Electrical design and debugging integrated intelligent platform and implementation method

Abstract

The invention discloses an electrical design and debugging integrated intelligent platform and an implementation method. Comprising the steps of setting a data model of electrical design debugging; the method comprises the following steps: mapping design data generated based on an electrical logic diagram before debugging to obtain initial debugging data; the simulation model and the physical equipment are connected, a semi-physical simulation environment is constructed, variables of the simulation model and physical signals of the physical equipment are fused during debugging, and debugging data are obtained and updated; performing inverse mapping on the updated debugging data to obtain updated design data, and obtaining an updated electrical logic diagram based on the updated data; and based on the diagnosis knowledge in the data model library, an intelligent diagnosis module is adopted to diagnose the debugging data updated during debugging to obtain new diagnosis data. Design and debugging integration of electrical development is realized, and the intelligent level of fault diagnosis is improved.

Description

Technical Field

[0001] This invention relates to the field of electrical design and commissioning automation technology, and in particular to an intelligent platform method and implementation method that integrates electrical design and commissioning. Background Technology

[0002] In existing electrical system development processes, design and debugging, such as PLC debugging and field testing, are typically completed independently using different tools. This separate development model has the following technical drawbacks: First, data fragmentation: design data and debugging parameters need to be manually converted, which can easily lead to version inconsistencies; second, low efficiency: the debugging phase requires repeated switching between software tools and hardware devices, extending the development cycle; third, experience dependence: fault diagnosis relies on engineers' experience and lacks intelligent decision support based on historical data; fourth, insufficient real-time anomaly detection: traditional simulation tools cannot be synchronously verified with physical devices, making it difficult to capture dynamic anomalies. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide an intelligent platform and implementation method for integrated electrical design and debugging, with the aim of realizing integrated design and debugging of electrical development and improving the level of intelligent fault diagnosis.

[0004] To achieve the above objectives, according to a first aspect of the present invention, an intelligent platform integrating electrical design and commissioning is provided, comprising:

[0005] A data model library is used to set up data models for electrical design and commissioning, and to uniformly store, update, and manage design data, commissioning data, diagnostic data, and diagnostic knowledge for electrical design and commissioning based on the data models.

[0006] The design and debugging collaboration engine communicates with the data model library and is used to synchronize the design data and the debugging data in the data model library.

[0007] The virtual-real fusion debugging module communicates with the data model library and includes a program interface for connecting the simulation model and a physical interface for connecting the physical device. During debugging, the virtual-real fusion debugging module fuses the variables of the simulation model and the physical signals of the physical device and stores the debugging data in the data model library.

[0008] The intelligent diagnostic module is communicatively connected to the data model library. It is used to form diagnostic knowledge based on the stored design data, debugging data, and diagnostic data, diagnose new design data based on the diagnostic knowledge, and store the new diagnostic data in the data model library.

[0009] Furthermore, the physical devices include a motor PLC controller and sensors, the design data includes an electrical logic diagram, and the debugging data includes a variable mapping table, IO configuration, and debugging code.

[0010] Furthermore, the design and debugging collaboration engine includes a logic mapper, a code generator, and a bidirectional synchronizer;

[0011] The logic mapper parses the various components in the electrical logic diagram and the connection relationships between the components, mapping them into the corresponding variable mapping table, IO configuration, and PLC program framework;

[0012] The code generator generates PLC program code based on the variable mapping table obtained by the logic mapper, the IO configuration, and the PLC program framework.

[0013] The bidirectional synchronizer detects modifications made to the variable mapping table and the PLC program code during debugging, and synchronizes the confirmed modifications with the electrical logic diagram.

[0014] Furthermore, the virtual-real fusion debugging module maintains a signal mapping table in the physical interface. The signal mapping table sets the mapping relationship between the variables in the simulation model and the I / O addresses of the physical device. In each debugging cycle, the data fusion between the simulation model and the physical device is completed to obtain the debugging data.

