Modular modeling system suitable for sewage treatment mathematical model and method thereof

Abstract

The invention discloses a modular modeling system and method suitable for a sewage treatment mathematical model, and the construction method divides a sewage treatment mathematical simulation process into three parts: a biochemical process matrix model used for storing and displaying the biochemical process matrix model; the data set is used for storing and displaying the sewage treatment process; and the model solution module is used for combining the biochemical process matrix model and the data set, and storing and displaying the combined biochemical process matrix model and data set. According to the method, the use cost and the learning threshold of the sewage treatment mathematical model can be reduced, the popularity and reliability of the model and the reusability of data are improved, implicit errors are reduced, the modeling efficiency is improved, and the method can be widely applied to the technical field of data processing.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a modular modeling system and method applicable to sewage treatment mathematical models. Background Art

[0002] Due to the complexity of wastewater treatment processes, researchers often rely on mathematical models to explain mechanisms, predict outcomes, optimize designs, and achieve cost savings. The activated sludge models (ASMs), proposed by the International Water Quality Association (IWA) in 1987, are a classic example of modern wastewater treatment mathematical models. Using a matrix approach, ASMs describe the various biochemical reactions involved in wastewater treatment, providing theoretical support for the design, control, and operation of wastewater treatment plants.

[0003] With the rapid development of matrix models, their structures have become increasingly complex, with an increasing number of components and parameters, and increasingly complex stoichiometric coefficients and biochemical reaction rate expressions. Furthermore, due to the complexity of wastewater treatment processes, nearly every practical process requires reconstruction from scratch, encompassing data collection, model structure selection, and model solution. This has led to increasing costs for constructing and learning modern wastewater treatment mathematical models, making model and data reuse difficult, reducing model adoption and development efficiency. Furthermore, complex model components, parameters, stoichiometric coefficients, and reaction rate expressions can also lead to numerous hidden errors that are difficult to detect. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide a modular modeling system and method suitable for sewage treatment mathematical models, which can reduce the use cost and learning threshold of sewage treatment mathematical models and improve the reusability of models and data.

[0005] To achieve the above objectives, one aspect of an embodiment of the present application provides a modular modeling system suitable for a sewage treatment mathematical model, comprising:

[0006] Biochemical process matrix model, used to store and display biochemical matrix models;

[0007] Datasets for storing and displaying the sewage treatment process;

[0008] The model solution module is used to combine the biochemical process matrix model and the data set, and store and display the combined biochemical process matrix model and the data set.

[0009] In some embodiments, the biochemical process matrix model includes a component module, a parameter module and a matrix module, the component module is used to store biochemical component information, the parameter module is used to store biochemical parameter information, and the matrix module is used to store biochemical matrix model information, wherein each column of the biochemical matrix model is a biochemical component, each row of the biochemical matrix model is a biochemical reaction process, and the corresponding values ​​of each row and column of the biochemical matrix model are chemical quantitative coefficient expressions corresponding to the biochemical component and the biochemical reaction process.

[0010] In some embodiments, the component module includes biochemical component expressions, the parameter module includes biochemical parameter expressions, the matrix module includes the biochemical component expressions and the biochemical parameter expressions, the biochemical component expressions in the matrix module are the same as the biochemical component expressions in the component module and the order corresponds, and the biochemical parameter expressions in the matrix module are the same as the biochemical parameter expressions in the parameter module and the order corresponds.

[0011] In some embodiments, the data set includes a unit module, an indicator module, a container module, a measurement module, an inflow module, a flow module, an association module and a chart module. The unit module is used to store various measurement units of the sewage treatment process, the indicator module is used to store relevant pollutant indicator information of the sewage treatment process, the container module is used to store relevant reaction container information of the sewage treatment process, the measurement module is used to store the measured information of pollution indicators in each reaction container, the inflow module is used to store the measured information of each pollution indicator in each inflow, the flow module is used to store the measured information of each flow, the association module is used to store the connection relationship between each reaction container of the sewage treatment process, and the chart module is used to store flow chart json information.

[0012] In some embodiments, the indicator module and the inflow module both include pollutant indicator expressions, the pollutant indicator expressions in the indicator module are the same as the pollutant indicator expressions in the inflow module and the order corresponds, the container module, the measurement module and the association module all include reaction container names, the reaction container name in the container module is the same as the reaction container name in the measurement module and the association module, the inflow module and the association module also include inflow names, the inflow name in the inflow module is the same as the inflow name in the association module, the flow module and the association module both include flow names, the flow name in the flow module is the same as the flow name in the association module.

[0013] In some embodiments, the model solution module includes a variable module, a transformation module, a weight module, a target value module and an activation module. The variable module is used to store parameter information during model solving, the transformation module is used to store the transformation relationship between the component module in the biochemical process matrix model and the indicator module in the data set, the weight module is used to store the weight ratio of the indicator module in the data set in the objective function, the target value module is used to store additional pollutant indicators that need to be converted, and the activation module is used to store whether the reaction container in the data set participates in the biochemical reaction process in the biochemical process matrix model.

[0014] In some embodiments, the variable module includes a biochemical component expression, a biochemical parameter expression, an inflow name, a flow name, and a reaction container name; the conversion module includes the biochemical component expression and a pollutant index expression; the target value module includes the pollutant index expression; the weight module includes the pollutant index expression and the reaction container name; the activation module includes the reaction container name; the biochemical component expressions in the variable module and the conversion module are the same as the biochemical component expressions of the component module in the biochemical process matrix model and the order corresponds; the biochemical parameter expressions in the variable module are the same as the biochemical process matrix model. The biochemical parameter expressions of the parameter module in the matrix model are the same and correspond in order, the inflow name in the variable module is the same as the inflow name of the inflow module in the dataset and corresponds in order, the flow name in the variable module is the same as the flow name of the flow module in the dataset and corresponds in order, the reaction container name in the variable module, the weight module and the activation module is the same as the reaction container name of the container module in the dataset and corresponds in order, and the pollutant index expression in the conversion module and the weight module is the same as the pollutant index expression in the index module in the dataset and corresponds in order.

