Dragon scale system DCS simulation automatic modeling method and device

Abstract

The invention provides a dragon scale system DCS simulation automatic modeling method and device, and relates to the technical field of simulation platform data processing, and the method comprises the steps: obtaining an initial file, obtaining an initial part file and an initial configuration file from the initial file, and enabling the initial configuration file to comprise graph information, part configuration information and connection line information; analyzing based on the initial component file, determining a main body and a node of each component, and generating a target component file; performing analysis based on the graph information, the component configuration information and the connection line information to perform dynamic wiring on nodes associated with each component, determining a target connection line of each component, and generating a target configuration file; and modeling is performed on a simulation platform based on the target configuration file and the target component file, and the problem that existing simulation modeling depends on manual operation of a graphical module and is low in efficiency is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of simulation platform data processing, and in particular to a method and device for automatic modeling of a DCS simulation of a dragon scale system. Background Art

[0002] The Dragon Scale System is a nuclear safety-level digital control device (DCS) independently developed by the China Nuclear Power Research and Design Institute. It is called the "central nervous system" of a nuclear power plant. The Dragon Scale System DCS modeling is a way to create and manage models based on the Dragon Scale System DCS (distributed control device). Most DCSs use graphical modeling, which usually refers to the use of graphical methods to represent and analyze the structure and behavior of the device. In the simulation development process of the distributed control device, the modeling relies on the configuration rules of the simulation platform to generate graphical simulation configuration files. Therefore, most of the existing modeling uses manual operation of graphical modules, which is cumbersome and inefficient. Summary of the invention

[0003] In order to overcome the above technical defects, the purpose of the present invention is to provide a method and device for automatic modeling of DCS simulation of a dragon scale system, so as to solve the problem that the existing simulation modeling relies on manual operation of graphical modules and has low efficiency.

[0004] The invention discloses a DCS simulation automatic modeling method for a dragon scale system, comprising: Acquire an initial file, and acquire an initial component file and an initial configuration file from the initial file, wherein the initial configuration file includes drawing information, component configuration information, and connection line information; Parsing the initial component file to determine the body and nodes of each component and generate a target component file; Parsing based on the graph information, component configuration information and connection line information to dynamically route nodes associated with each component, determine target connection lines for each component, and generate a target configuration file; Modeling is performed on a simulation platform based on the target configuration file and the target component file.

[0005] Preferably, the parsing based on the diagram information, component configuration information and connection line information includes: Performing data mapping on the graph information to generate target graph information; Classify and process the component configuration information to generate target configuration information corresponding to each component under the target configuration file; The connection line information is parsed to obtain the wiring area and the node pairs associated with each component.

[0006] Preferably, dynamically routing nodes associated with each component to determine target connection lines of each component includes: Acquire the node pairs associated with the wiring area and each component based on the initial configuration file; Performing grid division on the wiring area, wherein each component and its node are located at at least one grid point, and the target connection line corresponds to a path formed between the grid points; According to the node pairs associated with each component, a path set associated with each node pair is formed, and the path iterative optimization is performed based on the path set according to preset conditions to obtain the target path associated with each node pair and determine the target connection line of each component.

[0007] Preferably, at least one path algorithm is used to determine the path in the path set for each node pair.

[0008] Preferably, the iterative path optimization based on the path set includes: Each grid point in the routing area is weighted so that grid points covered by other paths or nodes are avoided under any path.

[0009] Preferably, after obtaining the target paths associated with each node pair, the method further includes: Post-processing is performed on the paths associated with each node pair, and the post-processing includes smoothing and spacing optimization.

[0010] Preferably, the classifying and processing the component configuration information to obtain the target configuration information corresponding to each component under the target configuration file includes: Obtain basic information of the component and determine the component type, wherein the component type includes an interface component and an algorithm component; When the component type is an interface component, data conversion is performed according to a preset parameter type to generate target configuration information; When the component type is an algorithm component, the corresponding algorithm module is called to generate target configuration information.

[0011] Preferably, the parsing based on the initial component file to determine the body and nodes of each component includes: Determine the body of each component based on the vector diagram of each component in the initial component file; The nodes of each component are defined based on the pin information of each component in the initial component file, wherein each node includes a node number, a node type, a node coordinate, a node description, and a node position.