[0015] Furthermore, the simulation model includes a simulation model built in MATLAB based on the electrical logic diagram or a simulation model built in Simulink; the design data includes design data from EPLAN software, and the debugging data includes running parameters from TIAPortal software.

[0016] According to a second aspect of the present invention, an integrated method for electrical design and commissioning is provided, comprising:

[0017] An electrical design and commissioning data model is set in the data model library, and the data model includes the relationship between the design data and the commissioning data of the electrical design and commissioning.

[0018] Using the aforementioned design and debugging collaboration engine, the design data generated based on the electrical logic diagram is mapped before debugging to obtain the initial debugging data;

[0019] The virtual-real fusion debugging module connects the simulation model and physical devices to build a semi-physical simulation environment. During debugging, the variables of the simulation model and the physical signals of the physical devices are fused to update the debugging data in the data model library.

[0020] The design and debugging collaboration engine is used to reverse map the updated debugging data to obtain the updated design data, and the updated electrical logic diagram is obtained based on the updated data; furthermore, based on the diagnostic knowledge in the data model library, the intelligent diagnostic module is used to diagnose the updated debugging data during debugging to obtain new diagnostic data.

[0021] Furthermore, based on the diagnostic knowledge in the data model library, the intelligent diagnostic module is used to diagnose the debugging data updated during debugging, obtaining new diagnostic data, including:

[0022] The time-frequency domain features of the physical signal in the debugging data are extracted according to a preset sliding window.

[0023] The extracted time-frequency domain features are matched with the fault time-frequency domain features in the diagnostic knowledge, and it is determined whether the matching degree exceeds a preset threshold.

[0024] In response to the similarity exceeding a preset threshold, the intelligent diagnostic module performs root cause analysis on the fault based on the root cause knowledge in the diagnostic knowledge, generates the diagnostic data, and the diagnostic data includes optimization suggestions for the topology or component parameters of the electrical logic diagram, and stores the confirmed optimization suggestions as the diagnostic knowledge.

[0025] Furthermore, the matching degree is cosine similarity.

[0026] Furthermore, the method also includes generating the diagnostic knowledge based on the stored design data, debugging data, and diagnostic data.

[0027] Furthermore, a pre-trained neural network is used to classify and analyze the stored design data, debugging data, and diagnostic data to generate the diagnostic knowledge.

[0028] The embodiments of the present invention have at least one of the following advantages or beneficial effects:

[0029] This invention, through the construction of an intelligent platform integrating electrical design and commissioning and its implementation method, achieves efficient integration and intelligent management of the entire electrical system development process.

[0030] The embodiments of the present invention use a data model library to uniformly store, update and manage design data, debugging data, diagnostic data and diagnostic knowledge for electrical design and debugging, making data management more standardized and systematic, improving data integrity and consistency, and solving the problem of data fragmentation in the prior art.

[0031] The embodiments of the present invention achieve real-time synchronization between design data and debugging data through a design-debugging collaboration engine. By updating and synchronizing, manual intervention is reduced, and the problems of version confusion and high error rate caused by manual conversion between design data and debugging data are avoided.

[0032] This invention employs a virtual-physical fusion debugging module to connect the simulation model and physical devices, constructing a semi-physical simulation environment. It fuses the virtual signals of the simulation model with the physical signals of the physical devices, achieving seamless integration between virtual simulation and physical debugging. This fusion method can verify the correctness of the design logic in real time, identify potential problems in advance, and reduce the complexity and risk of on-site debugging.

[0033] In this embodiment of the invention, debugging data is updated to the data model library during the debugging process, providing accurate data support for subsequent diagnosis and optimization, and significantly improving debugging efficiency and accuracy.

[0034] In this embodiment of the invention, a diagnostic knowledge base is generated by an intelligent diagnostic module using stored design data, debugging data, and diagnostic data. Data mining and machine learning algorithms (such as pre-trained neural networks) are then used to perform diagnostic analysis on the debugging data to obtain diagnostic knowledge.

[0035] The diagnostic knowledge in this invention includes not only fault characteristics but also root cause knowledge, enabling optimization suggestions for the topology or component parameters of the electrical logic diagram based on this root cause knowledge. These optimization suggestions, once confirmed, are stored as new diagnostic knowledge, further enriching the knowledge base and achieving self-evolution and accumulation of diagnostic knowledge, thereby improving the platform's intelligence level and fault handling capabilities.

[0036] This invention, through the mapping and synchronization of design data and debugging data, combined with real-time feedback from the intelligent diagnostic module, forms a closed-loop control throughout the entire process from design to debugging and optimization. This closed-loop mechanism can quickly respond to design changes and debugging feedback, significantly shorten the development cycle, and reduce development costs.

[0037] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained through the details specifically pointed out in the description and drawings. Attached Figure Description

[0038] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0039] Figure 1 This is a schematic diagram of the main components of the intelligent platform integrating electrical design and commissioning according to an embodiment of the present invention;

[0040] Figure 2 This is a schematic diagram illustrating an application scenario of the intelligent platform integrating electrical design and commissioning according to an embodiment of the present invention;

[0041] Figure 3 This is a schematic diagram of the main process of an intelligent platform method integrating electrical design and commissioning according to another embodiment of the present invention. Detailed Implementation

[0042] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0043] Understandably, the development process of an electrical system refers to the various stages from conceptualization to formal system operation, generally including engineering phases such as requirements analysis and planning, electrical design, electrical commissioning, and delivery and maintenance. Electrical design is the blueprint planning phase of the electrical system. Based on theoretical calculations and standards, it involves the logical conceptualization, functional definition, and static description of the entire system in a drawing or software environment. This typically includes drawing electrical schematics, selecting components, and physical layout. Electrical commissioning is the practical verification phase of the electrical system. In a field or simulation environment, the design blueprint is implemented, and dynamic testing is used to verify, correct, and ensure the system operates stably as expected. This generally includes hardware and software deployment and configuration, single-device testing, system integration testing, fault diagnosis, and adjustments and optimizations.

[0044] The design and commissioning phases of existing electrical systems are usually completed independently using different tools. For example, the design phase uses professional electrical design tools such as AutoCAD Electrical and EPLAN, while the commissioning phase uses PLC programming and commissioning platforms such as TIA Portal and mathematical model simulation environments such as MATLAB / Simulink. This leads to problems such as data fragmentation, low efficiency, reliance on experience, and insufficient real-time anomaly detection.

[0045] To address the problems in the prior art, embodiments of the present invention provide an intelligent platform and a method for integrating electrical design and debugging, thereby realizing the integration of electrical development design and debugging and improving the level of intelligent fault diagnosis.

[0046] Example 1

[0047] This embodiment is used to describe in detail an intelligent platform integrating electrical design and debugging according to the first aspect of the present invention.

[0048] Figure 1 This is a schematic diagram of the main components of the intelligent platform integrating electrical design and commissioning according to an embodiment of the present invention. Figure 1 As shown, the intelligent platform integrating electrical design and debugging in this embodiment of the present invention includes a data model library, a design and debugging collaboration engine, a virtual-real fusion debugging module, and an intelligent diagnostic module.

[0049] A data model library is used to set up data models for electrical design and commissioning, and to uniformly store, update, and manage design data, commissioning data, diagnostic data, and diagnostic knowledge for electrical design and commissioning based on the data models.

[0050] The design and debugging collaboration engine communicates with the data model library and is used to synchronize the design data and the debugging data in the data model library.

[0051] The virtual-real fusion debugging module communicates with the data model library and includes a program interface for connecting the simulation model and a physical interface for connecting the physical device. During debugging, the virtual-real fusion debugging module fuses the variables of the simulation model and the physical signals of the physical device and stores the debugging data in the data model library.

[0052] The intelligent diagnostic module is communicatively connected to the data model library. It is used to form diagnostic knowledge based on the stored design data, debugging data, and diagnostic data, diagnose new design data based on the diagnostic knowledge, and store the new diagnostic data in the data model library.

[0053] Figure 2 This is a schematic diagram illustrating an application scenario of the intelligent platform integrating electrical design and commissioning according to an embodiment of the present invention. Specifically, for example... Figure 2 As shown, the intelligent platform integrating electrical design and debugging in this embodiment of the invention seamlessly connects with existing design and debugging software. Design data from software such as EPLAN, as well as debugging data from software such as TIA Portal and MATLAB / Simulink, ensure that all data are from the same source, consistent, and version controllable.

[0054] Specifically, in this embodiment and some embodiments of the present invention, the physical device includes a PLC controller and sensors for devices such as motors.

[0055] Specifically, it communicates with design software such as EPLAN and debugging software such as TIA Portal through the design and debugging collaboration engine, and communicates with simulation software such as MATLAB / Simulink, PLC controllers and sensors through the virtual-real fusion debugging module.

[0056] Specifically, in this embodiment and some embodiments of the present invention, the design data includes an electrical logic diagram, and the debugging data includes a variable mapping table, I / O configuration, and debugging code. The design debugging collaboration engine includes a logic mapper, a code generator, and a bidirectional synchronizer.

[0057] The logic mapper parses the various components in the electrical logic diagram and the connection relationships between the components, and maps them into the corresponding variable mapping table, IO configuration and PLC program framework;

[0058] The code generator generates PLC program code based on the variable mapping table obtained by the logic mapper, the IO configuration, and the PLC program framework;

[0059] A bidirectional synchronizer detects modifications made to the variable mapping table and the PLC program code during debugging, and synchronizes the confirmed modifications with the electrical logic diagram.

[0060] Specifically, in this embodiment and some embodiments of the present invention, the virtual-real fusion debugging module maintains a signal mapping table in the physical interface. This signal mapping table sets the mapping relationship between the variables in the simulation model and the I / O addresses of the physical device. Within each debugging cycle, it completes the data fusion between the simulation model and the physical device to obtain the debugging data. For example, the signal mapping table predefines the correspondence between each output variable (e.g., "motor speed") in the simulation model and each input address (e.g., "IW104") of the PLC controller, and the correspondence between each output address (e.g., "QW108") of the PLC controller and each input variable (e.g., "start command") in the simulation model. Based on this table, the virtual-real fusion debugging module automatically performs data transfer, format conversion, and routing within each communication cycle. This enables high-precision synchronization (e.g., synchronization error <2ms) between virtual variables and hardware feedback signals, thereby verifying dynamic operating conditions in a near-realistic environment.

[0061] Specifically, in this embodiment and some embodiments of the present invention, the simulation model includes a simulation model built in MATLAB based on the electrical logic diagram or a simulation model built in Simulink; the design data includes design data from EPLAN software, and the debugging data includes running parameters from TIA Portal software.

[0062] Specifically, in this embodiment and some embodiments of the present invention, the intelligent diagnostic module uses diagnostic knowledge from the data model library, including structured stored fault characteristics, root cause knowledge, and design optimization suggestions. It can be understood that the intelligent platform of this embodiment constructs a closed-loop knowledge base from anomaly detection and root cause analysis to design source optimization, not only solving current faults but also striving to prevent the recurrence of similar problems through a data-driven approach and continuously optimizing diagnostic knowledge.

[0063] More specifically, in this embodiment and some embodiments of the present invention, each record of diagnostic knowledge includes fault characteristics, root cause knowledge, and design optimization suggestions. Fault characteristics include fault timing data snapshots, fault time-frequency domain characteristics, alarm codes, and device status words. Root cause knowledge includes the design drawing number, component model, schematic diagram segment, I / O address, and environmental information corresponding to the faulty device or circuit; further, environmental information includes the operating load and runtime at the time of the fault. Design optimization suggestions include ultimately verified effective maintenance steps, parameter adjustment values ​​(such as PID parameters), or component replacement records.

[0064] Specifically, the intelligent platform in this embodiment and some embodiments of the present invention dynamically constructs and enriches diagnostic knowledge in three ways. First, expert experience is solidified: the diagnostic logic of senior engineers is entered into the data model library in the form of rules. Second, data mining is used, employing big data algorithms to mine historical fault data in the data model library, automatically discovering implicit correlations between frequently co-occurring fault modes and design parameters (e.g., "when using a model A contactor to drive a model B motor, the probability of its starting current exceeding the limit increases significantly"). The system monitors continuous time-series data streams from the equipment in real time (such as current and vibration signals). Third, a sliding window technique is used to calculate the time-domain characteristics (mean, variance, peak value, waveform factor) and frequency-domain characteristics (main spectrum components extracted through Fast Fourier Transform, FFT) of the data within the window in real time, comparing and matching them with historical fault data (e.g., using Dynamic Time Warping (DTW) algorithm or cosine similarity) to discover new diagnostic knowledge.

[0065] Furthermore, the intelligent platform in this embodiment and some embodiments of the present invention can also automatically generate diagnostic reports using a large language model, clearly pointing out the most likely root cause (e.g., "The three-phase current of the motor is unbalanced, and the root cause is most likely that the power supply terminal is loose"), and directly associate it with the specific location in the design drawings, such as highlighting the corresponding circuit.

[0066] Understandably, the intelligent platform in this embodiment and some embodiments of the present invention can identify certain inherently vulnerable design patterns by analyzing a large number of similar fault cases. For example, when diagnostic knowledge analysis reveals that a certain circuit topology (such as "direct turn-off of inductive load without buffer circuit") causes contact erosion during multiple debugging sessions, the system will automatically generate a design optimization suggestion: suggesting "adding an RC absorption circuit" to the schematic diagram. The optimization suggestion is then pushed for confirmation: the optimization scheme is stored as a new diagnostic knowledge in the intelligent platform's data model library. After confirmation and storage, when a similar topology is used again in a future project, the intelligent platform will automatically prompt for the optimization suggestion, preventing the problem from recurring at its source.

[0067] Example 2

[0068] This embodiment is used to illustrate in detail a method for integrating electrical design and commissioning according to the second aspect of the present invention.

[0069] Figure 3 This is a schematic diagram of the main components of the intelligent platform integrating electrical design and commissioning according to an embodiment of the present invention. Figure 3 As shown, the integrated electrical design and commissioning method of the present invention in this embodiment includes steps S301 to S304.

[0070] Step S301: Set up a data model for electrical design and commissioning in the data model library. The data model includes the relationship between the design data and the commissioning data of electrical design and commissioning.

[0071] Step S302: Using the design and debugging collaboration engine, the design data generated based on the electrical logic diagram is mapped before debugging to obtain the initial debugging data;

[0072] Step S303: Connect the simulation model and physical device through the virtual-real fusion debugging module to build a semi-physical simulation environment. During debugging, fuse the variables of the simulation model and the physical signals of the physical device to update the debugging data in the data model library.

[0073] Step S304: The updated debugging data is reverse-mapped using the design and debugging collaboration engine to obtain updated design data, and an updated electrical logic diagram is obtained based on the updated data; furthermore, based on the diagnostic knowledge in the data model library, the intelligent diagnostic module is used to diagnose the updated debugging data during debugging to obtain new diagnostic data.

[0074] Specifically, in this embodiment and some embodiments of the present invention, step S304 involves using the intelligent diagnostic module to diagnose the updated debugging data based on the diagnostic knowledge in the data model library to obtain new diagnostic data, including steps S304a to S304c.

[0075] Step S304a: Extract the time-frequency domain features of the physical signal in the debugging data according to the preset sliding window;

[0076] Step S304b: Perform similarity matching between the extracted time-frequency domain features and the fault time-frequency domain features in the diagnostic knowledge, and determine whether the obtained matching degree exceeds a preset threshold.

[0077] In step S304c, in response to the similarity exceeding a preset threshold, the intelligent diagnostic module performs root cause analysis on the fault based on the root cause knowledge in the diagnostic knowledge, generates the diagnostic data, and the diagnostic data includes optimization suggestions for the topology or component parameters of the electrical logic diagram, and stores the confirmed optimization suggestions as the diagnostic knowledge.

[0078] Specifically, in this embodiment and some embodiments of the present invention, the matching degree is cosine similarity.

[0079] Specifically, in this embodiment and some embodiments of the present invention, the method further includes: generating the diagnostic knowledge based on the stored design data, the debugging data, and the diagnostic data.

[0080] Specifically, in this embodiment and some embodiments of the present invention, a pre-trained neural network is used to classify and analyze the stored design data, debugging data and diagnostic data to generate the diagnostic knowledge.

[0081] Understandably, in this embodiment and some embodiments of the present invention, training the neural network involves using historical data (design, debugging, and diagnosis) as training samples. This allows the neural network to learn the complex mapping relationships between hidden fault modes and design / debugging parameters, thereby forming an intelligent module capable of automatically identifying potential problems and summarizing diagnostic knowledge. Specifically, in this embodiment and some embodiments of the present invention, the neural network training employs existing training methods. The training steps include dataset preparation and preprocessing, model construction including loss functions and training algorithms, and model training.

[0082] Based on the above detailed description of the embodiments of the present invention, it can be more clearly understood that the present invention has the following advantages:

[0083] This invention, through the construction of an intelligent platform integrating electrical design and commissioning and its implementation method, achieves efficient integration and intelligent management of the entire electrical system development process.

[0084] The embodiments of the present invention use a data model library to uniformly store, update and manage design data, debugging data, diagnostic data and diagnostic knowledge for electrical design and debugging, making data management more standardized and systematic, improving data integrity and consistency, and solving the problem of data fragmentation in the prior art.

[0085] The embodiments of the present invention achieve real-time synchronization between design data and debugging data through a design-debugging collaboration engine. By updating and synchronizing, manual intervention is reduced, and the problems of version confusion and high error rate caused by manual conversion between design data and debugging data are avoided.

[0086] This invention employs a virtual-physical fusion debugging module to connect the simulation model and physical devices, constructing a semi-physical simulation environment. It fuses the virtual signals of the simulation model with the physical signals of the physical devices, achieving seamless integration between virtual simulation and physical debugging. This fusion method can verify the correctness of the design logic in real time, identify potential problems in advance, and reduce the complexity and risk of on-site debugging.

[0087] In this embodiment of the invention, debugging data is updated to the data model library during the debugging process, providing accurate data support for subsequent diagnosis and optimization, and significantly improving debugging efficiency and accuracy.

[0088] In this embodiment of the invention, a diagnostic knowledge base is generated by an intelligent diagnostic module using stored design data, debugging data, and diagnostic data. Data mining and machine learning algorithms (such as pre-trained neural networks) are then used to perform diagnostic analysis on the debugging data to obtain diagnostic knowledge.

[0089] The diagnostic knowledge in this invention includes not only fault characteristics but also root cause knowledge, enabling optimization suggestions for the topology or component parameters of the electrical logic diagram based on this root cause knowledge. These optimization suggestions, once confirmed, are stored as new diagnostic knowledge, further enriching the knowledge base and achieving self-evolution and accumulation of diagnostic knowledge, thereby improving the platform's intelligence level and fault handling capabilities.

[0090] This invention, through the mapping and synchronization of design data and debugging data, combined with real-time feedback from the intelligent diagnostic module, forms a closed-loop control throughout the entire process from design to debugging and optimization. This closed-loop mechanism can quickly respond to design changes and debugging feedback, significantly shorten the development cycle, and reduce development costs.

