A dynamic mathematical model establishing method, device, equipment and storage medium

Abstract

The application relates to intelligent decision-making technology and discloses a dynamic mathematical model establishment method, device and equipment and a computer readable storage medium, which comprises the following steps: querying a variable category in a controlled object model, extracting a global object of the controlled object model from the variable category, performing model definition on the controlled object model to obtain a target object model; identifying a model category of the target object model, querying an import form corresponding to the model category, performing form conversion on the target object model to obtain a form object model, and importing the form object model into an OPC server corresponding to the controlled object model; constructing variable information in the OPC server, constructing a tag number set corresponding to the variable information, and determining an association relationship between the form object model and the variable information; acquiring user end data corresponding to the OPC server, calculating server data of the user end data, and determining a dynamic mathematical model of the OPC server. The application is characterized by the method for establishing the dynamic mathematical model.

Description

Technical Field

[0001] This invention relates to the field of intelligent decision-making technology, and in particular to a method, apparatus, device, and computer-readable storage medium for establishing dynamic mathematical models. Background Technology

[0002] OPC, used for process control and OLE, is currently the common protocol for industrial data communication. Most DCS manufacturers have implemented their own OPC servers, and many industrial control software programs communicate with them as OPC clients. The development, testing, and simulation training of industrial control software require the cooperation of OPC servers, especially OPC servers that can respond to inputs according to specific mathematical models, so as to complete tasks more effectively. However, most of the OPC servers available on the market are custom-made products for DCS manufacturers, lacking OPC servers that can simulate real industrial environments during software development. Consequently, OPC servers cannot construct the dynamic characteristics of the service objects. Therefore, a method to build dynamic mathematical models is needed. Summary of the Invention

[0003] This invention provides a method, apparatus, device, and storage medium for establishing dynamic mathematical models, the main purpose of which is to provide a method for establishing dynamic mathematical models.

[0004] To achieve the above objectives, the present invention provides a method for establishing a dynamic mathematical model, comprising:

[0005] Obtain the controlled object model, query the variable categories in the controlled object model, extract the global object of the controlled object model from the variable categories, and perform standard format conversion on the controlled object model based on the global object to obtain the target object model;

[0006] Identify the model category of the target object model, query the import format corresponding to the model category, perform a format conversion on the target object model according to the import format to obtain a formal object model, and import the formal object model into the OPC server corresponding to the controlled object model;

[0007] In the OPC server, variable information is constructed, and based on the variable information, a set of reference numbers corresponding to the variable information is constructed. Based on the set of reference numbers, the association between the formal object model and the variable information is determined.

[0008] Obtain the client data corresponding to the OPC server, calculate the server data of the client data using the formal object model based on the association relationship, and determine the dynamic mathematical model of the OPC server based on the server data.

[0009] Optionally, extracting the global object of the controlled object model from the variable category includes:

[0010] Obtain the independent and dependent variables from the variable categories, and identify the variable information of the independent and dependent variables;

[0011] Based on the variable information, determine the variable relationship between the independent variable and the dependent variable;

[0012] Based on the variable relationships, the variable information, and the variable categories, a global object of the controlled object model is generated.

[0013] Optionally, determining the variable relationship between the independent variable and the dependent variable based on the variable information includes:

[0014] The relationship between the independent variable and the dependent variable is determined by the following formula:

[0015]

[0016] Among them, f j，k (s) represents the variable relationship between the j-th independent variable and the k-th dependent variable, and G represents the quantity of variable information. I T represents the linear value corresponding to the variable information. z s represents the vector mean corresponding to the variable information, T y2 T represents the mapping value corresponding to the dependent variable. y1 e represents the mapping value corresponding to the independent variable. -τs This indicates the variable dimensions corresponding to the independent and dependent variables.

[0017] Optionally, the step of defining the controlled object model based on the global object to obtain the target object model includes:

[0018] Identify the format corresponding to each object in the global object to obtain multiple object formats, and extract the format features of each format in the multiple object formats to obtain multiple format features;

[0019] The multiple format features are fused to obtain fused format features, and the step response matrix of the multiple object formats is constructed.

[0020] The step response matrix is ​​convolved to obtain the calculation result. Based on the calculation result and the fusion format features, the controlled object model is defined to obtain the target object model.

