision-making module are used for the prediction result match control scheme model according to prediction module and generate
Parameter configuration scheme, the parameter configuration scheme includes aeration quantity；
Control module, the control module is for setting the sewage treatment of each sewage treatment plant according to parameter configuration scheme
Standby operating parameter is regulated and controled.
In technical solution of the present invention, the parameter information by receiving each sewage treatment plant constructs a perfect sewage
Database is handled, prediction module is realized by big data analysis means to each sewage according to the data of sewage treatment database
Each state parameter of the sewage for the treatment of plant, such as water quality, the variation tendency of water are predicted, and then can be determined in advance
Plan and deployment, by prediction scheme analog module, using process modeling library, to each sewage treatment plant under the action of external disturbance
Situation is simulated and emulates such as the case where Sewage shock or emergency event, generates prediction scheme analog result, and be directed to prediction scheme
Analog result is analyzed, and the control program model for being directed to different external disturbances is generated, and decision-making module is then based on prediction module
Prediction result, make corresponding aid decision suggestion, generate parameter configuration scheme, and by control module remotely to each sewage
The sewage disposal device for the treatment of plant is regulated and controled, and then auto-control equipment running status, reach adjustment and Optimizing Process Parameters,
Realize the purpose of factory's group's scheduling and fining control., can be to the regulation that aeration quantity is refined during this, it can be with
Optimal parameter configuration is made for various external disturbances, aeration efficiency is improved, reduces aeration energy consumption.
Further, the prediction scheme simulation includes temperature change simulation, water change modeling and sludge loading amount changing pattern
It is quasi-.Prediction scheme simulation is carried out in terms of temperature, water and sludge loading amount three, can be covered common all kinds of external disturbances and be made
At emergency case.
Further, the state parameter includes temperature data, water data and sludge loading amount data, from temperature, water
Three aspects of amount and sludge loading amount are predicted, are adapted with prediction scheme simulation.
Further, the water quality data includes temperature data, pH data, DO data, SS data, COD data, ammonia nitrogen number
According to, total nitrogen data and total phosphorus data, the water quality condition of sewage can be more comprehensively reacted.
It further, further include model building module and model parameter setting module, the model building module is used for for pipe
Reason personnel create process modeling, and the model parameter setting module is used to set the parameters of process modeling for user, convenient
Administrative staff create process modeling.
It further, further include model correction module, the model correction module includes parameter calibration analysis module and sensitivity
Property analysis module, the model correction module for process modeling of the administrative staff to sewage treatment plant for being corrected.It can be with
Process modeling is corrected, so that prediction scheme simulation is more accurate.
Further, the process modeling uses ASM2D model.ASM2D model includes multiple biochemical reaction processes, model group
Point, Chemical Measurement constant and kinetic parameter, biology can be simulated except processes such as carbon, denitrogenation and dephosphorization, be widely used in
Sewage treatment field.
Detailed description of the invention
Fig. 1 is that the present invention is based on the logical boxs of biochemical wastewater treatment optimization and the sewage management platform embodiment being finely aerated
Figure；
Fig. 2 is that the present invention is based on aerators in factory's group's monitoring water quality and the sewage management platform embodiment two of modelling management
Structure sectional view.
Specific embodiment
It is further described below by specific embodiment:
Appended drawing reference in Figure of description include: installing pipe 1, mounting base 2, installation set 3, connecting tube 4, the first jet pipe 5,
Aeration plate 6, tension spring 7, motor 8, first gear 9, the second spline 10, the first spline 11.
Embodiment one
As shown in Figure 1, the disclosed sewage management platform optimized based on biochemical wastewater treatment and be finely aerated of the present embodiment,
Including data reception module, database, prediction module, model building module, model parameter setting module, model correction module,
Process modeling library, prediction scheme analog module, decision-making module and control module.Wherein:
Data reception module is used to receive the parameter information that each sewage treatment plant uploads, and parameter information includes water quality number
According to, water data and equipment operating data.Database is used to store the parameter current information and history of each sewage treatment plant
Parameter information is also stored with prediction related data in database.In this implementation, water quality data includes temperature data, pH data, DO
Data, SS data, COD data, ammonia nitrogen data, total nitrogen data and total phosphorus data.Predict that related data includes sewage treatment plant
Geographical location, geography and climate, history rainfall information, the weather forecast information in location etc..