[0015] In some embodiments, the biochemical process matrix model, the data set, and the model solution module are all stored in a preset database in a preset data format, and the preset data format includes at least one or a combination of xlsx format, json format, and xml format.

[0016] In some embodiments, the biochemical process matrix model, the data set, and the model solution module are all displayed through an HTML front-end page.

[0017] To achieve the above objectives, another aspect of the present invention provides a modular modeling method for a modular modeling system of a sewage treatment mathematical model, comprising the following steps:

[0018] The biochemical process matrix model is stored and displayed to obtain the biochemical process matrix model;

[0019] The sewage treatment process is stored and displayed to obtain a data set;

[0020] The biochemical process matrix model and the data set are combined, and the combined biochemical process matrix model and the data set are stored and displayed to obtain a model solution module.

[0021] The beneficial effects of the present invention are: the modular modeling system and method suitable for sewage treatment mathematical models of the present invention divide the sewage treatment mathematical simulation process into three parts, including a biochemical process matrix model for storing and displaying the biochemical process matrix model; a data set for storing and displaying the sewage treatment process; and a model solution module for combining the biochemical process matrix model and the data set, and storing and displaying the combined biochemical process matrix model and data set. Through the modular modeling method provided by the present invention, the user's use cost and learning threshold for the sewage treatment mathematical model can be reduced, the model's popularity, reliability and data reusability can be improved, and implicit errors can be reduced, thereby improving modeling efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following introduction is made to the drawings required for use in the embodiments of the present invention. It should be understood that the drawings introduced below are only for the convenience of clearly describing some embodiments of the technical solutions of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative work.

[0023] Figure 1 A schematic structural diagram of a modular modeling system for a sewage treatment mathematical model provided by an embodiment of the present invention;

[0024] Figure 2 A schematic diagram of the xlsx data format of the component module of the biochemical process matrix model provided in an embodiment of the present invention;

[0025] Figure 3 A schematic diagram of an HTML front-end webpage of a component module of a biochemical process matrix model provided in an embodiment of the present invention;

[0026] Figure 4 A schematic diagram of the xlsx data format of the parameter module of the biochemical process matrix model provided by an embodiment of the present invention;

[0027] Figure 5A schematic diagram of an HTML front-end webpage of a parameter module of a biochemical process matrix model provided by an embodiment of the present invention;

[0028] Figure 6 A schematic diagram of the xlsx data format of the matrix module of the biochemical process matrix model provided in an embodiment of the present invention;

[0029] Figure 7 A schematic diagram of an HTML front-end webpage of a matrix module of a biochemical process matrix model provided by an embodiment of the present invention;

[0030] Figure 8 A schematic diagram of the xlsx data format of the Unit module of the data set provided in an embodiment of the present invention;

[0031] Figure 9 A schematic diagram of an HTML front-end webpage of a unit module of a data set provided in an embodiment of the present invention;

[0032] Figure 10 A schematic diagram of the xlsx data format of the Target module of the data set provided in an embodiment of the present invention;

[0033] Figure 11 A schematic diagram of the HTML front-end webpage of the Target module of the dataset provided in an embodiment of the present invention;

[0034] Figure 12 A schematic diagram of the xlsx data format of the container (Tank) module of the data set provided in an embodiment of the present invention;

[0035] Figure 13 A schematic diagram of an HTML front-end webpage of a container (Tank) module of a data set provided in an embodiment of the present invention;

[0036] Figure 14 A schematic diagram of the xlsx data format of the measured module of the data set provided in an embodiment of the present invention;

[0037] Figure 15 A schematic diagram of the HTML front-end webpage of the measured module of the data set provided in an embodiment of the present invention;

[0038] Figure 16 A schematic diagram of the xlsx data format of the inflow module of the data set provided in an embodiment of the present invention;

[0039] Figure 17 A schematic diagram of an HTML front-end webpage of an inflow module of a dataset provided in an embodiment of the present invention;

[0040] Figure 18 A schematic diagram of the xlsx data format of the flow module of the data set provided in an embodiment of the present invention;

[0041] Figure 19 A schematic diagram of the HTML front-end webpage of the flow module of the data set provided in an embodiment of the present invention;

[0042] Figure 20 A schematic diagram of the xlsx data format of the (Connection) module of the dataset provided in an embodiment of the present invention;

[0043] Figure 21 A schematic diagram of the HTML front-end webpage of the (Connection) module of the dataset provided in an embodiment of the present invention;

[0044] Figure 22 A schematic diagram of the xlsx data format of the graph module of the data set provided in an embodiment of the present invention;

[0045] Figure 23 A schematic diagram of an HTML front-end webpage of a graph module for a data set provided in an embodiment of the present invention;

[0046] Figure 24 A schematic diagram of the xlsx data format of the variable module of the model solution module provided in an embodiment of the present invention;

[0047] Figure 25 A schematic diagram of an HTML front-end webpage of a variable module of a model solution module provided in an embodiment of the present invention;

[0048] Figure 26 A schematic diagram of the xlsx data format of the conversion module of the model solution module provided in an embodiment of the present invention;

[0049] Figure 27 A schematic diagram of an HTML front-end webpage of a conversion module of a model solution module provided in an embodiment of the present invention;