[0021] Optionally, the step of extracting the format features of each of the multiple object formats to obtain multiple format features includes:

[0022] The format features of each of the multiple object formats are extracted using the following formula:

[0023]

[0024] Where T(d) represents the format feature of each format, a represents the starting value among multiple object formats, and F i H represents the vector value for each format. average The matrix means represents the sum of the format vectors of multiple objects, and N represents the vector dimension coefficient corresponding to each format vector.

[0025] Optionally, determining the association between the formal object model and the variable information based on the set of reference numbers includes:

[0026] Extract the variable label for each variable from the variable information, and extract the model label for the formal object model;

[0027] Calculate the correlation degree between the variable label and the model label, and determine the association relationship between the formal object model and the variable information based on the correlation degree.

[0028] Optionally, calculating the correlation between the variable label and the model label includes:

[0029] The correlation between the variable labels and the model labels is calculated using the following formula:

[0030]

[0031] Where Y(x) represents the correlation between variable labels and model labels, i represents the initial value of the variable labels, P represents the total number of variable labels, and K... u This represents the mapping value corresponding to the u-th variable label. ω represents the mapping value corresponding to the model label, ω represents the correlation coefficient corresponding to the variable label, and u∈P represents the range to which the variable label belongs.

[0032] To address the above problems, the present invention also provides a dynamic mathematical model establishing device, the device comprising:

[0033] The model conversion module is used to obtain the controlled object model, query the variable categories in the controlled object model, extract the global object of the controlled object model from the variable categories, and define the model of the controlled object model according to the global object to obtain the target object model.

[0034] The model import module is used to identify the model category of the target object model, query the import form corresponding to the model category, perform form conversion on the target object model according to the import form to obtain a formal object model, and import the formal object model into the OPC server corresponding to the controlled object model.

[0035] The relationship determination module is used to construct variable information in the OPC server, construct a set of reference numbers corresponding to the variable information based on the variable information, and determine the association relationship between the formal object model and the variable information based on the set of reference numbers.

[0036] The dynamic model building module is used to obtain the client data corresponding to the OPC server, calculate the server data of the client data using the formal object model according to the association relationship, and determine the dynamic mathematical model of the OPC server based on the server data.

[0037] To address the above problems, the present invention also provides an electronic device, the electronic device comprising:

[0038] At least one processor; and,

[0039] A memory communicatively connected to the at least one processor; wherein,

[0040] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the dynamic mathematical model establishment method described above.

[0041] To address the aforementioned problems, the present invention also provides a computer-readable storage medium storing at least one computer program, which is executed by a processor in an electronic device to implement the dynamic mathematical model establishment method described above.

[0042] This invention, by acquiring a controlled object model and querying the variable categories within that model, can identify the variable types present in the controlled object model, thus ensuring the subsequent extraction of global objects from the controlled object model. Furthermore, by identifying the model category of the target object model and querying the corresponding import format, this invention ensures the subsequent formal conversion of the target object model using that import format. Specifically, this invention constructs variable information within the OPC server, facilitating the subsequent construction of corresponding tag sets based on this variable information. Additionally, by acquiring the user-side data corresponding to the OPC server, this invention facilitates the subsequent calculation of server data corresponding to the user-side data using the formal object model. Therefore, the dynamic mathematical model establishment method, apparatus, device, and storage medium provided by this invention enable the establishment of dynamic mathematical models. Attached Figure Description

[0043] Figure 1 A flowchart illustrating a method for establishing a dynamic mathematical model according to an embodiment of the present invention;

[0044] Figure 2 A functional block diagram of a dynamic mathematical model building device provided in an embodiment of the present invention;

[0045] Figure 3 This is a schematic diagram of the structure of an electronic device that implements the dynamic mathematical model establishment method according to an embodiment of the present invention.

[0046] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0047] The present disclosure will be further described below with reference to the embodiments shown in the accompanying drawings.

[0048] This application provides a method for establishing a dynamic mathematical model. In this application, the executing entity of the dynamic mathematical model establishment method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the dynamic mathematical model establishment method can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0049] Reference Figure 1 The diagram shown is a flowchart illustrating a dynamic mathematical model establishment method according to an embodiment of the present invention. In this embodiment, the dynamic mathematical model establishment method includes steps S1-S4:

[0050] S1. Obtain the controlled object model, query the variable categories in the controlled object model, extract the global object of the controlled object model from the variable categories, define the controlled object model according to the variable categories and the global object, and obtain the target object model.