Prediction module be used for according to parameter current information, historical parameter information and prediction related data to each sewage at
The variation tendency for managing each state parameter of the sewage of factory is predicted and generates prediction result.In the present embodiment, state parameter
Including temperature data, water data and sludge loading amount data, prediction module using existing BP neural network technology come into
Row prediction specifically constructs one three layers of BP neural network model, including input layer, hidden layer and output layer, this implementation first
In example, using the parameter information of sewage treatment plant and prediction related data as the input of input layer, therefore input layer has 13
Node, and output is the prediction to temperature, water and sludge loading amount, therefore shares 3 nodes；It is directed to hidden layer, this reality
It applies example and has used following formula to determine the quantity of hidden node:Wherein l is the number of nodes of hidden layer, and n is
The number of nodes of input layer, m are the number of nodes of output layer, and a is a number between 1 to 10, are taken as 3 in the present embodiment, therefore hidden
Layer shares 7 nodes.BP neural network generallys use the excitation function of Sigmoid differentiable function and linear function as network.
Excitation function of the S type tangent function tansig as hidden neuron is selected herein.Prediction model chooses S type logarithmic function
Excitation function of the tansig as output layer neuron.After the building of BP network model, the history parameters of database are utilized
Information and prediction related data are trained model as sample, due to being stored with data over the years in database,
The model obtained after the completion of training can obtain accurate prediction result.
Process modeling inventory contains the process modeling of each sewage treatment plant；Model building module is used to create for administrative staff
Process modeling is built, model parameter setting module is used to set the parameters of process modeling for user.Model correction module includes
Parameter calibration analysis module and sensitivity analysis module, model correction module are used for for administrative staff to the technique of sewage treatment plant
Model is corrected.In this implementation, process modeling uses ASM2D model.ASM2D includes 21 biochemical reaction processes, 19 kinds of moulds
Type component, 22 Chemical Measurement constants and 42 kinetic parameters can simulate biology and remove the processes such as carbon, denitrogenation and dephosphorization,
It is widely used in sewage treatment field, in the present embodiment, by taking AAO process modeling as an example, user selects AAO when creating model
Process modeling, the layout for then drawing each equipment in sewage treatment plant are completed model creation, are then set by model parameter
Cover half block is configured the parameters of process modeling, parameter, the volume of node, oxygen mass transfer coefficient, row of node of such as intaking
The parameters such as mud amount, interior regurgitant volume.After process modeling creates, for effluent quality result and the actual conditions phase for obtaining model
Symbol, it is also necessary to check and checking research be carried out to model, the model correction module in the present embodiment can pass through parameter for user
Calibration and sensitivity analysis are corrected model, parameter calibration refer to parameter substitute into model obtains calculated result, then
Calculated result is compared with measured data, is adjusted according to calculated result to parameter, so that measured data and calculating data
Difference is minimum, such as the calibration for the parameter for component of intaking, then is sampled and tests according to table one.
Table one
In the present embodiment, sensitivity analysis module can for user to model carry out sensitivity analysis, and then to model into
Row checks work.
Prediction scheme analog module be used for according to the process modeling of sewage treatment plant to sewage treatment plant external disturbance effect
Under situation carry out prediction scheme simulation and generate prediction scheme analog result, prediction scheme simulation includes temperature change simulation, water change modeling
And sludge loading amount change modeling, prediction scheme analog module are also used to the technique mould according to prediction scheme analog result and sewage treatment plant
Type generates control program model.Control program model includes match parameter and regulation parameter, and match parameter includes the control program
The parameter area of model applicable sewage quality and water, including water data, temperature data and sludge loading amount parameter, are adjusted
Controlling parameter includes the parameters such as aeration quantity, aeration time, interior return flow.
Decision-making module is obtained for being matched according to the prediction result of prediction module with the match parameter of control program model
To most matched control program model and using the regulation parameter of control program model as parameter configuration scheme.
Control module is used for according to parameter configuration scheme to the operating parameter of the sewage disposal device of each sewage treatment plant
Regulated and controled.