[0012] The present invention also provides a DCS simulation automatic modeling device for a dragon scale system, comprising: An acquisition module, used for acquiring an initial file, and acquiring an initial component file and an initial configuration file from the initial file, wherein the initial component file is a text format file, the initial configuration file is a graphic format file, and the initial configuration file includes graphic information, component configuration information and connection line information; A component file translation module, used to parse the initial component file, determine the body and nodes of each component, and generate a target component file; A configuration file translation module is used to parse the diagram information, component configuration information and connection line information to dynamically route nodes associated with each component, determine target connection lines of each component, and generate a target configuration file; The processing module is used for modeling on a simulation platform based on the target configuration file and the target component file.

[0013] Preferably, the configuration file translation module includes: A graph information processing module, used for processing graph information; A component configuration information processing module, used for processing component configuration information; The connection line information processing module is used to process the connection line information.

[0014] Compared with the prior art, the above technical solution has the following beneficial effects: The automatic modeling method and device provided in the present application are based on the initial file, and parse the initial component file and the initial configuration file in the initial file. According to the configuration rules of the simulation platform, based on the dynamic wiring of the associated nodes, the target connection lines between each node of each component are determined, and a simulation configuration file suitable for the simulation platform graphics is generated, that is, including the target configuration file and the target component file. Automatic modeling is performed on the simulation platform, which solves the problem that the existing simulation modeling relies on manually operated graphical modules and has low efficiency, and improves the efficiency and quality of control system modeling and development. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A method flow chart of an embodiment of a method and device for DCS simulation automatic modeling of a dragon scale system according to the present invention; Figure 2 A flowchart of dynamically wiring nodes associated with each component and determining target connection lines of each component in a method and device embodiment of a dragon scale system DCS simulation automatic modeling method and device according to the present invention; Figure 3 A schematic diagram of a node pair with connecting lines in an embodiment of a method and device for automatic modeling of a DCS simulation of a dragon scale system according to the present invention; Figure 4This is a schematic diagram of a device module of an embodiment of a dragon scale system DCS simulation automatic modeling method and device according to the present invention.

[0016] Reference numerals: 5-automatic modeling device; 51-acquisition module; 52-component file translation module; 53-configuration file translation module; 531-graph information processing module; 532-component configuration information processing module; 533-connection line information processing module; 54-processing module. DETAILED DESCRIPTION

[0017] The advantages of the present invention are further described below in conjunction with the accompanying drawings and specific embodiments.

[0018] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0019] The terms used in this disclosure are for the purpose of describing specific embodiments only and are not intended to limit the disclosure. The singular forms of "a", "said" and "the" used in this disclosure and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0020] It should be understood that the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determination" depending on the context. In the subsequent description, suffixes such as "module", "component" or "unit" used to represent elements are used only to facilitate the description of the present invention and have no specific meaning in themselves. Therefore, "module" and "component" may be used interchangeably.

[0021] Example: This embodiment discloses a method for automatic modeling of DCS simulation of a dragon scale system. Based on the initial file obtained by the dragon scale system (configuration file under the dragon scale system), a graphical simulation configuration file, i.e., a target configuration file, is generated according to the configuration rules of the simulation platform. Code is automatically generated through the download function of the simulation platform to realize automatic modeling. For details, see Figure 1 ,include: S10: Obtaining an initial file, and obtaining an initial component file and an initial configuration file from the initial file, wherein the initial configuration file includes drawing information, component configuration information, and connection line information; The above initial file is the configuration file under the Dragon Scale system. The following target component file and target configuration file are files for Rnsin2.0 adapted to the simulation platform. After directly inputting the platform, the download function of the platform's engineer station automatically generates code for automatic modeling. The target component file is in xml format, and the target configuration file is a graph format file. The configuration file reflects the status, connection relationship / control logic of each component. The connection relationship / control logic associates the nodes (control nodes / pins, such as input, output, etc.) of each component. Each component can contain multiple nodes (pins).