[0051] This invention obtains the controlled object model and queries the variable categories in the controlled object model to understand which variable types exist in the controlled object model, thus providing a guarantee for the subsequent extraction of the global object of the controlled object model.

[0052] The controlled object model is a mathematical expression of the dynamic characteristics of the controlled object, that is, a mathematical function relationship between the output of the controlled object and the input. The variable category is the changing factors in the controlled object model, such as environmental factors and temperature factors. Furthermore, the controlled object model can be obtained by mechanism modeling, and the variable category in the controlled object model can be queried by the type() function.

[0053] This invention extracts the global object of the controlled object model from the variable category, thereby obtaining all variable objects in the controlled object model, which facilitates subsequent format conversion of the controlled object model. The global object is the corresponding global variable in the controlled object model.

[0054] As an embodiment of the present invention, the step of extracting the global object of the controlled object model from the variable category includes: obtaining the independent variables and dependent variables in the variable category, identifying the variable information of the independent variables and the dependent variables, determining the variable relationship between the independent variables and the dependent variables based on the variable information, and generating the global object of the controlled object model based on the variable relationship, the variable information and the variable category.

[0055] The independent variable is a factor or condition in the variable category that can be actively manipulated to cause subsequent changes. The dependent variable is a variable that changes with the independent variable. The variable information includes the name, description, and unit of the independent and dependent variables. The variable relationship is the dependency relationship between the independent and dependent variables, which shows the influence of the independent variable on the dependent variable.

[0056] Furthermore, the independent and dependent variables in the variable category can be obtained through the Math.random() function, the variable information of the independent and dependent variables can be identified through OCR text recognition technology, and the global object of the controlled object model can be generated through the constructor.

[0057] Furthermore, as an optional embodiment of the present invention, determining the variable relationship between the independent variable and the dependent variable based on the variable information includes:

[0058] The relationship between the independent variable and the dependent variable is determined by the following formula:

[0059]

[0060] Among them, f j，k (s) represents the variable relationship between the j-th independent variable and the k-th dependent variable, and G represents the quantity of variable information. I T represents the linear value corresponding to the variable information. z s represents the vector mean corresponding to the variable information, T y2 T represents the mapping value corresponding to the dependent variable. y1 e represents the mapping value corresponding to the independent variable. -τs This indicates the variable dimensions corresponding to the independent and dependent variables.

[0061] This invention defines a target object model by defining the controlled object model according to the variable category and the global object. The controlled object model can be defined as the model to be used. The target object model is the model obtained by defining the controlled object model according to the global object.

[0062] As an embodiment of the present invention, the step of defining the controlled object model based on the global object to obtain the target object model includes: identifying the format corresponding to each object in the global object to obtain multiple object formats; extracting the format features of each format in the multiple object formats to obtain multiple format features; performing feature fusion on the multiple format features to obtain fused format features; constructing the step response matrix of the multiple object formats; performing convolution calculation on the step response matrix to obtain calculation results; and defining the controlled object model based on the calculation results and the fused format features to obtain the target object model.

[0063] Wherein, the object format is the specification form corresponding to each object in the global object, the format feature is the symbol and mark of the object format, the fused format feature is the feature obtained by fusing multiple format features together, the step response matrix is ​​the matrix of the step response order corresponding to the multiple object formats, and the calculation result is the result obtained after convolution calculation of the step response matrix. Furthermore, the format corresponding to each object in the global object can be identified by a format recognition tool. The format recognition tool is compiled by Java language and can convert the format of the controlled object model by a format converter. The model definition of the controlled object model can be implemented by a state space model, specifically: X = QX1 + RU, Y = SX + TU, where X represents the changes inside the state space model after the calculation result and the fused format feature are input into the state space model, X1 represents the fused format feature, Q represents the state matrix, R represents the matrix corresponding to the fused format feature, U represents the controlled object model, Y represents the output result of the state space model, S represents the measurement matrix in the state space model, and T represents the zero matrix.

[0064] Furthermore, as an optional embodiment of the present invention, the step of extracting the format features of each of the plurality of object formats to obtain a plurality of format features includes:

[0065] The format features of each of the multiple object formats are extracted using the following formula:

[0066]

[0067] Where T(d) represents the format feature of each format, a represents the starting value among multiple object formats, and F i H represents the vector value for each format. average The matrix means represents the sum of the format vectors of multiple objects, and N represents the vector dimension coefficient corresponding to each format vector.