In the present embodiment, the parameter information by receiving each sewage treatment plant constructs a perfect sewage treatment number
According to library, prediction module is realized by big data analysis means to each sewage treatment plant according to the data of sewage treatment database
Sewage each state parameter, such as water quality, the variation tendency of water predicted, and then can carry out decision and portion in advance
Administration, by prediction scheme analog module, using process modeling library, to each sewage treatment plant the external disturbance the case where, as sewage rushes
It hits or the case where emergency event, prediction scheme simulation is carried out in terms of temperature, water and sludge loading amount three, can be covered common
All kinds of external disturbances caused by emergency case, then generate prediction scheme analog result, and analyzed for prediction scheme analog result,
The control program model for being directed to different external disturbances is generated, decision-making module then based on the prediction result of prediction module, makes phase
The aid decision suggestion answered generates parameter configuration scheme, and by the control module remotely sewage treatment to each sewage treatment plant
Equipment is regulated and controled, and then auto-control equipment running status, reach adjustment and Optimizing Process Parameters, realize factory's group's scheduling and
Refine the purpose of control.During this, various external disturbances can be directed to the regulation that aeration quantity is refined
Optimal parameter configuration is made, aeration efficiency is improved, reduces aeration energy consumption.
Embodiment two
As shown in Fig. 2, the difference between this embodiment and the first embodiment lies in: it further include aerating system in the present embodiment, institute
Stating aerating system includes control cabinet, aerator and the pipeline for connecting aerator, and array distribution has installation straight up on pipeline
Pipe 1, aerator include installation set 3 and mounting base 2, and mounting base 2 and installing pipe 1 are rotatablely connected, between mounting base 2 and installation set 3
Be fixedly connected, and be equipped with 30 degree of angle between installation set 3 and installing pipe 1, be additionally provided with motor 8 in installing pipe 1, motor 8 it is defeated
Shaft is equipped with first gear 9, and second gear is socketed in mounting base 2, and the motor 8 can control the rotation of mounting base 2, in turn
It can control the inclined direction of installation set 3, installation set 3 is equipped with aeration head, and the aeration head includes aeration plate 6 and connecting tube 4,
Connecting tube 4 is equipped with the first spline 11 and the second spline 10, and installation set 3 is protruded into far from one end of pipeline in one end of connecting tube 4,
It is equipped with Turbo Flora keyway in installation set 3 and is equipped with swivelling chute on the top of Turbo Flora keyway, connecting tube 4 passes through 11 He of the first spline
Second spline 10 is connect with installation set 3, and part of the connecting tube 4 between the first spline 11 and the second spline 10 is equipped with the first spray
Pipe 5 and the second jet pipe, first jet pipe 5 and the second jet pipe are symmetrical arranged and along the eccentric axial of installation set 3 not in same
On straight line, connecting tube 4, which protrudes into, is equipped with tension spring 7 between one end in installation set 3 and installation set 3.
Pipeline connection has aeration blower, and solenoid valve is equipped between each aerator and pipeline, is equipped in the control cabinet
Controller and wireless communication module, controller module and control module data connection, solenoid valve and controller by wireless communication
Connection, configuration parameter relevant to aeration in parameter configuration scheme is sent to controller by control module, by controller to air blast
Machine and solenoid valve are controlled；Control module includes aeration control module, and aeration control module includes occlusion adjustments module, institute
Occlusion adjustments module is stated for judging some region of aeration in biochemical reaction tank according to the received DO data of data reception module
Whether device blocks, and occlusion adjustments module is also used to when detecting that a certain region DO data are too low, controls other surrounding exposures
The motor 8 of gas device rotates, and adjusts the blocked aerator of the inclined direction alignment of these aerators, while controlling blocking region
The corresponding solenoid valve discontinuity opening and closing of aerator.