[0050] Figure 28 A schematic diagram of the xlsx data format of the target value (Target) module of the model solution module provided in an embodiment of the present invention;

[0051] Figure 29 A schematic diagram of an HTML front-end webpage of the target value (Target) module of the model solution module provided in an embodiment of the present invention;

[0052] Figure 30A schematic diagram of the xlsx data format of the weight module of the model solution module provided in an embodiment of the present invention;

[0053] Figure 31 A schematic diagram of an HTML front-end webpage of the weight module of the model solution module provided in an embodiment of the present invention;

[0054] Figure 32 A schematic diagram of the xlsx data format of the Activator module of the model solution module provided in an embodiment of the present invention;

[0055] Figure 33 A schematic diagram of an HTML front-end webpage of an activation (Activator) module of a model solution module provided in an embodiment of the present invention;

[0056] Figure 34 A flowchart of the steps of a modular modeling method of a modular modeling system suitable for a sewage treatment mathematical model provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. They are merely examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the appended claims.

[0058] It will be understood that the terms "first", "second", etc. used in this application may be used herein to describe various concepts, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0059] The terms "at least one", "plurality", "each", "any", etc. used in this application include "at least one", "two" or more, "plurality" or "each", "any" or "any one", "each" or "any one" as used herein.

[0060] Due to the complexity of wastewater treatment processes, researchers often rely on mathematical models to explain mechanisms, predict outcomes, optimize designs, and achieve cost savings. The activated sludge models (ASMs), proposed by the International Water Quality Association (IWA) in 1987, are a classic example of modern wastewater treatment mathematical models. Using a matrix approach, ASMs describe the various biochemical reactions involved in wastewater treatment, providing theoretical support for the design, control, and operation of wastewater treatment plants.

[0061] With the rapid development of matrix models, their structures have become increasingly complex, with an increasing number of components and parameters, and increasingly complex stoichiometric coefficients and biochemical reaction rate expressions. Furthermore, due to the complexity of wastewater treatment processes, nearly every practical process requires reconstruction from scratch, encompassing data collection, model structure selection, and model solution. This has led to increasing costs for constructing and learning modern wastewater treatment mathematical models, making model and data reuse difficult, reducing model adoption and development efficiency. Furthermore, complex model components, parameters, stoichiometric coefficients, and reaction rate expressions can also lead to numerous hidden errors that are difficult to detect.

[0062] To this end, an embodiment of the present invention proposes a modular modeling system for sewage treatment mathematical models. This system divides the sewage treatment mathematical simulation process into three parts: a biochemical process matrix model for storing and displaying the biochemical process matrix model in a format; a dataset for storing and displaying the sewage treatment process; and a model solution module for combining the biochemical process matrix model and the dataset and storing and displaying the combined biochemical process matrix model and dataset. The modular modeling method provided by the present invention can reduce the user's cost and learning threshold for sewage treatment mathematical models, improve the model's popularity, reliability, and data reusability, reduce implicit errors, and improve modeling efficiency. The system can be applied to scenarios such as sewage treatment management and optimization, urban wastewater treatment, and water resources management, but is not limited to these.

[0063] Reference Figure 1 , Figure 1 This is a schematic diagram of the structure of a modular modeling system for a sewage treatment mathematical model provided by an embodiment of the present invention. The embodiment of the present invention provides a modular modeling system for a sewage treatment mathematical model, including:

[0064] Biochemical process matrix model, used to store and display biochemical matrix models;

[0065] Datasets for storing and displaying the sewage treatment process;

[0066] The model solution module is used to combine the biochemical process matrix model and the data set, and store and display the combined biochemical process matrix model and data set.

[0067] Further as an optional implementation, the biochemical process matrix model includes a component module, a parameter module and a matrix module, the component module is used to store biochemical component information, the parameter module is used to store biochemical parameter information, and the matrix module is used to store biochemical matrix model information, wherein each column of the biochemical matrix model is a biochemical component, each row of the biochemical matrix model is a biochemical reaction process, and the corresponding values ​​of each row and column of the biochemical matrix model are chemical quantitative coefficient expressions of the corresponding biochemical components and the corresponding biochemical reaction processes.

[0068] Specifically, the reusable BioModel is used to store and display biochemical matrix models. It is divided into three modules: the Component module, the Parameter module, and the Matrix module. The Component module defines six biochemical components; the Parameter module defines nine biochemical parameters; and the Matrix module defines three biochemical processes.

[0069] Further as an optional embodiment, the component module includes biochemical component expressions, the parameter module includes biochemical parameter expressions, the matrix module includes biochemical component expressions and biochemical parameter expressions, the biochemical component expressions in the matrix module are the same as the biochemical component expressions in the component module and the order corresponds, and the biochemical parameter expressions in the matrix module are the same as the biochemical parameter expressions in the parameter module and the order corresponds.

[0070] In some optional embodiments, such as Figure 2 The following is a schematic diagram of the xlsx data format of the component module of the biochemical process matrix model. Figure 3 The figure shows a schematic diagram of the HTML front-end webpage of the component module of the biochemical process matrix model. The component module is used to store specific information of the biochemical component, including four columns: 1) Symbol: the expression of the biochemical component; 2) Unit: the unit of the biochemical component; 3) Name: the name of the biochemical component; and 4) Description: the description of the biochemical component.