[0068] As an optional embodiment of the present invention, the step of performing feature fusion on the plurality of format features to obtain fused format features includes: obtaining a vector corresponding to each feature in the plurality of format features to obtain the plurality of feature vectors; calculating the similarity of the plurality of feature vectors; merging the plurality of feature vectors according to the similarity to obtain a feature merge vector; performing vector fusion on the feature merge vector to obtain a fused feature vector; and obtaining the fused format features according to the fused feature vector.

[0069] Wherein, the feature vector is the vector representation of the format feature, the similarity is the degree of similarity of the feature vectors, the similarity can be 0.1 or can be set according to the actual business scenario, the feature merge vector is the vector obtained by merging feature vectors whose similarity error is within a certain range, and the fused feature vector is the vector obtained by merging the merged vectors together.

[0070] Furthermore, as an optional embodiment of the present invention, the vector corresponding to each of the multiple format features can be obtained by using the word2vec algorithm, the similarity of the multiple feature vectors can be calculated by using the cosine function, the multiple feature vectors can be merged by performing vector addition, and the merged feature vectors can be fused by using the late fusion method.

[0071] Furthermore, as an optional embodiment of the present invention, constructing the step response matrix of the plurality of object formats includes:

[0072] The step response matrix of the multiple object formats is constructed using the following formula:

[0073]

[0074] Where A represents the step response matrix of multiple object formats, n and m represent the number of rows and the number of elements in each row of the step response matrix, and a represents the vector value corresponding to the object format.

[0075] S2. Identify the model category of the target object model, query the import format corresponding to the model category, perform a format conversion on the target object model according to the import format to obtain a formal object model, and import the formal object model into the OPC server corresponding to the controlled object model.

[0076] This invention identifies the model category of the target object model and queries the corresponding import format for that model category, providing a guarantee for subsequent format conversion of the target object model using that import format. Here, the model category refers to the type of the target object model, and the import format is the format in which the target object model is imported into the OPC server. The OPC server is a server that exchanges data with lower-level machines and contains numerous communication and data storage programs. OPC stands for OLE for Process Control, and it is built upon the OLE specification, providing a standard data access mechanism for the industrial control field. Furthermore, the model category of the target object model can be identified using a linear discriminant function, and the import format corresponding to that model category can be queried using the aforementioned `type()` function.

[0077] This invention obtains a formal object model by performing a formal transformation on the target object model. The target object model can be transformed according to the import format, which facilitates its subsequent use with the OPC server. The formal object model is the model obtained after transforming the target object model according to the import format. Furthermore, the formal transformation of the target object model can be completed by querying the format code of the import format and modifying the code of the target object model according to the format code.

[0078] This invention imports the formal object model into the OPC server corresponding to the controlled object model, so that the data in the OPC server can be processed subsequently through the formal object model.

[0079] As an embodiment of the present invention, the step of importing the formal object model into the OPC server corresponding to the controlled object model includes: obtaining the model parameters of the formal object model, querying the code corresponding to the model parameters to obtain the model code, configuring the model code into the OPC server, running the model code in the OPC server, and generating the formal object model.

[0080] The model parameters are various data information of the formal object model, such as the model running process, running environment, and required data format. The model code is the source code corresponding to the model parameters. Furthermore, the model parameters of the formal object model can be obtained through a cloud platform, the code corresponding to the model parameters can be queried through a code query tool, and the model code can be configured to the OPC server through code programming software. The code programming software is compiled in Java and can run the model code through code execution instructions.

[0081] S3. Construct variable information in the OPC server, construct a set of tag numbers corresponding to the variable information based on the variable information, and determine the association between the formal object model and the variable information based on the set of tag numbers.

[0082] This invention constructs variable information in the OPC server so that a corresponding set of reference numbers can be constructed subsequently based on the variable information. The variable information is the information of independent and dependent variables involved in the OPC server. Furthermore, the variable information can be constructed by the data processor in the OPC server.

[0083] This invention constructs a set of reference numbers corresponding to the variable information based on the variable information. The reference number set provides relevant information about the variable information, which facilitates the accurate determination of the relationship between the formal object model and the variable information. The reference number set is a collection of information about the variable information, such as the current value of the variable information, its on / off status, and other information. Furthermore, the reference number set corresponding to the variable information can be constructed using the Collections tool.

[0084] This invention determines the association between the formal object model and the variable information based on the set of reference numbers. The method by which the formal object model processes the variable information can be determined through the association. The association is the interaction and correlation between the formal object model and the variable information.

[0085] As an embodiment of the present invention, determining the association between the formal object model and the variable information based on the tag set includes: extracting the variable label of each variable in the variable information, extracting the model label of the formal object model, calculating the association degree between the variable label and the model label, and determining the association between the formal object model and the variable information based on the association degree.

[0086] Wherein, the variable label is the identification attribute of each variable in the variable information, the model label is the identification attribute of the formal object model, the correlation degree is the degree of correlation between the variable label and the model label, and further, the variable label of each variable in the variable information can be extracted by a label extractor.

[0087] Further, as an optional embodiment of the present invention, calculating the correlation between the variable label and the model label includes:

[0088] The correlation between the variable labels and the model labels is calculated using the following formula:

[0089]

[0090] Where Y(x) represents the correlation between the variable label and the model label, i represents the initial value of the variable label, P represents the total number of variable labels, and Ku represents the mapping value corresponding to the u-th variable label. ω represents the mapping value corresponding to the model label, ω represents the correlation coefficient corresponding to the variable label, and u∈P represents the range to which the variable label belongs.

[0091] S4. Obtain the client data corresponding to the OPC server, calculate the server data corresponding to the client data using the formal object model based on the association relationship, and determine the dynamic mathematical model of the OPC server based on the server data.

[0092] This invention obtains the client data corresponding to the OPC server, which facilitates the subsequent calculation of the server data corresponding to the client data through the formal object model. The client data is the data input by the user in the OPC server, such as newly entered parameter information.

[0093] This invention calculates the server data corresponding to the user-end data using the formal object model based on the association relationship, so as to obtain the dynamic mathematical model of the OPC server through the server data, wherein the server data is the data corresponding to the user-end data in the OPC server.

[0094] This invention determines the dynamic mathematical model of the OPC server based on the server data, thereby obtaining the dynamic mathematical model of the OPC server, which facilitates the subsequent expression of the dynamic characteristics of the controlled object in the OPC server.

[0095] This invention, by acquiring a controlled object model and querying the variable categories within that model, can identify the variable types present in the controlled object model, thus ensuring the subsequent extraction of global objects from the model. Furthermore, by identifying the model category of the target object model and querying the corresponding import format, this invention ensures the subsequent formal transformation of the target object model using that import format. Specifically, this invention constructs variable information within the OPC server, enabling the subsequent construction of corresponding tag sets based on this variable information. Additionally, by acquiring the user-side data corresponding to the OPC server, this invention facilitates the subsequent calculation of server data corresponding to the user-side data using the formal object model. Therefore, the dynamic mathematical model establishment method provided by this invention is a method capable of establishing dynamic mathematical models.

[0096] like Figure 2 The diagram shown is a functional block diagram of a dynamic mathematical model establishment device provided in an embodiment of the present invention.

[0097] The dynamic mathematical model building device 100 of this invention can be installed in an electronic device. Depending on the functions implemented, the dynamic mathematical model building device 100 may include a model conversion module 101, a model import module 102, a relationship determination module 103, and a dynamic model construction module 104. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and which are stored in the memory of the electronic device.

[0098] In this embodiment, the functions of each module / unit are as follows:

[0099] The model conversion module 101 is used to obtain the controlled object model, query the variable categories in the controlled object model, extract the global object of the controlled object model from the variable categories, and define the model of the controlled object model according to the global object to obtain the target object model.

[0100] The model import module 102 is used to identify the model category of the target object model, query the import form corresponding to the model category, perform form conversion on the target object model according to the import form to obtain a formal object model, and import the formal object model into the OPC server corresponding to the controlled object model.

[0101] The relationship determination module 103 is used to construct variable information in the OPC server, construct a set of reference numbers corresponding to the variable information based on the variable information, and determine the association relationship between the formal object model and the variable information based on the set of reference numbers.

[0102] The dynamic model construction module 104 is used to obtain the client data corresponding to the OPC server, calculate the server data of the client data using the formal object model according to the association relationship, and determine the dynamic mathematical model of the OPC server based on the server data.

[0103] In detail, each module in the dynamic mathematical model establishing device 100 described in this application embodiment adopts the same approach as described above during use. Figure 1 The method used is the same as the dynamic mathematical model establishment method described above, and it can produce the same technical effect, so it will not be repeated here.

[0104] like Figure 3 The diagram shown is a schematic diagram of the structure of an electronic device 1 that implements a dynamic mathematical model establishment method according to an embodiment of the present invention.

[0105] The electronic device 1 may include a processor 10, a memory 11, a communication bus 12, and a communication interface 13. It may also include a computer program, such as a dynamic mathematical model establishment method program, stored in the memory 11 and capable of running on the processor 10.

[0106] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device 1, connecting various components of the electronic device through various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., executing dynamic mathematical model establishment methods) and calls data stored in the memory 11 to perform various functions of the electronic device and process data.

[0107] The memory 11 includes at least one type of readable storage medium, including flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of an electronic device, such as a portable hard drive. In other embodiments, the memory 11 can be an external storage device of the electronic device, such as a plug-in portable hard drive, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, etc. Furthermore, the memory 11 can include both internal and external storage units of the electronic device. The memory 11 can be used not only to store application software and various types of data installed on the electronic device, such as the code of a dynamic mathematical model establishment method program, but also to temporarily store data that has been output or will be output.

[0108] The communication bus 12 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable communication between the memory 11 and at least one processor 10, etc.

[0109] The communication interface 13 is used for communication between the electronic device 1 and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, Bluetooth interface, etc.), typically used to establish communication connections between the electronic device and other electronic devices. The user interface may be a display, an input unit (such as a keyboard), or, optionally, a standard wired or wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device and to display a visual user interface.

[0110] Figure 3 Only electronic devices with components are shown; it will be understood by those skilled in the art that... Figure 3 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0111] For example, although not shown, the electronic device 1 may also include a power supply (such as a battery) to power various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0112] It should be understood that the embodiments described are for illustrative purposes only and are not limited to this structure in the scope of the patent application.

[0113] The dynamic mathematical model establishment method program stored in the memory 11 of the electronic device 1 is a combination of multiple instructions, which, when run in the processor 10, can achieve the following:

[0114] Obtain the controlled object model, query the variable categories in the controlled object model, extract the global object of the controlled object model from the variable categories, define the model of the controlled object model based on the global object, and obtain the target object model;

[0115] Identify the model category of the target object model, query the import format corresponding to the model category, perform a format conversion on the target object model according to the import format to obtain a formal object model, and import the formal object model into the OPC server corresponding to the controlled object model;

[0116] In the OPC server, variable information is constructed, and based on the variable information, a set of reference numbers corresponding to the variable information is constructed. Based on the set of reference numbers, the association between the formal object model and the variable information is determined.

[0117] Obtain the client data corresponding to the OPC server, calculate the server data of the client data using the formal object model based on the association relationship, and determine the dynamic mathematical model of the OPC server based on the server data.

[0118] Specifically, the specific implementation method of the processor 10 for the above instructions can be referred to the description of the relevant steps in the corresponding embodiment of the accompanying drawings, and will not be repeated here.

[0119] Furthermore, if the modules / units integrated in the electronic device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0120] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor of an electronic device, can perform the following:

[0121] Obtain the controlled object model, query the variable categories in the controlled object model, extract the global object of the controlled object model from the variable categories, define the model of the controlled object model based on the global object, and obtain the target object model;

[0122] Identify the model category of the target object model, query the import format corresponding to the model category, perform a format conversion on the target object model according to the import format to obtain a formal object model, and import the formal object model into the OPC server corresponding to the controlled object model;

[0123] In the OPC server, variable information is constructed, and based on the variable information, a set of reference numbers corresponding to the variable information is constructed. Based on the set of reference numbers, the association between the formal object model and the variable information is determined.

[0124] Obtain the client data corresponding to the OPC server, calculate the server data of the client data using the formal object model based on the association relationship, and determine the dynamic mathematical model of the OPC server based on the server data.

[0125] In the several embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0126] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0127] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0128] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0129] Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be embraced within the invention. No appended diagram markings in the claims should be construed as limiting the scope of the claims.

[0130] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0131] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices recited in a system claim may also be implemented by a single unit or device through software or hardware. The terms "first," "second," etc., are used to indicate names and do not indicate any specific order.