In the present embodiment, since installation set 3 is obliquely installed, the aeration plate 6 of aerator top surface can be made to tilt, Jin Erke
To allow Parts of deposits to slide from aeration plate 6, when aerator being avoided to be not turned on, accumulative deposit object, tilts simultaneously on aeration plate 6
The aeration plate 6 of setting can make the direction for spraying gas change, and then increase the time of contact of gas and sewage, work as exposure
When gas disk 6 blocks, under the influence of air pressure, aeration head can be moved up along spline, be rotated simultaneously, when the first jet pipe 5
When leaking out with the second jet pipe, the first spline 11 is entered in swivelling chute at this time, due to the first jet pipe 5 and the second jet pipe central symmetry
Distribution, therefore under the reaction of the gas of ejection, on the one hand aeration head rotation, the first jet pipe 5 and the second jet pipe can be used as
Spare spray orifice is aerated the sewage of surrounding after the blocking of aeration plate 6, and on the other hand, the first jet pipe 5 and the second jet pipe make
Aeration head rotation is obtained, aeration head can be cleaned, the opening and closing cooperation tension spring 7 of solenoid valve discontinuity is it is also possible that aeration head
Displacement up and down reciprocatingly occurs, further the deposit on aeration head can be cleared up, is carried out after realizing aerator blocking
Self-cleaning function.When aerator blocking is more serious, surrounding aerator adjusts the direction of aeration plate 6 by motor 8,
Gas is sprayed to the aerator direction of blocking, the sewage of blocking region can be aerated, while water flow being pushed to flow, to stifled
The aeration plate 6 of the aerator of plug is cleared up, and whether can restore according to aerator after cleaning, judges that aerator is internal stifled
Plug or external blocking.
The above are merely the embodiment of the present invention, the common sense such as well known specific structure and characteristic are not made excessively herein in scheme
Description, all common of technical field that the present invention belongs to before one skilled in the art know the applying date or priority date
Technological know-how can know the prior art all in the field, and have using routine experiment means before the date
Ability, one skilled in the art can improve in conjunction with self-ability under the enlightenment that the application provides and implement we
Case, some typical known features or known method should not become the barrier that one skilled in the art implement the application
Hinder.It should be pointed out that for those skilled in the art, without departing from the structure of the invention, if can also make
Dry modification and improvement, these also should be considered as protection scope of the present invention, these all will not influence the effect that the present invention is implemented and
Patent practicability.The scope of protection required by this application should be based on the content of the claims, the specific reality in specification
Applying the records such as mode can be used for explaining the content of claim.
Claims (7)
1. the sewage management platform for being optimized based on biochemical wastewater treatment and being finely aerated, comprising:
Data reception module, the parameter information uploaded for receiving each sewage treatment plant, the parameter information includes water quality number
According to water data；
Database, the database are used to store the parameter current information and historical parameter information of each sewage treatment plant, institute
It states and is also stored with prediction related data in database；
Prediction module, the prediction module are used for according to parameter current information, historical parameter information and prediction related data pair
The variation tendency of each state parameter of the sewage of each sewage treatment plant is predicted and generates prediction result；
Process modeling library, the process modeling inventory contain the process modeling of each sewage treatment plant；
Prediction scheme analog module, the prediction scheme analog module are used for according to the process modeling of sewage treatment plant to sewage treatment plant outside
The case where under the action of portion's interference, carries out prediction scheme simulation and generates prediction scheme analog result, and the prediction scheme analog module is also used to basis
The process modeling of prediction scheme analog result and sewage treatment plant generates control program model；
Decision-making module, the decision-making module are used for the prediction result match control scheme model according to prediction module and generate parameter
Allocation plan, the parameter configuration scheme includes aeration quantity；
Control module, the control module are used for according to parameter configuration scheme to the sewage disposal device of each sewage treatment plant
Operating parameter is regulated and controled.
2. the sewage management platform according to claim 1 optimized based on biochemical wastewater treatment and be finely aerated, feature
Be: the prediction scheme simulation includes temperature change simulation, water change modeling and sludge loading amount change modeling.
3. the sewage management platform according to claim 2 optimized based on biochemical wastewater treatment and be finely aerated, feature
Be: the state parameter includes temperature data, water data and sludge loading amount data.
4. the sewage management platform according to claim 3 optimized based on biochemical wastewater treatment and be finely aerated, feature
Be: the water quality data includes temperature data, pH data, DO data, SS data, COD data, ammonia nitrogen data, total nitrogen data
And total phosphorus data.