[0071] like Figure 4 The following is a schematic diagram of the xlsx data format of the parameter module of the biochemical process matrix model. Figure 5The figure shows a schematic diagram of the HTML front-end web page of the parameter module of the biochemical process matrix model. The parameter module is used to store specific information of the biochemical parameters, including 7 columns: 1) Symbol: expression of the biochemical parameter; 2) Unit: unit of the biochemical parameter; 3) DefaultValue: default value of the biochemical parameter; 4) LowerBound: lower limit of the value of the biochemical parameter; 5) UpperBound: upper limit of the value of the biochemical parameter; 6) Name: name of the biochemical parameter and 7) Description: description of the biochemical parameter.

[0072] like Figure 6 The following is a schematic diagram of the xlsx data format of the matrix module of the biochemical process matrix model. Figure 7 The figure shows the schematic diagram of the HTML front-end web page of the matrix module of the biochemical process matrix model. The matrix module is used to store the specific information of the biochemical matrix model. A column of the matrix represents a biochemical component, a row of the matrix represents a biochemical process, and a cell of the matrix is ​​the chemical coefficient expression of the corresponding biochemical component (column) and the corresponding biochemical reaction process (row). The last column of the matrix is ​​the biochemical rate expression of the biochemical reaction process, specifically including: 1) The first column is Name: the name of the biochemical reaction process; 2) The last column is Rate: the biochemical reaction rate expression; 3) The middle columns: the expressions of each biochemical component. The writing and order of the expressions must be the same as the Symbol column in the component module.

[0073] Furthermore, each column in the biochemical process matrix model (BioModel) can be supplemented according to actual conditions, and the data in the biochemical process matrix model (BioModel) are all responsive, that is, the biochemical components and biochemical parameters contained in the matrix in the matrix module must be the same as the symbols defined in the component module and parameter module, and any change in any expression (specific expression and order) must be synchronized to the corresponding module at the same time.

[0074] Further as an optional implementation, the data set includes a unit module, an indicator module, a container module, a measurement module, an inflow module, a flow module, an association module and a chart module. The unit module is used to store various measurement units of the sewage treatment process, the indicator module is used to store relevant pollutant indicator information of the sewage treatment process, the container module is used to store relevant reaction container information of the sewage treatment process, the measurement module is used to store the measured information of pollution indicators in each reaction container, the inflow module is used to store the measured information of each pollution indicator in each inflow, the flow module is used to store the measured information of each flow, the association module is used to store the connection relationship between each reaction container of the sewage treatment process, and the chart module is used to store flow chart json information.

[0075] Specifically, the reusable DataSet is used to store and display data based on the actual conditions of the sewage treatment process. It is divided into eight modules: the Unit module, the Target module, the Tank module, the Measured module, the Inflow module, the Flow module, the Connection module, and the Graph module. The Unit module defines three units; the Target module defines six pollutant indicators; the Tank module defines two reaction vessels; the Measured module stores the measured data for each pollutant indicator in each reaction vessel; the Inflow module defines the measured data for each pollutant indicator in each inflow; the Flow module defines the measured data for each flow; the Connection module defines how these reaction vessels are connected; and the Graph module stores the flow chart JSON and drawing information.

[0076] Further as an optional implementation, the indicator module and the inflow module both include pollutant indicator expressions, the pollutant indicator expressions in the indicator module are the same as the pollutant indicator expressions in the inflow module and the order corresponds, the container module, the measurement module and the association module all include reaction container names, the reaction container name in the container module is the same as the reaction container name in the measurement module and the association module, the inflow module and the association module also include inflow names, the inflow name in the inflow module is the same as the inflow name in the association module, the flow module and the association module both include flow names, the flow name in the flow module is the same as the flow name in the association module.

[0077] In some optional embodiments, such as Figure 8 The following is a schematic diagram of the xlsx data format of the Unit module of the dataset: Figure 9The figure shows the HTML front-end webpage diagram of the Unit module of the dataset. The Unit module is used to store various measurement units of the sewage treatment process, including three columns: 1) Time: time units, including day, hour, minute and second; 2) Volume: volume units, including m3; and 3) Flow: flow units, including m3 / d.

[0078] like Figure 10 The following is a schematic diagram of the xlsx data format of the indicator (Target) module of the data set, as shown in Figure 11 The figure shows the HTML front-end webpage diagram of the target module of the dataset. The target module is used to store specific information about pollutant indicators related to the sewage treatment process, including four columns: 1) Symbol: pollutant indicator expression; 2) Unit: unit of pollutant indicator; 3) Name: name of pollutant indicator; and 4) Description: description of pollutant indicator.

[0079] like Figure 12 The following is a schematic diagram of the xlsx data format of the container (Tank) module of the data set, as shown in Figure 13 The figure shows the schematic diagram of the html front-end web page of the container (Tank) module of the dataset. The container (Tank) module is used to store specific information of the reaction vessel related to the sewage treatment process, including: 1) Name: the name of the reaction vessel; 2) Type: the type of reaction vessel, including CSTR, Point Settling and MBR, etc.; 3) BioCalculated: whether the reaction vessel participates in the biochemical reaction calculation, including True and False; 4) Volume: the volume of the reaction vessel; 5) ConstantVolume: whether the reaction vessel is a constant volume, including True and False and 6) SettlingFactor: the sedimentation ratio of the Point Settling type reaction vessel, with a value range of [0,1].

[0080] like Figure 14 The following is a schematic diagram of the xlsx data format of the measured module of the data set. Figure 15The figure shows a schematic diagram of the html front-end web page of the measured (Measured) module of the data set. The measured (Measured) module is used to store the measured information of each pollution indicator in each reaction container, specifically including: 1) the first row stores the name of each reaction container, which is the same as the Name in the container (Tank) module; 2) the second row stores the expression of each pollution indicator, which is the same as the Symbol in the indicator (Target) module; 3) the third to the last row are the measured values ​​of each pollution indicator in each reaction container in chronological order; 4) the name of each reaction container in the first row will be repeated according to the pollutant indicator, and a separator column needs to be inserted between each reaction container. The first row of this column is "Tank", the second row is "Target", the third row is "0", and the fourth to the last row are time (type is numeric).