[0022] S20: parsing the initial component file to determine the body and nodes of each component and generating a target component file; In this implementation, the initial component file includes source data corresponding to each component under the dragon scale system, which needs to be converted into a target component file recognizable by the simulation platform, so as to be combined with the target configuration file described below, so that the simulation configuration logic diagram finally presented to the user on the simulation platform (wherein each component is represented by a target connection line, the target diagram information determines the diagram state, and the target configuration information is used to determine the state of each component) has a high degree of restoration and realism, so as to achieve a visually consistent effect with the configuration logic diagram under the dragon scale system.

[0023] As an illustration, the information of each component in the initial component file is located in the entity tag (group / data) under the item (component) of its dragon scale system configuration file, which includes two parts, one is the main body appearance, and the other is the pin information. These two parts of information are parsed and processed to obtain a file that can be used to determine the component body and each node under the simulation device, that is, the above-mentioned target component file.

[0024] Specifically, the parsing based on the initial component file to determine the body and nodes of each component includes: determining the body of each component based on the vector diagram of each component in the initial component file; defining the nodes of each component based on the pin information of each component in the initial component file, wherein each node includes a node number, a node type, a node coordinate, and a node position.

[0025] Based on the above: For the main body of the component, the main body of the component in the initial file is included in the body tag under entity, which is generally expressed as a vector graphic in SVG format. SVG is an XML-based vector graphic format. They are composed of paths, shapes and basic graphics, and can be infinitely enlarged or reduced without distortion. The Rinsim2.0 simulation platform used in this embodiment supports SVG images, so the main body appearance can be generated by directly calling the SVG file, that is, no other operations are required, and the vector graphics file in the initial file can be directly obtained to determine the main body of each component.

[0026] For each node of a component, the pin information is located in the pins tag in the initial file. A component can contain multiple pins, so there are usually multiple pins under the pins tag. As an example, the component node (control node / pin) under the simulation platform can be automatically defined through the following pin information: pinNumber: pin number, type is integer (corresponding to the node number defined in the simulation device); direction: pin IO type. IO types are divided into input type, output type and internal type. 0 represents input type, 1 represents output type and 2 represents internal type (the corresponding definition is applied to the node type under the simulation device); dataType: pin data type, where analog represents analog quantity with quality, binary represents switch quantity with quality, int represents integer, kcg_real represents floating point type, kcg_bool represents Boolean type, and mulriple represents indefinite type; x: the horizontal coordinate of the pin in the component body, of floating point type, in pixels (the corresponding definition is applied to the node coordinates under the simulation device); y: the vertical coordinate of the pin in the component body, the type is floating point, the unit is pixel; nameInfo: A text description of the pin and its position in the component body, including the component name, horizontal coordinate, and vertical coordinate, which are connected by a semicolon (the corresponding definition is applied to the node position under the simulation device).

[0027] Based on the above, the component body and nodes of the application simulation platform are defined by the initial file body data and pins data. As an explanation, it can be simply understood that the target component file generated above is used to determine the basic information or presentation location of each component, and the target configuration file below is used to determine the connection / control relationship of each component. The final overall presentation is a simulation configuration logic diagram containing each component, which can be adapted to the simulation platform to generate code based on the simulation configuration logic diagram for autonomous modeling, that is, to establish a simulation device corresponding to its components, functions and applications based on the Dragon Scale system.

[0028] S30: parsing based on the graph information, component configuration information and connection line information to dynamically route nodes associated with each component, determine target connection lines of each component, and generate a target configuration file; It can be understood that the configuration file (here the target configuration file) is a file used to define and configure the parameters and behaviors of each component. As mentioned above, the above target component files are collected to determine the parameters and behaviors of each component to achieve the simulation modeling required later. Due to the differences in graph information, component configuration information and connection line information, different processing is performed. The processing of different information can be performed sequentially or in steps / synchronously. The target configuration file is generated by the following target graph information, target configuration information and target connection line collection, which can be expressed as a simulation configuration logic diagram of each component with target connection lines as mentioned above. The target graph information represents the graph state, and the target configuration information is used to represent the state of each component.

[0029] Specifically, the analysis based on the graph information, component configuration information and connection line information includes: performing data mapping on the graph information to obtain target graph information; classifying the component configuration information to obtain target configuration information corresponding to each component under the target configuration file; parsing the connection line information to obtain node pairs associated with the wiring area and each component.

[0030] As an example, the specific description is as follows: Analysis of graph information: Graph information is the graph attribute information corresponding to each logic graph (i.e. the initial file, the configuration logic graph under the Dragon Scale system) (pageInfo, cpuBorder and PageDescription tags under the Dragon Scale system PAGE module); According to a mapping relationship table provided in advance, wherein the mapping relationship table contains several data types (such as node name, logic diagram name, logic diagram position, logic diagram size, logic diagram associated document and logic diagram description, etc.); extract the preset data type in the diagram information, and convert and generate the target diagram information (ModelFigure information) in the target configuration file.

[0031] Specifically, as an example, parse the three tags pageInfo, cpuBorder and PageDescription in the initial file; From the above three tags, we need to extract the following: siteName: control station name, type is string.

[0032] pageName: logical diagram name, type is string.

[0033] cpuBorder@x, cpuBorder@y: logical map position, both of integer type.

[0034] cpuBorder@width, cpuBorder@height: logical graph size, both of integer type.

[0035] referencePageName: logical diagram related document, type is string.

[0036] effectName: logical diagram description, type is string.

[0037] The ModelFigure information in the target configuration file that needs to be generated finally includes the following: Name: corresponds to the pageName in the Dragon Scale system configuration file; LogicSystem: corresponds to the siteName in the dragon scale system configuration file; Width: corresponds to the width attribute under the cpuBorder node in the Dragon Scale system configuration file; Height: corresponds to the height attribute under the cpuBorder node in the Dragon Scale system configuration file; RelatedPaperPage: corresponds to the referencePageName in the Dragon Scale system configuration file; Description: Corresponds to effectNam in the Dragon Scale system configuration file.

[0038] Therefore, a mapping relationship table is established in advance to make each type of data correspond to each other, and the processing of the graph information can be realized through extraction and mapping.

[0039] Analysis of component configuration information: The ITEM (component) module in the initial file corresponds to a component in the above simulation platform configuration logic diagram. As an example, its component configuration information includes the following information: frameID: The unique serial number of the component in the diagram, of integer type.

[0040] itemTexts: component text prompt information, the type is string.

[0041] Geometry@x: The horizontal coordinate of the component, of integer type.

[0042] Geometry@y: The component's vertical coordinate, of integer type.

[0043] functionID: The type is an integer. When the value is 0, it indicates that the component type is an interface component. When the value is non-zero, it indicates that the component type is an algorithm component.

[0044] Specifically, the classifying and processing the component configuration information to obtain the target configuration information corresponding to each component under the target configuration file includes: Obtain basic information of the component and determine the component type, wherein the component type includes an interface component and an algorithm component; When the component type is an interface component, data conversion is performed according to a preset parameter type to obtain target configuration information; When the component type is an algorithm component, the corresponding algorithm module is called to generate target configuration information.

[0045] Based on the above, it can be understood that the component type can be determined according to the functionID.

[0046] As an example: The interface component includes the following information (that is, the above preset parameter types include varType, variableType and variableDataType): varType: interface type identifier, type is string. variableType: data flow direction, 0-bit input, 1-bit output, type is integer. variableDataType: data type, analog is analog quantity, binary is switch quantity, type is string. variableAttribute@name: interface name, type is string. For interface components, the three parameters of varType, variableType and variableDataType are used to determine the called components that can be identified in the simulation platform (that is, the target configuration information corresponding to the component under the generated target configuration file), as shown below:

[0047] From the above examples, it can be seen that different parameters of the same interface type in the initial file can also generate different component configuration information in the target configuration file, that is, corresponding conversion / calling is performed according to preset conditions (or preset mapping table).

[0048] For the algorithm component, the corresponding algorithm module is called based on the preset mapping table to generate the target configuration information and determine the target configuration information. The preset mapping table includes the information and calling information of each algorithm component under the Dragon Scale system. For example, when the above functionID is not 0, it is an algorithm component. The called algorithm component is determined according to the value of the functionID. For example, when the functionID is 4, the algorithm component is SSF_A, and the simulation platform calls the corresponding algorithm module according to the algorithm component indicated by the functionID for simulation.

[0049] The configuration information ultimately needs to generate component information / labels (i.e. component configuration information) in the target configuration file. The component information / labels contain the following attributes: ID: corresponds to the frameID in the dragon scale system configuration file (initial file); Name: component name, such as the interface component or algorithm component in the above example; TagNumber: corresponds to the name attribute under variableAttribute in the Dragon Scale system configuration file; Caption: corresponds to itemTexts in the Dragon Scale system configuration file; PosX: corresponds to the x attribute under Geometry in the Dragon Scale system configuration file; PosX: corresponds to the y attribute under Geometry in the dragon scale system configuration file.

[0050] Therefore, each data in the target configuration file can be generated from the component configuration information in the initial file.

[0051] Analysis of connection line information: Connection lines are used to represent the connection of various nodes and / or logic gates in a component to determine associated node pairs. In this embodiment, the wiring area and the associated node pairs under each component can be obtained; In the initial file (under the LINE module of the Dragon Scale system), each connection line in the configuration logic diagram corresponds to a line label (such as Figure 3 The following information can be extracted: startFrameID: The frameID of the starting component, of integer type.

[0052] endFrameID: The frameID of the end component, of integer type.

[0053] startPinID: The pinID of the starting component, of integer type.

[0054] endPinID: The pinID of the end component, which is an integer.

[0055] Since the connection line information in the initial file is encrypted, that is, how the modules in the Dragon Scale system are connected (control logic) is encrypted, only the nodes at the starting and ending ends of the above control process (that is, the associated node pairs) can be determined, and the path of the connection line cannot be directly obtained, that is, the connection relationship between the node pairs cannot be directly obtained (control logic). Therefore, in this embodiment, a method for autonomous path planning is proposed, and the wiring area is determined according to all the connection line information, and a number of connection lines are generated according to the nodes (pairs) (components, logic gates, etc.) to be connected. The length, number of crossings, signal integrity, wiring density, etc. of the connection lines are further optimized to determine the optimal connection lines, and the wiring problem is converted into a path optimization problem, in which the nodes are defined to represent the input / output endpoints of the components or the logic gates thereon, and the edges formed by the connections represent possible connection paths.

[0056] For details, see Figure 2 In the above S30, the nodes associated with each component are dynamically routed to determine the target connection line (connection relationship / control logic) of each component, including: S31: based on the initial configuration file, the node pairs associated with the routing area and each component are obtained (that is, as in the above example, the associated node pairs can be obtained under the line label corresponding to a connection line in each configuration logic diagram in the initial file, and all connection lines can determine the routing area); S32: the routing area is grid-divided, wherein each component and its node are located at at least one grid point, and the target connection line corresponds to the path formed between the grid points; S33: according to the node pairs associated with each component, a path set associated with each node pair is formed, and the path is iteratively optimized based on the path set according to preset conditions to obtain the target path associated with each node pair and determine the target connection line of each component.

[0057] Based on the above, the wiring area is divided into grid points, wherein the input nodes and output nodes of the component or the logic gate thereon are located on the grid points. Each component may occupy multiple grid points, and there may be more than one logic gate thereon, and therefore may also have multiple input nodes and / or output nodes.

[0058] Based on the above, the formed path (target connection line / control logic) can only move on the specified path between the grid points. Optionally, at least one path algorithm is used to determine the path in the path set of each node pair, including but not limited to the Dijkstra algorithm, A* search algorithm or Bellman-Ford algorithm, etc. A shortest path algorithm can also be selected to find the shortest path between any two nodes.

[0059] Since there are multiple components, there are also several node pairs, and there are also several paths formed thereby, there may be problems such as covering the grid points where the components are located and crossing, which may lead to confusion in the formed paths and their corresponding target connection lines (connection relationships). Therefore, further, the path iterative optimization based on the path set includes: weighting each grid point in the routing area so that grid points covered by other paths or nodes are avoided under any path: the nodes / grid points can be weighted iteratively to remove paths that cover other nodes or cross; that is, in the routing process, other grid points of existing lines or logic gates may become obstacles. These obstacles can be regarded as impassable edges or additional weights can be added for screening; when designing the path, it is also necessary to ensure that there are no crossing lines. This can be achieved by adding rules in the algorithm / or iteratively weighting the grid points. For example, once a path occupies a grid point, subsequent paths can no longer use the grid point.

[0060] Furthermore, as an option, components with multiple layers of components can also be considered in the wiring area, and the paths formed by node pairs located in different layers can be converted into layer formats, that is, in the case of multi-layer wiring, the connections between different layers can be considered. Specifically, vias can be used to achieve conversion between layers, and the use of vias can be optimized during iteration.

[0061] The above optimization of the path formed between node pairs may require multiple iterations to optimize. In each iteration, the shortest path algorithm can be set to find a path for the currently unwired nodes, and then the obstacle information in the graph (grid weights where the nodes are located, etc.) can be updated synchronously, thereby providing an efficient wiring method that arranges the shortest path between each node pair to reduce the wiring length and reduces line crossings. It can be understood that in addition to the shortest path, the above preset conditions can also be other optimization conditions / goals, such as minimizing the total wiring area, etc., so as to dynamically / iteratively adjust the path formed between each node pair in the wiring area to meet application requirements.

[0062] Based on the above iteration, in order to further improve the effect of the generated path, after obtaining the target path associated with each node pair, it also includes: post-processing the path associated with each node pair, and the post-processing includes smoothing, spacing optimization, to meet the design rule check (DRC) requirements, etc.

[0063] The connection line information in the above initial file needs to generate the JoinLine information / label in the target configuration file. The JoinLine information / label contains the following data: StartComponentID: corresponds to the startFrameID in the Dragon Scale system configuration file (i.e. the initial configuration file) StartPointID: corresponds to the startPinID in the Dragon Scale system configuration file; EndPointID: corresponds to the endPinID in the Dragon Scale system configuration file The path of the JoinLine node pair (i.e., the connection line between the node pairs) can be determined according to the above wiring method.

[0064] Therefore, based on the above, the diagram information, component configuration information, and connection line information can be parsed, and the corresponding attribute information of the simulation logic diagram (i.e., target diagram information, ModelFigure information), target component configuration information (Component information) and target connection lines (JoinLine information) after autonomous path optimization can be generated to generate a target configuration file.

[0065] S40: Modeling is performed on a simulation platform based on the target configuration file and the target component file.

[0066] Based on the data processing in the above S10-S30, the obtained target configuration files and target component files are input into the simulation platform for autonomous modeling, thereby realizing the automatic generation of configuration files and component files adapted to the Rinsim2.0 platform using the Dragon Scale system configuration file as input, and the code is generated based on the underlying simulation platform to realize the automatic modeling of the simulation device.

[0067] This embodiment also provides a DCS simulation automatic modeling device for a dragon scale system, see Figure 4 ,include: An acquisition module, used for acquiring an initial file, and acquiring an initial component file and an initial configuration file from the initial file, wherein the initial configuration file includes drawing information, component configuration information and connection line information; A component file translation module (SYMBOL module), used to parse the initial component file, determine the body and pins of each component, and generate a target component file; Configuration file translation module (xmlParser module and mfgCreator module, wherein the xmlParser module parses the graph information, module configuration information, and connection line information in the initial file, and the mfgCreator module is used to generate graph attribute information, target configuration information, associated nodes, and target connection lines that are adapted to the modeling platform and correspond to the graph information, component configuration information, and connection line information, respectively, to generate a simulation graph, i.e., a target configuration file), for parsing based on the graph information, component configuration information, and connection line information to dynamically route nodes associated with each component, determine target connection lines for each component, and generate a target configuration file, which can be expressed as a logic diagram containing control logics of each component; The processing module is used for modeling on the platform based on the target configuration file and the target component file.

[0068] Specifically, the configuration file translation module includes: Figure information processing module (generated by PAGE module and FIGURE module) is used to process the figure information; Component configuration information processing module (ITEM module parsing, COMPONENT module generation), used to process component configuration information; Connection line information processing module (LINE module parsing, JOINLINE module generation), used to process connection line information; Generate target configuration files based on the above modules.

[0069] In this embodiment, data processing is implemented according to the cooperation of the configuration data analysis module mfgCreator module and the component file translation module SYMBOL module to generate target configuration files and target component files, which can be adapted to the simulation system. After entering the simulation platform, a graphical simulation configuration file is generated according to the configuration rules of the simulation platform. The download function of the simulation platform's engineer station automatically generates code for automatic modeling, thereby improving work efficiency.

[0070] The methods and modules provided in this embodiment can be implemented in hardware, software or a combination thereof, and can be implemented and executed in combination with various illustrative steps, devices, processors, memories, integrated circuits or other combinations described in the present invention. When implemented in software, in combination with the illustrative steps described above, the module can also be stored as one or more instructions or codes on a computer-readable storage medium for transmission. Whether these methods and functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0071] It should be noted that the embodiments of the present invention have better practicability and do not impose any form of limitation on the present invention. Any technician familiar with the field may use the technical content disclosed above to change or modify it into an equivalent effective embodiment. However, any modification or equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A method for automatic modeling of DCS simulation of dragon scale system, characterized in that: include: Acquire an initial file, and acquire an initial component file and an initial configuration file from the initial file, wherein the initial configuration file includes drawing information, component configuration information, and connection line information; Parsing the initial component file to determine the body and nodes of each component and generate a target component file; Parsing based on the graph information, component configuration information and connection line information to dynamically route nodes associated with each component, determine target connection lines for each component, and generate a target configuration file; Modeling is performed on a simulation platform based on the target configuration file and the target component file.

2. The automatic modeling method according to claim 1, characterized in that: The parsing based on the diagram information, component configuration information and connection line information includes: Performing data mapping on the graph information to generate target graph information; Classify and process the component configuration information to generate target configuration information corresponding to each component under the target configuration file; The connection line information is parsed to obtain the wiring area and the node pairs associated with each component.

3. The automatic modeling method according to claim 1, characterized in that: The dynamically routing nodes associated with each component to determine the target connection lines of each component includes: Acquire the node pairs associated with the wiring area and each component based on the initial configuration file; Performing grid division on the wiring area, wherein each component and its node are located at at least one grid point, and the target connection line corresponds to a path formed between the grid points; According to the node pairs associated with each component, a path set associated with each node pair is formed, and the path iterative optimization is performed based on the path set according to preset conditions to obtain the target path associated with each node pair and determine the target connection line of each component.

4. The automatic modeling method according to claim 3, characterized in that: At least one path algorithm is used to determine a path in the path set for each node pair.

5. The automatic modeling method according to claim 3, characterized in that: The iterative path optimization based on the path set includes: Each grid point in the routing area is weighted so that grid points covered by other paths or nodes are avoided under any path.

6. The automatic modeling method according to claim 3, characterized in that: After obtaining the target paths associated with each node pair, the method further includes: Post-processing is performed on the paths associated with each node pair, and the post-processing includes smoothing and spacing optimization.

7. The automatic modeling method according to claim 2, characterized in that: The classifying and processing the component configuration information to generate target configuration information corresponding to each component under the target configuration file includes: Obtain basic information of the component and determine the component type, wherein the component type includes an interface component and an algorithm component; When the component type is an interface component, data conversion is performed according to a preset parameter type to generate target configuration information; When the component type is an algorithm component, the corresponding algorithm module is called to generate target configuration information.

8. The automatic modeling method according to claim 1, characterized in that: The parsing based on the initial component file to determine the body and nodes of each component includes: Determine the body of each component based on the vector diagram of each component in the initial component file; The nodes of each component are defined based on the pin information of each component in the initial component file, wherein each node includes a node number, a node type, a node coordinate, a node description, and a node position.

9. A DCS simulation automatic modeling device for a dragon scale system, characterized in that: include: An acquisition module is used to acquire an initial file, and acquire an initial component file and an initial configuration file from the initial file, wherein the initial component file is a text format file, the initial configuration file is a graphic format file, and the initial configuration file includes graphic information, component configuration information, and connection line information; A component file translation module, used to parse the initial component file, determine the body and nodes of each component, and generate a target component file; A configuration file translation module is used to parse the diagram information, component configuration information and connection line information to dynamically route nodes associated with each component, determine target connection lines of each component, and generate a target configuration file; The processing module is used for modeling on a simulation platform based on the target configuration file and the target component file.

10. The automatic modeling device according to claim 9, characterized in that: The configuration file translation module comprises: A graph information processing module, used for processing graph information; A component configuration information processing module, used for processing component configuration information; The connection line information processing module is used to process the connection line information.

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