5. the sewage management platform according to claim 4 optimized based on biochemical wastewater treatment and be finely aerated, feature
It is: further includes model building module and model parameter setting module, the model building module is used to create for administrative staff
Process modeling, the model parameter setting module are used to set the parameters of process modeling for user.
6. the sewage management platform according to claim 5 optimized based on biochemical wastewater treatment and be finely aerated, feature
It is: further includes model correction module, the model correction module includes parameter calibration analysis module and sensitivity analysis module,
The model correction module for process modeling of the administrative staff to sewage treatment plant for being corrected.
7. the sewage management platform according to claim 6 optimized based on biochemical wastewater treatment and be finely aerated, feature
Be: the process modeling uses ASM2D model.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910153344.9A CN109976187B (en) | 2019-02-28 | 2019-02-28 | Sewage management platform based on sewage biochemical treatment optimization and fine aeration |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910153344.9A CN109976187B (en) | 2019-02-28 | 2019-02-28 | Sewage management platform based on sewage biochemical treatment optimization and fine aeration |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109976187A true CN109976187A (en) | 2019-07-05 |
| CN109976187B CN109976187B (en) | 2021-08-17 |
Family
ID=67077663
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910153344.9A Active CN109976187B (en) | 2019-02-28 | 2019-02-28 | Sewage management platform based on sewage biochemical treatment optimization and fine aeration |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109976187B (en) |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111538229A (en) * | 2020-04-28 | 2020-08-14 | 重庆工商大学 | Aquaculture circulating water treatment system based on accurate control of ammonia nitrogen and dissolved oxygen |
| CN111533290A (en) * | 2020-04-30 | 2020-08-14 | 重庆市水务资产经营有限公司 | Method for generating optimal operation plan library of sewage treatment process and applying complex scene |
| CN112875957A (en) * | 2020-12-28 | 2021-06-01 | 国网河北省电力有限公司电力科学研究院 | Thermal power factory optimizes water consumption and waste water zero release processing system |
| CN113033917A (en) * | 2021-04-19 | 2021-06-25 | 重庆工商大学 | Sewage treatment plant prediction planning operation management method based on peripheral data |
| CN113253689A (en) * | 2021-06-11 | 2021-08-13 | 武汉科迪智能环境股份有限公司 | Equipment management method and device and server |
| CN113867233A (en) * | 2021-11-03 | 2021-12-31 | 龙游县河道疏浚砂资源开发有限公司 | Control method and system for granular sludge treatment based on pilot-scale research |
| CN113868983A (en) * | 2021-11-03 | 2021-12-31 | 龙游县河道疏浚砂资源开发有限公司 | Aerobic granular sludge treatment method and system based on CFD modeling simulation |
| CN114291912A (en) * | 2022-01-07 | 2022-04-08 | 北京首创生态环保集团股份有限公司 | Sewage treatment aeration system transformation method based on biological mathematical model |
| CN116675277A (en) * | 2023-08-03 | 2023-09-01 | 济南山源环保科技有限公司 | Control method of low-energy-consumption wastewater concentration system based on Internet of things |
| WO2023173450A1 (en) * | 2022-03-17 | 2023-09-21 | 国网河北省电力有限公司电力科学研究院 | Water-saving expected cost input-based water-saving and emission reduction mathematical solving system for thermal power plant |
| CN117585794A (en) * | 2024-01-19 | 2024-02-23 | 四川绿境科兴环境科技有限公司 | Sewage treatment aeration control method, device, equipment and storage medium |
Citations (23)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN2121449U (en) * | 1992-05-03 | 1992-11-11 | 武汉城市建设学院 | Hidden sucking double-jet aeration unit |