[0132] The various embodiments in this disclosure are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0133] The scope of protection of this disclosure is not limited to the embodiments described above. Obviously, those skilled in the art can make various modifications and variations to this disclosure without departing from its scope and spirit. If such modifications and variations fall within the scope of the claims of this disclosure and their equivalents, then the intent of this disclosure also includes such modifications and variations.

Claims

1. A method for establishing a dynamic mathematical model, characterized in that, The method includes: Obtain the controlled object model, query the variable categories in the controlled object model, extract the global object of the controlled object model from the variable categories, define the model of the controlled object model based on the global object, and obtain the target object model; Identify the model category of the target object model, query the import format corresponding to the model category, perform a format conversion on the target object model according to the import format to obtain a formal object model, and import the formal object model into the OPC server corresponding to the controlled object model; In the OPC server, variable information is constructed, and based on the variable information, a set of reference numbers corresponding to the variable information is constructed. Based on the set of reference numbers, the association between the formal object model and the variable information is determined. Obtain the client data corresponding to the OPC server; calculate the server data of the client data using the formal object model based on the association relationship; and determine the dynamic mathematical model of the OPC server based on the server data. The step of extracting the global object of the controlled object model from the variable categories includes: Obtain the independent and dependent variables from the variable categories, and identify the variable information of the independent and dependent variables; Based on the variable information, determine the variable relationship between the independent variable and the dependent variable; Based on the variable relationships, the variable information, and the variable categories, a global object of the controlled object model is generated; The step of defining the controlled object model based on the global object to obtain the target object model includes: Identify the format corresponding to each object in the global object to obtain multiple object formats, and extract the format features of each format in the multiple object formats to obtain multiple format features; The multiple format features are fused to obtain fused format features, and the step response matrix of the multiple object formats is constructed. The step response matrix is ​​convolved to obtain the calculation result. Based on the calculation result and the fusion format features, the controlled object model is defined to obtain the target object model.

2. The method for establishing a dynamic mathematical model as described in claim 1, characterized in that, Determining the variable relationship between the independent variable and the dependent variable based on the variable information includes: The relationship between the independent variable and the dependent variable is determined by the following formula: in, This represents the variable relationship between the j-th independent variable and the k-th dependent variable. This indicates the quantity corresponding to the variable information. This represents the linear value corresponding to the variable information. This represents the vector mean corresponding to the variable information. This represents the mapping value corresponding to the dependent variable. This represents the mapping value corresponding to the independent variable. This indicates the variable dimensions corresponding to the independent and dependent variables.

3. The method for establishing a dynamic mathematical model as described in claim 1, characterized in that, The extraction of format features from each of the multiple object formats yields multiple format features, including: The format features of each of the multiple object formats are extracted using the following formula: in, This represents the formatting characteristics of each format, where 'a' represents the starting value among multiple object formats. Represents the vector value for each format. The matrix mean representing multiple object format vectors. This represents the vector dimension coefficient corresponding to each format vector.

4. The method for establishing a dynamic mathematical model as described in claim 1, characterized in that, Determining the association between the formal object model and the variable information based on the set of reference numbers includes: Extract the variable label for each variable from the variable information, and extract the model label for the formal object model; Calculate the correlation degree between the variable label and the model label, and determine the association relationship between the formal object model and the variable information based on the correlation degree.

5. A dynamic mathematical model establishing apparatus for implementing the dynamic mathematical model establishing method according to any one of claims 1-4, characterized in that, The device includes: The model conversion module is used to obtain the controlled object model, query the variable categories in the controlled object model, extract the global object of the controlled object model from the variable categories, and convert the controlled object model into a standard format based on the global object to obtain the target object model. The model import module is used to identify the model category of the target object model, query the import form corresponding to the model category, perform form conversion on the target object model according to the import form to obtain a formal object model, and import the formal object model into the OPC server corresponding to the controlled object model. The relationship determination module is used to construct variable information in the OPC server, construct a set of reference numbers corresponding to the variable information based on the variable information, and determine the association relationship between the formal object model and the variable information based on the set of reference numbers. The dynamic model building module is used to obtain the client data corresponding to the OPC server, calculate the server data of the client data using the formal object model according to the association relationship, and determine the dynamic mathematical model of the OPC server based on the server data.

6. An electronic device, characterized in that, The electronic device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the dynamic mathematical model building method as described in any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the dynamic mathematical model establishment method as described in any one of claims 1 to 4.

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