[0091] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0092] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. An intelligent platform integrating electrical design and commissioning, characterized in that, include: A data model library is used to set up data models for electrical design and commissioning, and to uniformly store, update, and manage design data, commissioning data, diagnostic data, and diagnostic knowledge for electrical design and commissioning based on the data models. The design and debugging collaboration engine communicates with the data model library and is used to synchronize the design data and the debugging data in the data model library. The virtual-real fusion debugging module communicates with the data model library and includes a program interface for connecting the simulation model and a physical interface for connecting the physical device. During debugging, the virtual-real fusion debugging module fuses the variables of the simulation model and the physical signals of the physical device and stores the debugging data in the data model library. The intelligent diagnostic module is communicatively connected to the data model library. It is used to form diagnostic knowledge based on the stored design data, debugging data, and diagnostic data, diagnose new design data based on the diagnostic knowledge, and store the new diagnostic data in the data model library.

2. The platform according to claim 1, characterized in that, The physical devices include a motor PLC controller and sensors, the design data includes an electrical logic diagram, and the debugging data includes a variable mapping table, IO configuration, and debugging code.

3. The platform according to claim 2, characterized in that, The design and debugging collaboration engine includes a logic mapper, a code generator, and a bidirectional synchronizer; The logic mapper parses the various components in the electrical logic diagram and the connection relationships between the components, mapping them into the corresponding variable mapping table, IO configuration, and PLC program framework; The code generator generates PLC program code based on the variable mapping table obtained by the logic mapper, the IO configuration, and the PLC program framework. The bidirectional synchronizer detects modifications made to the variable mapping table and the PLC program code during debugging, and synchronizes the confirmed modifications with the electrical logic diagram.

4. The method according to claim 3, characterized in that, The virtual-real fusion debugging module maintains a signal mapping table in the physical interface. The signal mapping table sets the mapping relationship between the variables in the simulation model and the I / O addresses of the physical device. In each debugging cycle, the data fusion between the simulation model and the physical device is completed to obtain the debugging data.

5. The method according to any one of claims 1-4, characterized in that, The simulation model includes a simulation model built in MATLAB based on the electrical logic diagram or a simulation model built in Simulink; the design data includes design data from EPLAN software, and the debugging data includes running parameters from TIAPortal software.

6. A method for integrating electrical design and debugging, applied to the intelligent platform as described in any one of claims 1-5, characterized in that... include: An electrical design and commissioning data model is set in the data model library, and the data model includes the relationship between the design data and the commissioning data of the electrical design and commissioning. Using the aforementioned design and debugging collaboration engine, the design data generated based on the electrical logic diagram is mapped before debugging to obtain the initial debugging data; The virtual-real fusion debugging module connects the simulation model and physical devices to build a semi-physical simulation environment. During debugging, the variables of the simulation model and the physical signals of the physical devices are fused to update the debugging data in the data model library. The design and debugging collaboration engine is used to reverse map the updated debugging data to obtain the updated design data, and the updated electrical logic diagram is obtained based on the updated data; furthermore, based on the diagnostic knowledge in the data model library, the intelligent diagnostic module is used to diagnose the updated debugging data during debugging to obtain new diagnostic data.

7. The method according to claim 6, characterized in that, Based on the diagnostic knowledge in the data model library, the intelligent diagnostic module is used to diagnose the debugging data updated during debugging, and new diagnostic data is obtained, including: The time-frequency domain features of the physical signal in the debugging data are extracted according to a preset sliding window. The extracted time-frequency domain features are matched with the fault time-frequency domain features in the diagnostic knowledge, and it is determined whether the matching degree exceeds a preset threshold. In response to the similarity exceeding a preset threshold, the intelligent diagnostic module performs root cause analysis on the fault based on the root cause knowledge in the diagnostic knowledge, generates the diagnostic data, and the diagnostic data includes optimization suggestions for the topology or component parameters of the electrical logic diagram, and stores the confirmed optimization suggestions as the diagnostic knowledge.

8. The method according to claim 7, characterized in that, The matching degree is cosine similarity.

9. The method according to claim 6, characterized in that, The method further includes: The diagnostic knowledge is generated based on the stored design data, debugging data, and diagnostic data.

10. The method according to claim 9, characterized in that, Generating diagnostic knowledge based on the stored design data, debugging data, and diagnostic data includes: using a pre-trained neural network to classify and analyze the stored design data, debugging data, and diagnostic data to generate the diagnostic knowledge.

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