| CN2632076Y (en) * | 2003-07-21 | 2004-08-11 | 华南理工大学 | Jetting aeration distributor |
| CN1590318A (en) * | 1998-03-31 | 2005-03-09 | 韩相培 | Intermittent aeration device and method for waste water treatment equipment |
| CN2816025Y (en) * | 2005-09-02 | 2006-09-13 | 田伯海 | New type efficient rotary-mixing aeration device |
| US20070176307A1 (en) * | 2006-01-27 | 2007-08-02 | Young Richard N | Wastewater treatment system and method of using same |
| CN101182069A (en) * | 2007-11-13 | 2008-05-21 | 清华大学 | Oxidation ditch intelligent control system based on change of water entry |
| KR101046198B1 (en) * | 2011-03-22 | 2011-07-04 | 주식회사 차임이엔지 | A water treatment remote control monitoring system |
| CN202041828U (en) * | 2011-01-13 | 2011-11-16 | 北京工业大学 | Water inflow unstable-variation analog control system for biological wastewater treatment |
| CN102306021A (en) * | 2011-08-16 | 2012-01-04 | 上海交通大学 | Joint debugging and joint control method for guaranteeing biosafety of pipe network water quality based on real-time ArcGis |
| CN102707026A (en) * | 2012-06-06 | 2012-10-03 | 天津大学 | Water reclamation plant raw water quality online early warning system and control method thereof |
| CN102807301A (en) * | 2012-07-31 | 2012-12-05 | 天津大学 | Outlet water quality online monitoring and real-time forecasting system of water reclamation plant and control method thereof |
| CN102902257A (en) * | 2012-10-30 | 2013-01-30 | 威水星空（北京）环境技术有限公司 | Sewage treatment process optimization and energy-saving control system and method |
| WO2013093795A1 (en) * | 2011-12-19 | 2013-06-27 | Ariel-University Research And Development Company, Ltd. | Aeration of liquid suitable for aqueous waste treatment |
| CN103553208A (en) * | 2013-11-19 | 2014-02-05 | 林太才 | Aerator |
| KR101394728B1 (en) * | 2013-12-18 | 2014-05-15 | 엔시스 주식회사 | Appratus and method for aeration and agitation of compressed air type |
| DE202015002787U1 (en) * | 2015-04-16 | 2015-05-19 | Ingolf Kurtze | Device for aeration or gassing of liquids in the flow |
| KR20150095239A (en) * | 2014-02-13 | 2015-08-21 | 정선영 | Contaminated water purification method of the Yellow Sea. |
| CN104931669A (en) * | 2015-06-02 | 2015-09-23 | 苏州高新区、虎丘区环境监测站 | Automatic water quality monitoring integrated system for surface water |
| CN107265627A (en) * | 2017-07-24 | 2017-10-20 | 安徽永生堂药业有限责任公司 | A kind of circulating sanitary sewage aerator |
| DE202018001727U1 (en) * | 2018-04-05 | 2018-04-30 | Thomas Grabosch | Slanting circulating aerator |
| KR101858689B1 (en) * | 2018-01-25 | 2018-05-16 | 환경시설관리 주식회사 | Floating device for cleaning stagnant water |
| CN108640268A (en) * | 2018-05-31 | 2018-10-12 | 张荣斌 | A kind of aeration strains wetting system |
| CN208260331U (en) * | 2017-05-31 | 2018-12-21 | 井陉县玉峰钙业有限公司 | A kind of precipitation of calcium carbonate device |
-
2019
- 2019-02-28 CN CN201910153344.9A patent/CN109976187B/en active Active
Patent Citations (23)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN2121449U (en) * | 1992-05-03 | 1992-11-11 | 武汉城市建设学院 | Hidden sucking double-jet aeration unit |
| CN1590318A (en) * | 1998-03-31 | 2005-03-09 | 韩相培 | Intermittent aeration device and method for waste water treatment equipment |
| CN2632076Y (en) * | 2003-07-21 | 2004-08-11 | 华南理工大学 | Jetting aeration distributor |
| CN2816025Y (en) * | 2005-09-02 | 2006-09-13 | 田伯海 | New type efficient rotary-mixing aeration device |
| US20070176307A1 (en) * | 2006-01-27 | 2007-08-02 | Young Richard N | Wastewater treatment system and method of using same |
| CN101182069A (en) * | 2007-11-13 | 2008-05-21 | 清华大学 | Oxidation ditch intelligent control system based on change of water entry |
| CN202041828U (en) * | 2011-01-13 | 2011-11-16 | 北京工业大学 | Water inflow unstable-variation analog control system for biological wastewater treatment |
| KR101046198B1 (en) * | 2011-03-22 | 2011-07-04 | 주식회사 차임이엔지 | A water treatment remote control monitoring system |