[0081] like Figure 16 The following is a schematic diagram of the xlsx data format of the Inflow module of the dataset: Figure 17 The figure shows the schematic diagram of the HTML front-end web page of the inflow module of the dataset. The inflow module is used to store the measured information of each pollution indicator in each inflow, including: 1) the first row stores the name of each inflow; 2) the second row stores the expression of each pollution indicator, which is the same as the Symbol in the indicator (Target) module; 3) the third to the last row are the measured values ​​of each pollution indicator in each reaction container in chronological order; 4) each inflow name in the first row will be repeated according to the pollutant indicator, and a separator column needs to be inserted between each inflow. The first row of this column is "Inflow", the second row is "Target", the third row is "0", and the fourth to the last row are time (type is numeric).

[0082] like Figure 18 The following is a schematic diagram of the xlsx data format of the flow module of the data set. Figure 19 The figure shows the schematic diagram of the HTML front-end webpage of the flow module of the dataset. The flow module is used to store the measured information of each flow, including: 1) the first row stores the name of each flow; 2) the second to the last row are the measured values ​​of each flow in chronological order; 3) a separator column needs to be inserted between each flow, the first row of this column is "Flow", the second row is "0", and the third to the last row are time (type is numeric).

[0083] like Figure 20 The following is a schematic diagram of the xlsx data format of the (Connection) module of the dataset, as shown in Figure 21The figure shows the schematic diagram of the HTML front-end web page of the (Connection) module of the dataset. The (Connection) module is used to store the connection relationship of each reaction container in the sewage treatment process, and specifically includes 3 columns: 1) From: the outflow end of the connection relationship. The values ​​of this column include Inflow and Tank, which are the same as the expression of the inflow name defined in the inflow (Inflow) module and the same as the Name in the container (Tank) module (when the Tank type is Point Settling, the Name must be added with the suffixes "_Blanket" and "_Outlet"); 2) Flow: the flow of the connection relationship. The values ​​of this column are the same as the expression of the flow name defined in the flow (Flow) module; 3) Into: the inflow end of the connection relationship. The values ​​of this column include Tank, "Wasted" and "Outflow", which are the same as the Name in the container (Tank) module (when the Tank type is Point Settling, the Name must be added with the suffixes "_Blanket" and "_Outlet").

[0084] like Figure 22 This is a diagram of the xlsx data format of the graph module of the data set, such as Figure 23 This is a schematic diagram of the HTML front-end web page of the graph module of the dataset. The graph module is used to store the flowchart json information of the dataset. It specifically includes 1 column: the graph column (the first column). The first row stores the flowchart json information, which is used for drawing on the front-end of the web module.

[0085] Furthermore, each column in the dataset can be supplemented according to actual conditions, and the data in the dataset are all responsive, that is, the Symbol defined in the Target module must be the same as the pollutant index expression in the Measured module and the Inflow module, the Name defined in the Tank module must be the same as the expression of the reaction vessel name in the Measured module and the Connection module, the expression defined in the Inflow module must be the same as the expression of the inflow name in the Connection module, and the expression defined in the Flow module must be the same as the expression of the flow name in the Connection module. Any change in any expression (specific expression and order) must be synchronized to the corresponding module at the same time.

[0086] Further as an optional implementation, the model solution module includes a variable module, a transformation module, a weight module, a target value module and an activation module. The variable module is used to store parameter information when solving the model. The transformation module is used to store the transformation relationship between the component module in the biochemical process matrix model and the indicator module in the data set. The weight module is used to store the weight ratio of the indicator module in the data set in the objective function. The target value module is used to store additional pollutant indicators that need to be converted. The activation module is used to store whether the reaction vessel in the data set participates in the biochemical reaction process in the biochemical process matrix model.

[0087] In some optional embodiments, the model solution module (Solution) is used to combine, store, and display a specific version of a biochemical process matrix model (BioModel) with a specific version of a wastewater treatment process dataset (DataSet). It is divided into five modules: a variable module, a conversion module, a target module, a weight module, and an activator module. The variable module is used to store information related to all parameters required for model solution (a total of 39 parameters). The conversion module defines the conversion relationship between the six component modules in the biochemical process matrix model and the six target modules in the dataset and one additional target in the model solution module. TCOD is an additional target in the model solution module and is converted as follows: TCOD = 1×S_O2 + 1×S_S + 1×S_I + 1×X_P + 1×X_S + 1×S_OHO. This step is the key to combining the biochemical process matrix model and the data set; the target value (Target) module defines additional Targets to supplement the additional pollutant indicators that need attention. Only one additional pollutant indicator (TCOD) is defined here, and the additional pollutant indicator is converted to the indicator (Target) in the data set in the following manner: TCOD = 1×S_O2+1×S_S+1×S_I+1×X_P+1×X_S+1×S_OHO; the weight (Weight) module is used to store the weight ratio of the indicator (Target) module in the data set in the objective function during model evaluation. In the embodiment of the present invention, the weight ratio is set to 1, that is, the weights of all pollutant indicators in all reaction containers are equal. When performing model evaluation, these values ​​have the same impact on the evaluation target; the activation (Activator) module is used to store whether the reaction container in the data set participates in the biochemical reaction process in the biochemical process matrix model. In the embodiment of the present invention, it is set that all reaction containers participate in all biochemical reaction processes.

