Method and device for automatically generating drawings combining multi-dimensional integration of project information

Abstract

The present invention relates to the technical field related to multidimensional data analysis, and specifically includes a method and device for automatically generating drawings in combination with multidimensional integration of project information, including: collecting project IO tables and information, multidimensionally matching equipment and PLC IO modules; identifying drawing logic, generating primary drawings; combining project information and dynamic factor optimization, formatting according to user preferences, and visually outputting to a display device. The method solves the technical problems of information integration difficulties in the drawing generation process, inability to synchronize new design requirements in time when project requirements change, and limited drawing efficiency, and realizes the generation of primary drawings by automatically calling a template library through identifying the logical relationship generated by the drawings, and optimizing and adjusting in combination with the specific information and dynamic factors of the project, so as to more accurately reflect the equipment connection relationship and signal flow, and timely reflect the latest design requirements when project requirements change, thereby ensuring the technical effect of drawing efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field related to multidimensional data analysis, and in particular to a method and device for automatically generating drawings in combination with multidimensional integration of project information. Background Art

[0002] With the rapid development of modern industrial automation and intelligent manufacturing, the connection and interaction between devices and systems have become increasingly complex, involving the integration of multiple devices, sensors, and control modules. This complexity requires engineers to be able to efficiently generate and adjust design drawings during project implementation in order to accurately display device connections, signal flows, and control logic.

[0003] At present, although some advanced design tools have introduced the function of automatic drawing generation, they lack personalization and flexibility, resulting in the inability to timely reflect the latest design requirements at different stages of the project, especially when requirements change and optimization adjustments are made, leading to information asymmetry in the analysis and decision-making process.

[0004] In summary, the existing technology has the technical problem that it is difficult to integrate information during the drawing generation process and new design requirements cannot be synchronized in time when project requirements change, resulting in limited drawing efficiency. Summary of the invention

[0005] This application aims to solve the technical problems in the prior art of limited drawing efficiency caused by the difficulty in information integration during drawing generation and the inability to synchronize new design requirements in a timely manner when project requirements change, by providing an automatic drawing generation device that combines multi-dimensional integration of project information.

[0006] In view of the above problems, the technical solution to implement this application is:

[0007] On the one hand, the present application provides a method for automatically generating drawings by combining multi-dimensional integration of project information.

[0008] The method includes: collecting a project IO table and basic project information, wherein the project IO table includes device input information and device output information; based on the project IO table, combining the instrument digital display sequence and the device type dimension of the PLC IO information set to perform an association mapping analysis, and match the first mapping combination between the device and the PLC IO module; at the same time, performing an association mapping analysis from the signal property dimension and the IO point distribution dimension, and matching the second mapping combination and the third mapping combination between the device and the PLC IO module; according to the target drawing type, identifying the drawing generation logical relationship, and determining multiple dynamic extensible factors that affect the drawing generation; calling up a drawing template library, and generating a primary adaptive structured drawing under the constraints of the first mapping combination, the second mapping combination, and the third mapping combination, wherein the primary adaptive structured drawing is in a vector graphics format; optimizing and adjusting the primary adaptive structured drawing according to the project basic information and multiple dynamic extensible factors, and then formatting the drawing according to the user preferences, and visually outputting the drawing on a display device connected to the communication.

[0009] On the other hand, the present application provides an automatic drawing generation device that combines multi-dimensional integration of project information, wherein the device includes: an information collection module, which is used to collect a project IO table and basic project information, wherein the project IO table includes device input information and device output information; a first association mapping analysis module, which is used to perform association mapping analysis based on the project IO table, combined with the instrument digital display sequence, and the device type dimension of the PLC IO information set, to match the first mapping combination between the device and the PLC IO module; a second association mapping analysis module, which is used to simultaneously perform association mapping analysis from the signal property dimension and the IO point distribution dimension, respectively, to match the device and the PLC A second mapping combination and a third mapping combination between IO modules; a logical relationship identification module, used to identify the logical relationship of drawing generation according to the target drawing type, and determine multiple dynamic and extensible factors that affect the drawing generation; a drawing generation module, used to call the drawing template library, and generate primary adaptive structured drawings under the constraints of the first mapping combination, the second mapping combination, and the third mapping combination, wherein the primary adaptive structured drawings are in vector graphics format; a visual output module, used to optimize and adjust the primary adaptive structured drawings according to the basic information of the project and multiple dynamic and extensible factors, and then format them according to the user preferences, and output them visually on a display device connected to the communication.

[0010] In summary, one or more technical solutions provided in this application solve the technical problems of limited drawing efficiency due to the difficulty in information integration during drawing generation and the inability to synchronize new design requirements in a timely manner when project requirements change. It realizes the technical effect of identifying the logical relationship of drawing generation, automatically calling the template library to generate primary drawings, and optimizing and adjusting them based on the specific information and dynamic factors of the project, so as to more accurately reflect the equipment connection relationship and signal flow, and timely reflect the latest design requirements when project requirements change, thereby ensuring the technical effect of drawing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 A flow chart of a method for automatically generating drawings in combination with multi-dimensional integration of project information is provided for this application;

[0012] Figure 2 A structural schematic diagram of a drawing automatic generation device combining multi-dimensional integration of project information is provided for this application.

[0013] Explanation of reference numerals: information collection module M100, first association mapping analysis module M200, second association mapping analysis module M300, logical relationship identification module M400, drawing generation module M500, visualization output module M600. DETAILED DESCRIPTION

[0014] Embodiment 1

[0015] The present application is described in detail below with reference to the accompanying drawings. Figure 1 As shown, the present application provides a method for automatically generating drawings by combining multi-dimensional integration of project information, wherein the method comprises:

[0016] S1: Collect the project IO table and basic project information, wherein the project IO table includes device input information and device output information; S2: Based on the project IO table, perform an association mapping analysis in combination with the instrument digital display sequence and the device type dimension of the PLC IO information set to match the first mapping combination between the device and the PLC IO module; S3: At the same time, perform an association mapping analysis from the signal property dimension and the IO point distribution dimension to match the second mapping combination and the third mapping combination between the device and the PLC IO module.

[0017] Specifically, the project IO table is a table containing the input / output information of various types of equipment in the project. This information can include input signals and output signals of equipment sensors, controllers, actuators, etc. It is often used in system integration or automation projects; equipment input information refers to data or signals obtained from the outside, such as data from temperature sensors; equipment output information refers to operating instructions or control signals generated by the equipment, such as instructions to control the start / stop of a motor. PLC IO modules are used to manage the input and output signals of equipment in automation systems. PLC IO modules refer to interface modules that communicate with equipment; instrument digital display sequence refers to the digital instrument sequence in the project, which is usually used to display the numerical information of equipment status or signals, such as pressure gauges, temperature gauges, etc.; signal properties refer to the type of equipment signal, such as analog signals, digital signals, voltage signals, or current signals; IO point distribution dimension refers to the distribution of signal points between IO modules and equipment, which is usually related to the number of input and output of equipment, such as how many input points and output points each module supports.

[0018] Collect and organize the project's IO table, which includes the input and output signal information of all equipment. For example, the input and output signals of the temperature sensors, pressure sensors, valves and other equipment in the project should be fully recorded in the IO table. The basic project information includes the project name, equipment type, equipment quantity, process flow, etc.; Excel or other data management software can be used to manage these project IO tables and basic project information.

[0019] Perform correlation matching analysis on the signal types between the devices in the IO table and the PLC IO modules. The device type dimension refers to the category of the device, such as sensors, actuators, etc. At this time, match the appropriate PLC module by checking the device type. Database analysis tools or PLC configuration software (such as Siemens Step 7, Rockwell Studio 5000) help match the device and PLC IO modules. For example, a temperature sensor is an analog signal type and needs to be matched with the PLC's analog input module, while a valve controller needs to be matched with the PLC's digital output module.

[0020] A second mapping is performed based on the signal properties (analog or digital signal, voltage signal or current signal). Further, it is determined whether the signal is a voltage signal or a current signal to select the appropriate PLC module. Signal type analysis tools (such as Multisim) can be used to identify different signal properties. The input / output type of the PLC module can also be defined through software. If the temperature sensor outputs a 4-20mA current signal, you need to select a PLC module that supports current signal input.

[0021] Perform an association mapping analysis from the IO point distribution dimension and match the third mapping combination. Further, perform a third mapping analysis based on the number of IO points. For example, a PLC module supports up to 16 input signals and 16 output signals. If there are 20 input signals in the project, you need to consider using two IO modules. IO point distribution calculation tools or automated configuration software can be used to manage and optimize the distribution of IO points. Specifically, if there are 20 temperature sensors in a project and a single PLC module supports up to 16 input signals, then you need to add another module to process the extra 4 signals. In the above steps, the first mapping combination, the second mapping combination, and the third mapping combination between the device and the PLC IO module are matched through the device type dimension, the signal property dimension, and the IO point distribution dimension to provide data support for the subsequent generation of project drawings.

[0022] S4: According to the target drawing type, identify the logical relationship of drawing generation, and determine multiple dynamic and extensible factors that affect drawing generation; S5: Retrieve the drawing template library, and generate primary adaptive structured drawings under the constraints of the first mapping combination, the second mapping combination, and the third mapping combination, wherein the primary adaptive structured drawings are in vector graphics format; S6: According to the basic information of the project and multiple dynamic and extensible factors, optimize and adjust the primary adaptive structured drawings, and then format them according to user preferences, and output them visually on a display device connected to the communication.

[0023] Specifically, the target drawing type refers to the specific use of the generated drawing in the application, such as electrical wiring diagrams, process control diagrams, instrument layout diagrams, etc. Different types of drawings have their own design standards and requirements; the drawing generation logical relationship refers to how to generate drawings according to established rules and relationships based on the project's input and output information, equipment mapping and other data. For example, an electrical wiring diagram may require the display of wires connecting devices and the marking of specific interface locations; dynamic extensible factors refer to variables that may affect drawing generation and may be adjusted as project requirements change. For example, the number of equipment, connection methods, etc. may all be dynamic extensible factors; the drawing template library is a collection of pre-designed drawing templates that contains the basic Frameworks, structures, symbols, etc., using templates can speed up the drawing generation process and ensure the consistency of drawings; primary adaptive structured drawings refer to preliminary drawings generated according to preliminary mapping results and drawing templates without full optimization. Primary adaptive structured drawings are structured, that is, they have clear logic and hierarchical relationships, and are usually saved in vector format for subsequent editing and optimization; formatting refers to adjusting the drawings according to user preferences (such as color, font, line type, etc.) to meet the user's visual needs and style preferences; visual output is to display the generated and optimized drawings in real time through display devices (such as computer screens, tablet devices), so that users can interactively view and adjust the drawing content.

[0024] Determine the type of drawings to be generated (such as electrical diagrams, instrument diagrams, etc.) based on project requirements, and then identify the logical relationships generated by the drawings. For example, an electrical wiring diagram may need to show the wire connections and grounding wires between devices; each sensor (input) needs to be connected to the corresponding PLC input port, and each actuator (output) needs to be connected to the PLC output port. At the same time, the drawings need to show the physical connections and signal flows between each device and the control cabinet.

[0025] Dynamically scalable factors include the number, type, location, and connection method of equipment. These factors will affect the layout, connection method, and complexity of the drawings. For example, when the number of equipment increases, it is necessary to consider how to display all the equipment and their connection methods in a limited drawing space; under the constraints of the first mapping combination, the second mapping combination, and the third mapping combination, the drawing template library is called to generate a preliminary structured drawing. The first mapping combination, the second mapping combination, and the third mapping combination determine the connection method between the device and the PLC IO module, and the template library provides a preset drawing structure and framework. The generated primary drawings need further adjustment, but the primary adaptive structured drawings already include the basic information and connection relationships of the equipment.

[0026] Drawing template libraries can be implemented based on the template function of EPLAN or AutoCAD, and contain different types of drawing templates, which help to quickly generate drawings that meet project requirements; then, the drawings are further optimized based on the basic information of the project (such as the number of equipment, layout, signal properties, etc.) and dynamic scalable factors (such as new equipment, signal changes, etc.). The goal is to ensure that the drawings meet project requirements and are scalable and readable. Specifically, if it is found that the positions of some sensors are too dense, the positions of these devices in the drawings can be adjusted, and the connection lines can be rearranged to ensure that the drawings are clear and meet project requirements. Further, CAD tools such as AutoCAD and EPLAN are used in combination with scripting languages ​​(such as VBA and Python) for automated optimization and adjustment. For example, by writing scripts, the position and line type of the equipment can be quickly adjusted.

[0027] The purpose of formatting is to make the generated drawings conform to the user's visual and style preferences. For example, the user may prefer a certain line type, a specific drawing color scheme, or a specific annotation font. The final formatting adjustment of the drawing is made based on these preferences. Furthermore, the drawing formatting tool can use the layer function and style settings in AutoCAD, combined with template engine technology to manage user preferences. Specifically, the user prefers that all electrical connection lines are displayed in blue, sensor symbols are green, and device names are annotated with Arial font; the drawings are adjusted based on these preferences to meet the user's requirements.

[0028] After the optimization and formatting process is completed, the drawings will be visualized and output through the connected display device (such as a computer, projector, etc.). Users can interactively view the drawings on the screen and perform operations such as zooming, panning, and rotating. Furthermore, the visualization output can be achieved through the view tools of AutoCAD, EPLAN, or dedicated visualization software (such as Navisworks). Specifically, the user opens the generated drawings on the computer and uses the interactive functions of the software to view the details of different parts, zoom in on a certain area to check specific connection lines, or adjust the layers to view the relationship between different devices. Through the above steps, it is ensured that the drawing generation process is both efficient and flexible to meet the needs of complex projects.

[0029] Further, based on the project IO table, combined with the instrument digital display sequence and the device type dimension of the PLC IO information set, an association mapping analysis is performed to match the first mapping combination between the device and the PLC IO module. The method of the present application includes:

[0030] Based on the project IO table, M associated mapping starting points are added, and the mapping direction of the associated mapping starting points is consistent with the device type dimension; through the M associated mapping starting points, preliminary mapping relationships with the instrument digital display sequence and each device type in the PLC IO information set are established respectively to form a first mapping relationship network; based on the first mapping relationship network, verification is performed to determine the first mapping combination between the device and the PLC IO module.

[0031] Specifically, the project IO table is the input / output device information table in the project, which contains the input signals (such as sensor signals) and output signals (such as actuator signals) of the device. The IO table is a key data source when designing an automation system; the instrument digital display sequence is the order and format of the numerical values ​​displayed by the device, which is usually used to represent the measurement data or status information of the instrument. The digital display sequence of different instruments may have different display orders or formats; the PLC IO information set is the input and output information set of the PLC (programmable logic controller), which contains the connection information between the PLC and external devices, including input modules, output modules and their corresponding signal types; the device type dimension is the standard for classifying devices, such as sensors, actuators, control devices, etc. This is one of the important dimensions when matching devices with PLC IO modules; the association mapping starting point refers to the starting point used to connect the relationship between different devices during the mapping analysis process, which determines the direction and scope of the mapping; the mapping relationship network refers to the network structure of all mapping relationships between devices and PLCIO modules, which is the result of multiple mapping combinations.

[0032] Execution steps: Extract the input and output information of the device from the project IO table. Then, combined with the type dimension of the device, add M associated mapping starting points. Each starting point represents a mapping starting point, which identifies which PLC IO module the input or output of a device needs to be connected to. Specifically, commonly used tools include database or table management tools, such as Excel and SQL databases, which are used to store and manage data in the project IO table. Special software tools such as EPLAN or AutoCAD P&ID can help with the preliminary mapping of devices and PLCs. For example, the project IO table contains relevant data of a temperature sensor (input device) and a heater (output device). The added associated mapping starting points may include: the signal of the temperature sensor needs to be connected to the input module of the PLC, and the heater needs to be connected to the output module of the PLC.

[0033] Ensure that the mapping direction of each associated mapping starting point conforms to the device type dimension. For example, the data input direction of the sensor should be mapped to the input end of the PLC, and the control signal output direction of the actuator should be mapped to the output end of the PLC. Ensure the correct role and connection method of each device type in the system. Specifically, mapping analysis tools such as MATLAB Simulink and PLC programming tools (such as Siemens TIA Portal) can help analyze and visualize the mapping relationship between devices and PLCs. Combined with the above example, the temperature sensor is an input device, and its data signal mapping direction points to the input module of the PLC, while the heater is an output device, and its control signal is mapped to the output module of the PLC.

[0034] For each device type, extract relevant information from the instrument digital display sequence and PLC IO information set to establish a preliminary mapping relationship between the device and the PLC IO module. At this time, M associated mapping starting points are used as initial reference points to connect the input and output signals of the device with the PLC module. Specifically, data processing tools (such as Python Pandas library or Excel) can be used to process and associate these input and output information. Simulink or EPLAN can also help generate preliminary mapping relationships;

[0035] The preliminary mapping relationships between each device type and the PLC IO module are correlated to form a complete mapping relationship network, which is defined as the first mapping relationship network, showing how all devices are connected to the PLC and the signal transmission relationship between them. Then, the mapping relationship network is verified to check whether the connection between the device and the PLC module meets the industry standards and project requirements. The verification content may include the response time of the device, signal correctness, etc. Simulation tools (such as MATLAB Simulink, PLC simulation software) can be used to simulate these mapping relationships and verify them; the simulation tools are used to verify whether the signal transmission between the temperature sensor and the PLC input module is normal, and whether the control instructions between the heater and the PLC output module are correctly executed.

[0036] After the verification is completed, according to the verification results, the final matching relationship between the device and the PLC IO module is adjusted or confirmed to form the first mapping combination, which contains the specific connection methods of all devices and their corresponding PLC IO modules. Through the above steps, it is ensured that the devices in the project can be correctly connected to the PLC system, the data flow is clearly visible, and the accuracy of the mapping relationship is verified.

[0037] Further, based on the first mapping relationship network, verification is performed to determine a first mapping combination between the device and the PLC IO module. The method of the present application includes:

[0038] The first mapping relationship network is verified using a preliminary verification model, where the preliminary verification model is constructed based on industry standards; based on the preliminary verification results, mapping parameters are adjusted and system performance indicators are associated, where the system performance indicators include response time indicators, concurrency indicators, CPU usage indicators, and stability indicators; based on the preliminary verification results, the system performance indicators are used in combination with historical test cases for verification to determine a first mapping combination between the device and the PLC IO module.

[0039] Specifically, the first mapping relationship network is the network structure of the preliminary mapping relationship between the device and the PLC IO module formed through multi-dimensional association analysis. It shows how the device's signal is processed by the PLC module; the preliminary verification model is a model designed according to industry standards, which is used to verify the correctness of the first mapping relationship network, based on standards in actual applications, such as device response time, signal stability, etc.; mapping parameters are the parameters of the mapping relationship between the device and the PLC, which may include the input and output ports of the device connection, signal type, transmission frequency, etc.; system performance indicators are key indicators used to measure the system's operating efficiency and stability, including response time, concurrent processing capability, CPU usage, system stability, etc.; historical test cases are test scenarios and data previously used in similar systems or projects, which are used to verify the performance and reliability of the current system.

[0040] Execution steps: After the first mapping relationship network is generated, use the preliminary verification model built based on industry standards for verification. The goal of the verification is to ensure that the mapping relationship between the device and the PLC meets the project requirements and works within the standard range. Specifically, simulation and verification tools such as MATLAB Simulink, PLC programming tools (such as Siemens TIAPortal), EPLAN, etc. can be used. Signal transmission and logic verification can be performed according to industry standards (such as IEC 61131-3 standard). Combined with the above example, the signal transmission of the temperature sensor needs to reach the PLC within 100 milliseconds. Use simulation tools to verify whether this requirement is met. If the temperature signal takes 120 milliseconds to reach the PLC in the simulation, the connection parameters need to be adjusted.

[0041] According to the problems found during the preliminary verification process, adjust the mapping parameters between the device and the PLC, including the allocation of input and output ports, signal frequency, communication rate, etc. Specifically, use data analysis tools (such as Python, Excel) and PLC programming tools (such as Allen Bradley RSLogix) to adjust the parameters. Furthermore, if the preliminary verification finds that the signal of the temperature sensor is delayed during the mapping process, it is necessary to adjust the transmission frequency or change the connected PLC port to ensure that the signal can be transmitted in time.

[0042] The system performance indicators include response time indicators (transmission time of signals between equipment and PLC), concurrent number indicators (ability to process multiple signals simultaneously), CPU utilization indicators (processor utilization of PLC control system), stability indicators (reliability and failure rate in long-term operation). Furthermore, after the mapping parameters are adjusted, performance monitoring tools (such as Wireshark for network analysis, PLC monitoring software such as Siemens WinCC) are used to track system performance indicators and optimize according to key performance indicators. In combination with the above example, multiple sensors and actuators work simultaneously, and monitoring tools can be used to analyze the response time and concurrent processing capabilities of the system. If it is found that the system has a response time delay under high concurrency, it is necessary to further optimize the PLC configuration, which may increase hardware resources or optimize software logic.

[0043] Introduce historical test cases into the current system for testing to verify the performance of the mapping combination between the device and the PLC in various test scenarios. The test cases can cover scenarios such as normal operation, extreme load conditions, and fault handling. Specifically, historical test cases are stored in test management tools such as TestRail or JIRA, and can also be tested in combination with actual devices. PLC simulation tools (such as Siemens S7-PLCSIM) can also be used to perform these tests. In combination with the above example, historical test cases include response tests of temperature sensors under different ambient temperatures. Through simulation tests, it is verified whether the response of the temperature sensor under high temperature conditions meets the requirements; combined with system performance indicators such as response time, number of concurrency, CPU usage, and stability, the overall performance of the system is optimized, and the system performance is further verified through historical test cases to determine the mapping combination between the device and the PLC IO module, so as to ensure that the system is stable and reliable under various conditions. Multi-level verification and optimization are carried out in the above steps to determine the first mapping combination between the device and the PLC IO module, ensure that the connection between the device and the PLC in the system is accurate, and ensure that the signal transmission and control logic are stable and reliable in actual applications.

[0044] Further, by verifying the system performance indicators in combination with historical test cases, a first mapping combination between the device and the PLC IO module is determined. The method of the present application includes:

[0045] A virtual test unit is established, wherein the virtual test unit is used to simulate historical test cases, perform performance analysis and collect test results; the virtual test unit has an embedded performance evaluation framework, wherein the performance evaluation framework is used to evaluate system performance indicators of the first mapping combination.

[0046] Specifically, system performance indicators are used to measure key indicators of system performance, including response time, concurrent processing capability, CPU usage, system stability, etc. Historical test cases are test scenarios and data used in similar projects, including system performance results under different operating conditions. It is used to verify whether the performance of the current system meets the requirements; the virtual test unit is used to simulate the test structure of the real system in a simulation environment. It can run historical test cases and analyze the mapping combination performance between the device and the PLC IO module to avoid the risks brought by testing on actual hardware. Historical test cases can include the response of the device under different operating conditions, such as peak load, sudden environmental changes, etc. The performance evaluation framework is a tool embedded in the virtual test unit, which is used to evaluate the system performance of the mapping combination between the device and the PLC under simulation conditions, and judge the system performance by collecting different system performance indicators.

[0047] Execution steps: Establish a virtual test unit, that is, create a virtual environment through the software simulation platform to accurately simulate the actual connection and working process between the device and the PLC IO module. The virtual test unit can load and run historical test cases to detect the performance of the mapping combination between the device and the PLC under various conditions. The virtual environment allows the interaction of the input and output signals of the simulated device and the PLC; collect performance indicators during the simulation operation, such as response time, CPU usage, etc., to ensure that the system meets the design requirements. Specifically, you can use simulation software such as MATLAB Simulink, Siemens S7-PLCSIM or EPLAN to create a virtual test unit, simulate device input and output signals, and load historical test data for analysis.

[0048] The performance evaluation framework is the core evaluation tool in the virtual test unit. It continuously monitors and records system performance indicators during the simulation process. The performance evaluation framework determines whether the current mapping combination meets the project requirements based on preset performance thresholds, such as response time must not exceed 100 milliseconds and CPU usage must not exceed 80%. Through the collected data, the performance evaluation framework can automatically generate a performance report to show the performance of the mapping combination and point out the parts that need to be optimized. Specifically, the performance evaluation framework can be embedded in MATLAB Simulink or Siemens S7-PLCSIM to monitor system performance. Data acquisition tools such as Wireshark can be used to record performance indicators such as network delay and signal transmission time. Through the above steps, potential problems can be discovered in the early stages of project development, failures can be avoided in actual system deployment, and the overall reliability and performance of the system can be improved.

[0049] Furthermore, the performance evaluation framework is used to evaluate the system performance index of the first mapping combination, and the method of the present application includes:

[0050] Based on the performance evaluation framework, potential associated performance indicators are determined, and the potential associated performance indicators include a memory usage indicator, an error rate indicator, and a recovery time indicator; using a machine learning algorithm, the performance evaluation framework is used as a model architecture, and the potential associated performance indicators are integrated for prediction to obtain the system performance indicators of the first mapping combination; according to a preset performance threshold, it is determined whether the system performance indicators of the first mapping combination meet the project requirements; if not, a mapping parameter adjustment instruction is issued, and the mapping parameter adjustment instruction is used to return a mapping parameter node for optimization again.

[0051] Specifically, the performance evaluation framework is a tool used to monitor and analyze system performance indicators in real time. It can evaluate the overall health of the system and provide analysis reports based on these indicators. Potentially associated performance indicators are key indicators that affect performance during system operation, such as memory utilization, error rate, recovery time, etc. Memory utilization refers to the amount of memory used by the system during operation, which is usually an important measure of performance. Error rate refers to the frequency or proportion of system errors when performing tasks. Recovery time refers to the time required for the system to return to normal working state after a failure. Mapping parameter adjustment instructions automatically issue adjustment instructions for optimizing the mapping combination when system performance does not meet the standards, and adjust the parameters between the device and the PLC.

[0052] Implementation steps: Establish a performance evaluation framework to monitor the core performance parameters of the system in real time, such as memory usage, error rate, and recovery time. These performance indicators directly affect the overall performance of the system. For example, high memory usage may cause the system to respond slowly, high error rate may reduce system stability, and long recovery time may affect system continuity. Specifically, use performance monitoring software such as Nagios, Zabbix, or Prometheus to continuously collect and monitor key performance indicators during system operation.

[0053] After collecting a large amount of historical operation data, this data is input into the machine learning model, and the model predicts system performance based on the patterns of this data; by learning the correlation between potential performance indicators (such as memory usage, error rate, and recovery time), the machine learning model analyzes the complex relationship between various performance indicators to predict the performance of the mapping combination under specific conditions. For example, when the memory usage reaches a certain threshold, the error rate may increase, or the recovery time may be extended; the performance of the mapping combination is evaluated according to the performance threshold set by the project.

[0054] If certain performance indicators (such as memory usage or error rate) exceed the preset threshold, it means that the mapping combination is not suitable for the current system. The performance threshold can be set according to industry standards or specific project requirements. For example, memory usage should not exceed 80%, response time should be less than 200 milliseconds, etc.; combining the output of monitoring tools (such as Prometheus) and machine learning models, the system automatically determines whether the mapping combination meets the performance standards. For example, the traffic control system requires that the mapping combination of sensors and PLCs has a response time of no more than 100 milliseconds under extreme conditions. If the machine learning model predicts that the response time of a mapping combination is close to 120 milliseconds, the system will mark the mapping combination; if the performance of a mapping combination fails to pass the evaluation, the system will issue an automated mapping parameter adjustment instruction and return the mapping parameter node for adjustment, including adjusting the connection configuration between the device and PLC IO, signal priority, etc., and continuously adjust and optimize the mapping parameters based on the feedback data until the combination performance meets the project requirements.

[0055] In one feasible approach, the memory usage of the mapping combination of the control device and PLC under large-scale concurrent tasks; the machine learning algorithm is used to predict the memory usage when concurrent tasks increase; if the prediction results show that the memory usage may exceed 80%, a mapping parameter adjustment instruction is issued to reallocate signal processing tasks and reduce memory consumption; by adjusting the mapping parameters, the system memory usage is maintained below 70% to ensure efficient and stable operation. In the above steps, through the automated evaluation, prediction and adjustment process, the system can optimize performance in real time to ensure that the mapping combination of the device and PLC always meets the project requirements.

[0056] Furthermore, according to the basic information of the project and multiple dynamic and extensible factors, the primary adaptive structured drawings are optimized and adjusted. The application method includes:

[0057] Priority rules and interactive optimization strategies are set according to basic project information and multiple dynamically expandable factors; according to the priority rules and interactive optimization strategies, starting coordinates are set with the primary adaptive structured drawing, and a drawing optimization solution space is established; mapping parameter adjustment instructions of the first mapping combination, the second mapping combination, and the third mapping combination are associated, and directional exploration is performed in the drawing optimization solution space.

[0058] Specifically, the basic information of the project refers to all the basic data and parameters involved in the entire project, including equipment type, IO points, environmental requirements, user requirements, etc. This information provides the basic input for drawing optimization; dynamic extensible factors are parameters that may need to be adjusted in the project as time, tasks or conditions change. For example, load increase, equipment change, new functions, etc. are all extensible factors; priority rules are the rules or standards that are prioritized in the optimization process, which are key elements based on project requirements, such as response speed, resource occupation, function priority, etc.; interactive optimization strategy refers to the way in which users are allowed to interact with the system to adjust or fine-tune certain parameters during the drawing optimization process. Users can adjust the configuration recommended by the system according to actual needs; primary adaptive structured drawings are preliminary design drawings generated according to the previous steps, which contain the basic structure of the project, but have not yet been optimized and customized in detail; drawing optimization solution space refers to the range of potential solutions established for optimizing drawings, and the optimal drawing configuration is found by exploring in the solution space; mapping parameter adjustment instructions are specific operation instructions for adjusting the mapping relationship between the device and the PLC IO module to ensure the optimal parameter configuration of each module during the design process.

[0059] Execution steps: Define priority rules based on the basic information of the project (such as the type, quantity, connection relationship of the equipment, etc.) and scalable factors (such as possible new equipment, expansion requirements, etc.); priority rules can include how to handle key tasks, how to prioritize resource allocation, and which device functions to retain in the event of resource conflicts. For example, for certain high-priority devices or sensors, their signal processing will be given priority in system resource allocation. At the same time, set interactive optimization strategies to allow users to fine-tune certain key parameters during the optimization process to ensure that the drawings are more in line with actual needs. Specifically, the setting of priority rules can use rule-based optimization engines such as Drools. Such tools can automatically set optimization priorities based on project requirements; interactive optimization can use graphical interface development tools such as Qt or plug-ins for drawing design software to help users interact with the system in a visual interface.

[0060] According to the set priority rules, primary adaptive structured drawings are generated and the starting coordinates are set. The starting coordinates are the initial layout positions of the equipment and lines on the drawings, representing the basic framework of the design. On this basis, the drawing optimization solution space is established. The drawing optimization solution space represents the possible adjustment range and potential optimization direction of the drawing layout, covering all possible drawing design changes. The exploration process in the drawing optimization solution space aims to find the optimal layout. By exploring the potential layouts in different solution spaces, the optimized drawings that best suit the project requirements can be gradually found. The solution space exploration is carried out to ensure the optimal solution corresponding to the shortest path and minimum delay of signal transmission.

[0061] In the drawing optimization solution space, the parameters of each mapping combination will be optimized and adjusted according to the first mapping combination, the second mapping combination, and the third mapping combination (different mapping relationships between devices and PLC IO modules). The relationship between the mapping combinations determines how the system processes and transmits signals. Therefore, adjusting the mapping parameters is crucial. Furthermore, based on the exploration results in the solution space and combined with the mapping parameter adjustment instructions, the device position and signal connection in the drawing will be optimized. For example, if the amount of data between some sensors and PLC modules is too large, the system will automatically optimize its signal path and shorten the data transmission delay. The signal path, device position, and priority are continuously fine-tuned until the optimal drawing layout is found.

[0062] If the data flow between a sensor and the PLC module is significantly higher than other paths, it is recommended to change its signal connection method or introduce an additional caching mechanism to reduce latency and optimize overall performance. At the same time, in the setting of signal priority, the system will prioritize the signals according to real-time application requirements and data importance. For example, in the case of emergency response, the data of certain key sensors may need to be processed first to ensure timely response. Through this method, the system can dynamically adjust the signal transmission strategy to ensure that key data is delivered to the processing unit in the shortest time; in addition, the process of directed exploration will also involve simulating different configuration schemes to find the optimal drawing layout, for example, changing the relative position of the equipment to reduce the physical distance of the signal transmission, thereby reducing latency and enhancing signal quality. Such adjustments not only improve the signal transmission efficiency, but also help reduce the overall resource consumption of the system and improve sustainability.

[0063] In summary, through the directional exploration in the drawing optimization solution space, not only the optimization of device location and signal connection is achieved, but also the foundation is laid for the subsequent system maintenance and expansion, making the system more flexible and scalable. In the above steps, through the directional exploration in the drawing optimization solution space, the load balancing and signal priority optimization of the primary adaptive structured drawings are carried out to ensure that the signal transmission between different devices is more efficient and stable. At the same time, the drawing design of the project can efficiently and accurately meet dynamic needs, manage resources more effectively, and improve the overall system performance.

[0064] Furthermore, formatting is performed according to user preferences and visually outputted on a display device connected in communication. The method of the present application includes:

[0065] Obtain user preference features, which include drawing color, drawing line type, and drawing font; generate M adaptive drawing templates according to the user preference features and drawing layout rules; fill and layout the optimized and adjusted drawing contents on the basis of the M adaptive drawing templates to generate adaptive structured drawings, and display them in an interactive manner, allowing the user to zoom, translate, rotate and control layers.

[0066] Specifically, user preference characteristics refer to the user's personalized needs for drawing display, including visual features such as drawing color, drawing line type, font, etc., which determine the appearance style of the drawing and conform to the user's habits and aesthetics; drawing layout rules: the rules or standards of the drawing in terms of content layout, position arrangement, line connection, etc., to ensure that the generated drawings are both beautiful and meet the design specifications; adaptive drawing templates: drawing templates generated according to different project requirements can be adjusted according to user preference characteristics, so that the templates can adapt to different scenarios or users' personalized requirements; interactive display refers to allowing users to operate drawings on display devices, such as zooming, panning, rotating, etc., and can control the display and hiding of different layers to enhance user experience.

[0067] Execution steps: Obtain user preference characteristics through user input or system records, including drawing color, drawing line type (such as solid line, dashed line, dotted line, etc., solid line is often used for main connection, dashed line can be used for auxiliary connection or non-main equipment), drawing font; Generate multiple adaptive drawing templates (M templates) according to the preference characteristics input by the user and the established drawing arrangement rules, each template will meet the different preference characteristics of the user and meet the design specifications of the drawing in terms of layout and content arrangement.

[0068] Embed dynamic data (such as drawing content, user preference characteristics) into the template to generate the final adaptive drawing template. For example, the template engine embeds dynamic data into the predefined template to generate content that conforms to a specific format or style. Common template engines include Handlebars, Thymeleaf, etc.; fill the generated adaptive drawing template with the optimized drawing content through mapping relationships and dynamic extensible factors; during the filling and typesetting process, the system will follow the drawing layout rules and arrange the drawing content (such as equipment, connecting lines, labels, etc.) to the appropriate position according to the user's preferences; through typesetting, ensure that all parts of the drawing (such as device connections, signal paths, annotations, etc.) are clearly visible and well-structured. Specifically, use typesetting tools or graphic programming libraries, such as SVG (Scalable Vector Graphics Format) or AutoCAD Automation API is used to implement content filling and layout of vector graphics; the generated adaptive structured drawings are displayed on the display device in an interactive way, and users can perform zoom operations (view different detail levels of the drawings, for example, zoom in to view the connection details of each device), pan operations (conveniently move the viewing angle between different areas), rotation operations and layer control operations (view the connection status between a certain device and other devices or the layout of different signal paths) through the drawing operation interface to achieve efficient drawing rendering and user interaction functions.

[0069] In summary, the beneficial effects of the embodiments of the present application are:

[0070] 1. Through multi-dimensional information mapping analysis, the project's IO information, device type and signal characteristics are automatically integrated to generate accurate device connection diagrams and control logic diagrams. According to the basic information of the project and dynamic scalable factors, the drawings are automatically optimized to ensure that the drawings reflect the latest changes of the project in real time.

[0071] 2. Generate adaptive drawing templates by acquiring user preference characteristics to meet users' personalized needs in terms of color, line type, font, etc., and improve user satisfaction.

[0072] 3. Support users to perform interactive operations such as zooming, panning, and rotating the generated drawings, so that users can understand the drawing content more intuitively and improve the efficiency of information acquisition.

[0073] 4. Due to the use of setting priority rules and interactive optimization strategies based on the basic information of the project and multiple dynamic and scalable factors; according to the priority rules and interactive optimization strategies, the starting coordinates are set with the primary adaptive structured drawings, and the drawing optimization solution space is established; the mapping parameter adjustment instructions of the first mapping combination, the second mapping combination, and the third mapping combination are associated, and the directional exploration is carried out in the drawing optimization solution space. In the above steps, through the directional exploration in the drawing optimization solution space, the primary adaptive structured drawings are load balanced and signal priority optimized to ensure that the signal transmission between different devices is more efficient and stable. At the same time, the drawing design of the project can efficiently and accurately meet dynamic needs, more effectively manage resources, and improve the overall system performance.

[0074] Embodiment 2

[0075] Based on the same inventive concept as the automatic drawing generation method combining multi-dimensional integration of project information in the above-mentioned embodiment, Figure 2 As shown, the embodiment of the present application provides a drawing automatic generation device combining multi-dimensional integration of project information, wherein the device includes:

[0076] The information collection module M100 is used to collect the project IO table and project basic information. The project IO table includes device input information and device output information.

[0077] A first association mapping analysis module M200 is used to perform association mapping analysis based on the project IO table, in combination with the instrument digital display sequence and the device type dimension of the PLC IO information set, to match a first mapping combination between the device and the PLC IO module;

[0078] The second association mapping analysis module M300 is used to simultaneously perform association mapping analysis from the signal property dimension and the IO point distribution dimension, and match the second mapping combination and the third mapping combination between the device and the PLC IO module;

[0079] The logical relationship identification module M400 is used to identify the logical relationship of drawing generation according to the target drawing type and determine multiple dynamic and extensible factors that affect the drawing generation;

[0080] The drawing generation module M500 is used to call the drawing template library and generate a primary adaptive structured drawing under the constraints of the first mapping combination, the second mapping combination and the third mapping combination, wherein the primary adaptive structured drawing is in a vector graphics format;

[0081] The visualization output module M600 is used to optimize and adjust the primary adaptive structured drawings according to the basic project information and multiple dynamic expandable factors, and then format them according to user preferences and output them visually on a display device connected to the communication.

[0082] Furthermore, the first association mapping analysis module M200 is used to perform the following method:

[0083] Based on the project IO table, M association mapping starting points are added, and the mapping direction of the association mapping starting points is consistent with the device type dimension;

[0084] Through the M associated mapping starting points, preliminary mapping relationships with the instrument digital display sequence and each device type in the PLC IO information set are established to form a first mapping relationship network;

[0085] Verification is performed based on the first mapping relationship network to determine a first mapping combination between the device and the PLC IO module.

[0086] Furthermore, the first association mapping analysis module M200 is further configured to execute the following method:

[0087] Verifying the first mapping relationship network using a preliminary verification model, wherein the preliminary verification model is constructed based on industry standards;

[0088] According to the preliminary verification results, the mapping parameters are adjusted and the system performance indicators are associated, wherein the system performance indicators include response time indicator, concurrency number indicator, CPU usage indicator, and stability indicator;

[0089] On the basis of the preliminary verification result, the system performance index is used to verify the historical test cases, and the first mapping combination between the device and the PLC IO module is determined.

[0090] Furthermore, the first association mapping analysis module M200 is further configured to execute the following method:

[0091] Establishing a virtual test unit, the virtual test unit is used to simulate historical test cases, perform performance analysis and collect test results;

[0092] The virtual test unit has an embedded performance evaluation framework, and the performance evaluation framework is used to evaluate the system performance index of the first mapping combination.

[0093] Furthermore, the first association mapping analysis module M200 is further configured to execute the following method:

[0094] Based on the performance evaluation framework, determining potential related performance indicators, wherein the potential related performance indicators include a memory usage indicator, an error rate indicator, and a recovery time indicator;

[0095] Using a machine learning algorithm, taking the performance evaluation framework as a model architecture, integrating the potential associated performance indicators for prediction, and obtaining a system performance indicator of the first mapping combination;

[0096] According to a preset performance threshold, determining whether the system performance indicator of the first mapping combination meets the project requirements;

[0097] If not satisfied, a mapping parameter adjustment instruction is issued, wherein the mapping parameter adjustment instruction is used to return the mapping parameter node and perform optimization again.

[0098] Furthermore, the visual output module M600 is used to perform the following method:

[0099] Set priority rules and interactive optimization strategies based on project basic information and multiple dynamic scalable factors;

[0100] According to the priority rules and the interactive optimization strategy, the starting coordinates are set with the primary adaptive structured drawing, and the drawing optimization solution space is established;

[0101] The mapping parameter adjustment instructions of the first mapping combination, the second mapping combination, and the third mapping combination are associated to perform a directional exploration in the drawing optimization solution space.

[0102] Furthermore, the visual output module M600 is also used to execute the following method:

[0103] Acquire user preference features, wherein the user preference features include drawing color, drawing line type, and drawing font;

[0104] Generate M adaptive drawing templates according to the user preference characteristics and drawing arrangement rules;

[0105] On the basis of the M adaptive drawing templates, the optimized and adjusted drawing contents are filled and laid out to generate adaptive structured drawings, which are displayed in an interactive manner, allowing users to zoom, translate, rotate and control layers.

[0106] In summary, any step can be stored as a computer instruction or program in an unlimited computer memory, and can be called and recognized by an unlimited computer processor, and no unnecessary restrictions are made here.

[0107] Furthermore, the above-mentioned technical scheme only reflects the preferred technical scheme of the technical scheme of the embodiment of the present application. Some changes that may be made to some parts thereof by technicians in this technical field all reflect the novel principles of the embodiment of the present application. Obviously, technicians in this field can make various changes and modifications to the present application without departing from the scope of the present application.

Claims

1. A method for automatically generating drawings by combining multi-dimensional integration of project information, characterized in that: The method comprises: Collect project IO table and project basic information, the project IO table includes device input information and device output information; Based on the project IO table, combined with the instrument digital display sequence and the device type dimension of the PLC IO information set, an association mapping analysis is performed to match the first mapping combination between the device and the PLC IO module; At the same time, correlation mapping analysis is performed from the signal property dimension and IO point distribution dimension to match the second mapping combination and the third mapping combination between the device and the PLC IO module; According to the target drawing type, identify the logical relationship of drawing generation and determine multiple dynamic and extensible factors that affect drawing generation; Retrieving a drawing template library, generating a primary adaptive structured drawing under the constraints of the first mapping combination, the second mapping combination, and the third mapping combination, wherein the primary adaptive structured drawing is in a vector graphics format; and generating a primary adaptive structured drawing in a vector graphics format. The primary adaptive structured drawings are optimized and adjusted according to the basic project information and multiple dynamically extensible factors, and then formatted according to user preferences and output visually on a display device connected to the communication.

2. The method for automatically generating drawings by combining multi-dimensional integration of project information as claimed in claim 1, characterized in that: Based on the project IO table, combined with the instrument digital display sequence and the device type dimension of the PLC IO information set, an association mapping analysis is performed to match the first mapping combination between the device and the PLC IO module. The method includes: Based on the project IO table, M association mapping starting points are added, and the mapping direction of the association mapping starting points is consistent with the device type dimension; Through the M associated mapping starting points, preliminary mapping relationships with the instrument digital display sequence and each device type in the PLC IO information set are established to form a first mapping relationship network; Verification is performed based on the first mapping relationship network to determine a first mapping combination between the device and the PLC IO module.

3. The method for automatically generating drawings by combining multi-dimensional integration of project information as claimed in claim 2, characterized in that: Verifying based on the first mapping relationship network to determine a first mapping combination between a device and a PLC IO module, the method comprising: Verifying the first mapping relationship network using a preliminary verification model, wherein the preliminary verification model is constructed based on industry standards; According to the preliminary verification results, the mapping parameters are adjusted and the system performance indicators are associated, wherein the system performance indicators include response time indicator, concurrency number indicator, CPU usage indicator, and stability indicator; On the basis of the preliminary verification result, the system performance index is used to verify the historical test cases, and the first mapping combination between the device and the PLC IO module is determined.

4. The method for automatically generating drawings by combining multi-dimensional integration of project information as claimed in claim 3, characterized in that: By verifying the system performance indicator in combination with historical test cases, a first mapping combination between the device and the PLC IO module is determined, and the method includes: Establishing a virtual test unit, the virtual test unit is used to simulate historical test cases, perform performance analysis and collect test results; The virtual test unit has an embedded performance evaluation framework, and the performance evaluation framework is used to evaluate the system performance index of the first mapping combination.

5. The method for automatically generating drawings by combining multi-dimensional integration of project information as claimed in claim 4, characterized in that: The performance evaluation framework is used to evaluate the system performance index of the first mapping combination, and the method includes: Based on the performance evaluation framework, determining potential related performance indicators, wherein the potential related performance indicators include a memory usage indicator, an error rate indicator, and a recovery time indicator; Using a machine learning algorithm, taking the performance evaluation framework as a model architecture, integrating the potential associated performance indicators for prediction, and obtaining a system performance indicator of the first mapping combination; According to a preset performance threshold, determining whether the system performance indicator of the first mapping combination meets the project requirements; If not satisfied, a mapping parameter adjustment instruction is issued, wherein the mapping parameter adjustment instruction is used to return the mapping parameter node and perform optimization again.

6. The method for automatically generating drawings by combining multi-dimensional integration of project information as claimed in claim 5, characterized in that: According to the basic information of the project and a plurality of dynamically extensible factors, the primary adaptive structured drawing is optimized and adjusted, and the method includes: Set priority rules and interactive optimization strategies based on project basic information and multiple dynamic scalable factors; According to the priority rules and the interactive optimization strategy, the starting coordinates are set with the primary adaptive structured drawing, and the drawing optimization solution space is established; The mapping parameter adjustment instructions of the first mapping combination, the second mapping combination, and the third mapping combination are associated to perform a directional exploration in the drawing optimization solution space.

7. The method for automatically generating drawings by combining multi-dimensional integration of project information as claimed in claim 6, characterized in that: Formatting is performed according to user preferences and visually outputted on a display device connected in communication, the method comprising: Acquire user preference features, wherein the user preference features include drawing color, drawing line type, and drawing font; Generate M adaptive drawing templates according to the user preference characteristics and drawing arrangement rules; On the basis of the M adaptive drawing templates, the optimized and adjusted drawing contents are filled and laid out to generate adaptive structured drawings, which are displayed in an interactive manner, allowing users to zoom, translate, rotate and control layers.

8. The automatic drawing generation device combining multi-dimensional integration of project information is characterized by: The device for automatically generating drawings combined with multi-dimensional integration of project information according to any one of claims 1 to 7 comprises: An information collection module is used to collect a project IO table and basic project information, wherein the project IO table includes device input information and device output information; A first association mapping analysis module, used to perform association mapping analysis based on the project IO table, in combination with the instrument digital display sequence and the device type dimension of the PLC IO information set, to match a first mapping combination between the device and the PLC IO module; The second association mapping analysis module is used to simultaneously perform association mapping analysis from the signal property dimension and the IO point number distribution dimension, and match the second mapping combination and the third mapping combination between the device and the PLC IO module; A logical relationship identification module is used to identify the logical relationship of drawing generation according to the target drawing type and determine multiple dynamic and extensible factors that affect drawing generation; A drawing generation module, used for calling a drawing template library, and generating a primary adaptive structured drawing under the constraints of the first mapping combination, the second mapping combination, and the third mapping combination, wherein the primary adaptive structured drawing is in a vector graphics format; The visual output module is used to optimize and adjust the primary adaptive structured drawings according to the basic information of the project and multiple dynamically extensible factors, and then format them according to user preferences and output them visually on a display device connected to the communication.

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