| CN102306021A (en) * | 2011-08-16 | 2012-01-04 | 上海交通大学 | Joint debugging and joint control method for guaranteeing biosafety of pipe network water quality based on real-time ArcGis |
| WO2013093795A1 (en) * | 2011-12-19 | 2013-06-27 | Ariel-University Research And Development Company, Ltd. | Aeration of liquid suitable for aqueous waste treatment |
| CN102707026A (en) * | 2012-06-06 | 2012-10-03 | 天津大学 | Water reclamation plant raw water quality online early warning system and control method thereof |
| CN102807301A (en) * | 2012-07-31 | 2012-12-05 | 天津大学 | Outlet water quality online monitoring and real-time forecasting system of water reclamation plant and control method thereof |
| CN102902257A (en) * | 2012-10-30 | 2013-01-30 | 威水星空（北京）环境技术有限公司 | Sewage treatment process optimization and energy-saving control system and method |
| CN103553208A (en) * | 2013-11-19 | 2014-02-05 | 林太才 | Aerator |
| KR101394728B1 (en) * | 2013-12-18 | 2014-05-15 | 엔시스 주식회사 | Appratus and method for aeration and agitation of compressed air type |
| KR20150095239A (en) * | 2014-02-13 | 2015-08-21 | 정선영 | Contaminated water purification method of the Yellow Sea. |
| DE202015002787U1 (en) * | 2015-04-16 | 2015-05-19 | Ingolf Kurtze | Device for aeration or gassing of liquids in the flow |
| CN104931669A (en) * | 2015-06-02 | 2015-09-23 | 苏州高新区、虎丘区环境监测站 | Automatic water quality monitoring integrated system for surface water |
| CN208260331U (en) * | 2017-05-31 | 2018-12-21 | 井陉县玉峰钙业有限公司 | A kind of precipitation of calcium carbonate device |
| CN107265627A (en) * | 2017-07-24 | 2017-10-20 | 安徽永生堂药业有限责任公司 | A kind of circulating sanitary sewage aerator |
| KR101858689B1 (en) * | 2018-01-25 | 2018-05-16 | 환경시설관리 주식회사 | Floating device for cleaning stagnant water |
| DE202018001727U1 (en) * | 2018-04-05 | 2018-04-30 | Thomas Grabosch | Slanting circulating aerator |
| CN108640268A (en) * | 2018-05-31 | 2018-10-12 | 张荣斌 | A kind of aeration strains wetting system |
Non-Patent Citations (1)
| Title |
|---|
| 王征等: "基于Web的城市污水处理厂决策支持平台研究", 《山东农业大学学报（自然科学版）》 * |
Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111538229A (en) * | 2020-04-28 | 2020-08-14 | 重庆工商大学 | Aquaculture circulating water treatment system based on accurate control of ammonia nitrogen and dissolved oxygen |
| CN111533290A (en) * | 2020-04-30 | 2020-08-14 | 重庆市水务资产经营有限公司 | Method for generating optimal operation plan library of sewage treatment process and applying complex scene |
| CN112875957A (en) * | 2020-12-28 | 2021-06-01 | 国网河北省电力有限公司电力科学研究院 | Thermal power factory optimizes water consumption and waste water zero release processing system |
| CN113033917B (en) * | 2021-04-19 | 2022-04-12 | 重庆工商大学 | Sewage treatment plant prediction planning operation management method based on peripheral data |
| CN113033917A (en) * | 2021-04-19 | 2021-06-25 | 重庆工商大学 | Sewage treatment plant prediction planning operation management method based on peripheral data |
| CN113253689A (en) * | 2021-06-11 | 2021-08-13 | 武汉科迪智能环境股份有限公司 | Equipment management method and device and server |
| CN113868983A (en) * | 2021-11-03 | 2021-12-31 | 龙游县河道疏浚砂资源开发有限公司 | Aerobic granular sludge treatment method and system based on CFD modeling simulation |
| CN113867233A (en) * | 2021-11-03 | 2021-12-31 | 龙游县河道疏浚砂资源开发有限公司 | Control method and system for granular sludge treatment based on pilot-scale research |
| CN113867233B (en) * | 2021-11-03 | 2022-06-03 | 龙游县河道疏浚砂资源开发有限公司 | Control method and system for granular sludge treatment based on pilot-scale research |
| CN113868983B (en) * | 2021-11-03 | 2022-06-03 | 龙游县河道疏浚砂资源开发有限公司 | Aerobic granular sludge treatment method and system based on CFD modeling simulation |
| CN114291912A (en) * | 2022-01-07 | 2022-04-08 | 北京首创生态环保集团股份有限公司 | Sewage treatment aeration system transformation method based on biological mathematical model |
| CN114291912B (en) * | 2022-01-07 | 2022-10-21 | 北京首创生态环保集团股份有限公司 | Sewage treatment aeration system transformation method based on biological mathematical model |