[0088] Further as an optional embodiment, the variable module includes a biochemical component expression, a biochemical parameter expression, an inflow name, a flow name and a reaction container name, the conversion module includes a biochemical component expression and a pollutant index expression, the target value module includes a pollutant index expression, the weight module includes a pollutant index expression and a reaction container name, the activation module includes a reaction container name, the biochemical component expressions in the variable module and the conversion module are the same as the biochemical component expressions of the component module in the biochemical process matrix model and the order corresponds, the biochemical parameter expressions in the variable module are the same as the biochemical parameter expressions of the parameter module in the biochemical process matrix model and the order corresponds, the inflow name in the variable module is the same as the inflow name of the inflow module in the dataset and the order corresponds, the flow name in the variable module is the same as the flow name of the flow module in the dataset and the order corresponds, the reaction container name in the variable module, the weight module and the activation module is the same as the reaction container name of the container module in the dataset and the order corresponds, the pollutant index expression in the conversion module and the weight module is the same as the pollutant index expression of the index module in the dataset and the order corresponds.

[0089] In some optional embodiments, such as Figure 24 The following is a schematic diagram of the xlsx data format of the variable module of the model solution module, as shown in Figure 25The figure shows the HTML front-end webpage diagram of the variable module of the model solution module. The variable module is used to store the relevant information of all parameters required for model solution, which specifically includes 8 columns: 1) Variable: the expression of each parameter, divided into four parts. The first part (starting from the first row) is the same as the Symbol (order and expression) of the parameter module in the biochemical process matrix model, indicating the actual value of the parameter of the biochemical matrix model; the second part is the same as the Symbol expression of the component module in the biochemical process matrix model. The first part is fixed as "Volume", which represents the volume of each reaction vessel and is repeated for each reaction vessel (Tank) and inflow (Inflow) in the data set; the fourth part is fixed as "Flow", which represents the initial value of each flow and is repeated for each flow (Flow) in the data set; 2) Tank: The expression of each reaction vessel, inflow and flow, divided into five parts, one-to-one corresponding to the above Variable columns, the first part (starting from the first row, corresponding to the above Variable The first part of the column is blank; the second part is the same as the Name expression of the container (Tank) module in the data set (corresponding to the second part of the above Variable column), which is repeated according to each Component in the biochemical process matrix model; the third part is the same as the expression of the inflow name defined in the inflow (Inflow) module in the data set (corresponding to the second part of the above Variable column), which is repeated according to each Component in the biochemical process matrix model; the fourth part is the same as the Name expression of the container (Tank) module in the data (corresponding to the third part of the above Variable column); the fifth part is the same as the expression of the flow name defined in the flow (Flow) module in the data set (corresponding to the fourth part of the above Variable column); 3) Value: the actual value of the parameter during calculation; 4) Evaluation: whether the parameter participates in the model evaluation calculation, including True and False; 5) InitialValue: the initial value of the parameter when participating in the model evaluation; 6) DecimalPoint: the number of hourly points of the parameter (integer); 7) LowerBound: the lower limit of the parameter value; 8) UpperBound: the upper limit of the parameter value.

[0090] like Figure 26 The following is a schematic diagram of the xlsx data format of the conversion module of the model solution module. Figure 27This is a schematic diagram of the HTML front-end web page of the conversion module of the model solution module. The conversion module is used to store the conversion relationship between the Component in the biochemical process matrix model and the Target in the data set, specifically including: 1) The first column starting from the second row is the expression of each pollutant indicator. The writing method and order of the expression must be the same as the Symbol column in the indicator (Target) module in the data set; 2) Starting from the second column, the column name is the expression of each biochemical component. The writing method and order of the expression must be the same as the Symbol column in the component (Component) module in the biochemical process matrix model; 3) The value of each cell represents the conversion value of the Component in the biochemical process matrix model and the Target in the data set, that is, the value of the Component multiplied by each value in a row in sequence and the sum is the value of the Target corresponding to the row.

[0091] like Figure 28 The following is a schematic diagram of the xlsx data format of the target value (Target) module of the model solution module, as shown in Figure 29 The figure shows the html front-end webpage diagram of the target value (Target) module of the model solution module. The target value (Target) module is used to store additional pollutant indicators that need to be converted, including: 1) Symbol; the expression of the additional pollutant indicator cannot be repeated with the Symbol of the indicator (Target) module in the dataset; 2) Unit: the unit of the additional pollutant indicator; 3) Name: the name of the additional pollutant indicator; 4) Description: the description of the additional pollutant indicator; 5) the subsequent columns correspond to the Symbol of the indicator (Target) module in the dataset, and the conversion calculation method logic is the same as that of the conversion (Conversion) module.

[0092] like Figure 30 The following is a schematic diagram of the xlsx data format of the weight module of the model solution module. Figure 31 The figure shows a schematic diagram of the HTML front-end web page of the Weight module of the model solution module. The Weight module is used to store the weight ratio of the Target module in the dataset in the objective function during model evaluation, specifically including: 1) The first column starting from the second row is the expression of each pollutant indicator. The writing and order of the expression must be the same as the Symbol column in the Target module in the dataset; 2) Starting from the second column, the column name is the name of each reaction container. The writing and order of the name must be the same as the Name column in the Tank module in the dataset; 3) The value of each cell represents the weight value of the corresponding pollutant indicator in the corresponding reaction container.

[0093] like Figure 32 The following is a schematic diagram of the xlsx data format of the Activator module of the model solution module. Figure 33 The figure shows a schematic diagram of the HTML front-end web page of the Activator module of the model solution module. The Activator module is used to store whether the reaction vessels in the data set participate in the biochemical reaction process in the biochemical process matrix model, specifically including: 1) The first column starting from the second row is the name of the biochemical reaction process. The writing method and order of the name must be the same as the Name column in the Matrix module in the biochemical process matrix model; 2) Starting from the second column, the column name is the name of each reaction vessel. The writing method and order of the name must be the same as the Name column in the Tank module in the data set; 3) The value of each cell indicates whether the corresponding reaction vessel participates in the corresponding biochemical reaction, including True and False.

[0094] Furthermore, the columns in the model solution module can be supplemented according to actual conditions, and the data in the model solution module are all responsive, that is, the expressions of Parameter and Component in the Variable column of the Variable module must be the same as those in the biochemical process matrix model (specific expressions and order); the names and expressions of Tank, Inflow, and Flow in the Tank column of the Variable module must be the same as those in the dataset (specific names and order); the expressions of Component and Target in the Conversion module must be the same as those in the biochemical process matrix model and the Target in the dataset (specific expressions and order); the expression of Target in the Target module must be the same as the Target in the dataset (specific expressions and order); the expressions of Tank and Target in the Weight module must be the same as those in the dataset (specific expressions and order); the names of Tank and biochemical reaction in the Activator module must be the same as those in the biochemical process matrix model and the Tank in the dataset (specific names and order).

[0095] As a further optional implementation, the biochemical process matrix model, data set and model solution module are all stored in a preset database in a preset data format, and the preset data format includes at least one or a combination of xlsx format, json format and xml format.

[0096] For example, the biochemical process matrix model can be stored in the database in json format, and the specific format is directly converted from the data formats such as xlsx format, json format or xml format described by the biochemical process matrix model; the data set can be stored in the database in json format, and the specific format is directly converted from the data formats such as xlsx format, json format or xml format described by the data set; the model solution module can be stored in the database in json format, and the specific format is directly converted from the data formats such as xlsx format, json format or xml format described by the model solution module.

[0097] As a further optional implementation, the biochemical process matrix model, data set and model solution module are all displayed through an HTML front-end page.

[0098] Specifically, the biochemical process matrix model can be displayed through an HTML front-end web page. The content displayed on the page is consistent with the three pages of the xlsx file described by the biochemical process matrix model. Figure 3 、 Figure 5 as well as Figure 7 As shown; the dataset can be displayed through the HTML front-end web page, and the content displayed on the page is consistent with the 7 pages of the xlsx file described in the dataset, as shown in the following example. Figure 9 、 Figure 11 、 Figure 13 、 Figure 15 、 Figure 17 、 Figure 19 、 Figure 21 as well as Figure 23 As shown; the model solution module can be displayed through the HTML front-end web page, and the content displayed on the page is consistent with the 5 pages of the xlsx file described by the model solution module, as shown in the following example. Figure 25 、 Figure 27 、 Figure 29 、 Figure 31 as well as Figure 33 shown.

[0099] Furthermore, the biochemical process matrix model, data set, and specific data of the model solution module can be modified and saved and published as multiple versions.

[0100] The above describes a modular modeling system suitable for sewage treatment mathematical models according to an embodiment of the present invention. It will be appreciated that the present embodiment includes a model data storage format, a method for combining a biochemical process matrix model and a data set, and a model solution module. The modular modeling method provided by the present embodiment can provide users with a convenient, unified, and standardized modeling approach, reducing the cost and learning threshold for using sewage treatment mathematical models, improving the model's popularity, reliability, and data reusability, reducing potential errors, and improving modeling efficiency.

[0101] Reference Figure 34 The embodiment of the present invention further provides a modular modeling method for a modular modeling system of a sewage treatment mathematical model, comprising the following steps S101 to S103:

[0102] S101, storing and displaying the biochemical matrix model to obtain a biochemical process matrix model;

[0103] S102, storing and displaying the sewage treatment process to obtain a data set;

[0104] S103 , combining the biochemical process matrix model and the data set, and storing and displaying the combined biochemical process matrix model and data set to obtain a model solution module.

[0105] The contents of the above-mentioned embodiments of the modular modeling system applicable to sewage treatment mathematical models are all applicable to the embodiments of the modular modeling method of this modular modeling system applicable to sewage treatment mathematical models. The functions specifically implemented by the embodiments of the modular modeling method of this modular modeling system applicable to sewage treatment mathematical models are the same as those of the above-mentioned embodiments of the modular modeling system applicable to sewage treatment mathematical models, and the beneficial effects achieved are also the same as those achieved by the above-mentioned embodiments of the modular modeling system applicable to sewage treatment mathematical models.

[0106] An embodiment of the present invention further provides an electronic device comprising: a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for enabling communication between the processor and the memory. When the program is executed by the processor, the modular modeling system for the sewage treatment mathematical model described above is implemented. The electronic device can be any intelligent terminal, including a tablet computer and an in-vehicle computer.

[0107] An embodiment of the present invention also provides a storage medium, which is a computer-readable storage medium used for computer-readable storage. The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to realize the above-mentioned modular modeling system suitable for sewage treatment mathematical models.

[0108] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0109] In some optional embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the above-mentioned boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the present invention is provided in an exemplary manner for the purpose of providing a more comprehensive understanding of the technology. The disclosed method is not limited to the operation and logic flow presented herein. Optional embodiments are contemplated in which the order of the various operations is changed and the sub-operations described as a part of a larger operation are performed independently.

[0110] In addition, although the present invention is described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the above-mentioned functions and / or features can be integrated into a single physical device and / or software module, or one or more functions and / or features can be implemented in separate physical devices or software modules. It is also understood that a detailed discussion of the actual implementation of each module is not necessary for understanding the present invention. More specifically, given the properties, functions, and internal relationships of the various functional modules in the devices disclosed herein, the actual implementation of the module will be understood within the routine skills of an engineer. Therefore, a person skilled in the art can implement the present invention set forth in the claims using ordinary skills without undue experimentation. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0111] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the above methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program code.

[0112] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0113] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0114] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to the embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the claims and their equivalents.

[0115] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A modular modeling system for sewage treatment mathematical models, characterized in that: include: Biochemical process matrix model, used to store and display biochemical matrix models; Datasets for storing and displaying the sewage treatment process; The model solution module is used to combine the biochemical process matrix model and the data set, and store and display the combined biochemical process matrix model and the data set.

2. A modular modeling system suitable for sewage treatment mathematical models according to claim 1, characterized in that: The biochemical process matrix model includes a component module, a parameter module and a matrix module. The component module is used to store biochemical component information, the parameter module is used to store biochemical parameter information, and the matrix module is used to store biochemical matrix model information. Each column of the biochemical matrix model is a biochemical component, and each row of the biochemical matrix model is a biochemical reaction process. The corresponding values ​​of each row and column of the biochemical matrix model are chemical coefficient expressions corresponding to the biochemical component and the biochemical reaction process.

3. A modular modeling system suitable for sewage treatment mathematical models according to claim 2, characterized in that: The component module includes biochemical component expressions, the parameter module includes biochemical parameter expressions, and the matrix module includes the biochemical component expressions and the biochemical parameter expressions. The biochemical component expressions in the matrix module are the same as the biochemical component expressions in the component module and the order corresponds. The biochemical parameter expressions in the matrix module are the same as the biochemical parameter expressions in the parameter module and the order corresponds.

4. A modular modeling system for sewage treatment mathematical models according to claim 1, characterized in that: The data set includes a unit module, an indicator module, a container module, a measurement module, an inflow module, a flow module, an association module and a chart module. The unit module is used to store various measurement units of the sewage treatment process, the indicator module is used to store relevant pollutant indicator information of the sewage treatment process, the container module is used to store relevant reaction container information of the sewage treatment process, the measurement module is used to store the measured information of pollution indicators in each reaction container, the inflow module is used to store the measured information of each pollution indicator in each inflow, the flow module is used to store the measured information of each flow, the association module is used to store the connection relationship between each reaction container of the sewage treatment process, and the chart module is used to store flow chart json information.

5. A modular modeling system suitable for sewage treatment mathematical models according to claim 4, characterized in that: The indicator module and the inflow module both include pollutant indicator expressions, and the pollutant indicator expressions in the indicator module are the same as the pollutant indicator expressions in the inflow module and correspond in order. The container module, the measurement module and the association module all include reaction container names, and the reaction container name in the container module is the same as the reaction container name in the measurement module and the association module. The inflow module and the association module also both include inflow names, and the inflow name in the inflow module is the same as the inflow name in the association module. The flow module and the association module both include flow names, and the flow name in the flow module is the same as the flow name in the association module.

6. A modular modeling system for sewage treatment mathematical models according to claim 1, characterized in that: The model solution module includes a variable module, a transformation module, a weight module, a target value module and an activation module. The variable module is used to store parameter information during model solution. The transformation module is used to store the transformation relationship between the component module in the biochemical process matrix model and the indicator module in the data set. The weight module is used to store the weight ratio of the indicator module in the data set in the objective function. The target value module is used to store additional pollutant indicators that need to be converted. The activation module is used to store whether the reaction container in the data set participates in the biochemical reaction process in the biochemical process matrix model.

7. A modular modeling system for sewage treatment mathematical models according to claim 6, characterized in that: The variable module includes a biochemical component expression, a biochemical parameter expression, an inflow name, a flow name, and a reaction container name; the conversion module includes the biochemical component expression and a pollutant index expression; the target value module includes the pollutant index expression; the weight module includes the pollutant index expression and the reaction container name; the activation module includes the reaction container name; the biochemical component expressions in the variable module and the conversion module are the same as the biochemical component expressions of the component module in the biochemical process matrix model and the order corresponds; the biochemical parameter expressions in the variable module are the same as those in the biochemical process matrix model The biochemical parameter expressions in the parameter module are the same and in corresponding order, the inflow name in the variable module is the same as the inflow name in the inflow module in the dataset and in corresponding order, the flow name in the variable module is the same as the flow name in the flow module in the dataset and in corresponding order, the reaction container name in the variable module, the weight module and the activation module is the same as the reaction container name in the container module in the dataset and in corresponding order, the pollutant index expression in the conversion module and the weight module is the same as the pollutant index expression in the index module in the dataset and in corresponding order.

8. A modular modeling system for sewage treatment mathematical models according to claim 1, characterized in that: The biochemical process matrix model, the data set and the model solution module are all stored in a preset database in a preset data format, and the preset data format includes at least one of the xlsx format, the json format and the xml format or a combination thereof.

9. A modular modeling system for sewage treatment mathematical models according to claim 1, characterized in that: The biochemical process matrix model, the data set and the model solution module are all displayed through an HTML front-end page.

10. A modular modeling method for a modular modeling system for a sewage treatment mathematical model, for constructing a modular modeling system for a sewage treatment mathematical model as claimed in any one of claims 1 to 9, characterized in that: The following steps are involved: The biochemical matrix model is stored and displayed to obtain a biochemical process matrix model; The sewage treatment process is stored and displayed to obtain a data set; The biochemical process matrix model and the data set are combined, and the combined biochemical process matrix model and the data set are stored and displayed to obtain a model solution module.

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