| WO2023173450A1 (en) * | 2022-03-17 | 2023-09-21 | 国网河北省电力有限公司电力科学研究院 | Water-saving expected cost input-based water-saving and emission reduction mathematical solving system for thermal power plant |
| CN116675277A (en) * | 2023-08-03 | 2023-09-01 | 济南山源环保科技有限公司 | Control method of low-energy-consumption wastewater concentration system based on Internet of things |
| CN116675277B (en) * | 2023-08-03 | 2023-10-27 | 济南山源环保科技有限公司 | Control method of low-energy-consumption wastewater concentration system based on Internet of things |
| CN117585794A (en) * | 2024-01-19 | 2024-02-23 | 四川绿境科兴环境科技有限公司 | Sewage treatment aeration control method, device, equipment and storage medium |
| CN117585794B (en) * | 2024-01-19 | 2024-03-26 | 四川绿境科兴环境科技有限公司 | Sewage treatment aeration control method, device, equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109976187B (en) | 2021-08-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109976187A (en) | The sewage management platform for being optimized based on biochemical wastewater treatment and being finely aerated | |
| CN109933027A (en) | Sewage management platform based on factory's group's monitoring water quality and modelling management | |
| EP0432267A1 (en) | Supporting method and system for process control | |
| CN106873379A (en) | A kind of sewage disposal method for optimally controlling based on iteration ADP algorithms | |
| CN108549234A (en) | A kind of multiobjective optimization control method based on dynamic variate | |
| CN108439580B (en) | Dissolved oxygen concentration control system, method and device | |
| CN103425108A (en) | Water pollution prevention and control system and method based on quality-divided discharge and quality-divided treatment | |
| CN101364083A (en) | Sewage treatment control device and method and sewage treatment system using the same | |
| CN109948876A (en) | A kind of water shortage in north china municipal water Ecological Civilization Construction achievement evaluation method | |
| Erbe et al. | Integrated modelling as an analytical and optimisation tool for urban watershed management | |
| CN106495321A (en) | Biological tank process optimization and operation control system and its control method | |
| KR102311657B1 (en) | Smart management system for wastewater treatment | |
| CN108536106A (en) | A kind of aerating system dissolved oxygen based on Kalman filtering-extreme learning machine regulates and controls method online | |
| CN106200381B (en) | A method of according to the operation of processing water control by stages water factory | |
| Olsson | Instrumentation, control and automation in the water industry–state-of-the-art and new challenges | |
| CN106651032A (en) | Method for intelligently controlling ammoxidation process of SBR method by neural network | |
| CN114565154A (en) | Prediction method and optimization algorithm for carbon source adding amount of biochemical section of leachate | |
| CN203444305U (en) | Water pollution prevention and control system based on dual discharge and dual treatment | |
| JP2003245653A (en) | Operation supporting method for treatment system, operation supporting method for water treatment system and equipment therefor | |
| CN101833281A (en) | Control method for saving energy of aeration in sewage treatment | |
| CN105372995A (en) | Measurement and control method for sewage disposal system | |
| CN117023841A (en) | Water treatment system and method for intelligent water plant | |
| CN117196883A (en) | Sewage treatment decision optimization method and system based on artificial intelligence | |
| CN111180015A (en) | Management control method based on three-dimensional integrated model sewage treatment plant virtual reality | |
| Olsson et al. | Plant-wide control: dream, necessity or reality? |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |