Method and system for generating printed circuit board design drawings

Abstract

The present invention relates to the technical field of data mining, and in particular to a method and system for generating a printed circuit board design drawing. The method comprises the following steps: obtaining customer requirements and structuring them into circuit board design requirement data, and then performing pattern clustering to obtain design requirement pattern data; obtaining historical design logs, and based on this, performing circuit board hierarchical design clustering to obtain historical hierarchical design data, and then performing wiring structure topology analysis to form a wiring structure model set; quantifying wiring requirements, obtaining wiring requirement data based on demand pattern data, and matching the hierarchical wiring structure model set to form a matching model; laying out components, performing component layout on the matching wiring structure model, generating component layout data, and planning the direction of signal lines to form a hierarchical structure model; electromagnetic interference simulation, optimizing the hierarchical structure model based on simulation data to balance heat flow, and finally generating a circuit board design drawing. The present invention can improve the efficiency of circuit board design.

Description

Technical Field

[0001] The present invention relates to the technical field of data mining, and in particular to a method and system for generating a printed circuit board design drawing. Background Art

[0002] Printed Circuit Board (PCB) is a core component in modern electronic devices and is widely used in consumer electronics, communications, automobiles, medical and other fields. As electronic products develop towards miniaturization, high performance and multi-functions, the complexity of PCB design has increased significantly. The early PCB design process mainly relied on manual experience and manual drawing, which was not only inefficient but also prone to design errors. In the past few decades, PCB design technology has undergone significant progress. From early two-dimensional manual drawing to later computer-aided design (CAD), the evolution of technology has provided designers with more powerful tools. However, with the increase in circuit density and the improvement of signal integrity requirements, the existing PCB design process cannot comprehensively consider the heat distribution and wiring complexity of the PCB, resulting in generally low PCB design efficiency. Summary of the invention

[0003] Based on this, it is necessary for the present invention to provide a method and system for generating a printed circuit board design drawing to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for generating a printed circuit board design drawing comprises the following steps:

[0005] Step S1: Acquire customer demand data, and structure circuit board design demand according to the customer demand data, thereby obtaining circuit board design demand data; cluster the circuit board design demand data into design demand patterns, thereby obtaining circuit board design demand pattern data;

[0006] Step S2: Obtain the historical design log of the circuit board, and perform circuit board hierarchical design clustering according to the historical design log of the circuit board, so as to obtain the historical circuit board hierarchical design data; perform circuit board hierarchical wiring structure topology analysis based on the historical circuit board hierarchical design data, so as to obtain the circuit board hierarchical wiring structure model set;

[0007] Step S3: quantifying the wiring requirements of the circuit board based on the circuit board design requirement model data, thereby obtaining the wiring requirement data of the circuit board, and matching the wiring structure of the circuit board hierarchical wiring structure model set with the wiring structure of the circuit board according to the wiring requirement data of the circuit board, thereby obtaining the matching wiring structure model of the circuit board;

[0008] Step S4: Layout the circuit board components on the circuit board matching hierarchical wiring structure model according to the circuit board design requirement data, thereby obtaining circuit board hierarchical component layout data; plan the signal line direction of the circuit board components on the circuit board matching hierarchical wiring structure model according to the circuit board hierarchical component layout data, thereby obtaining the circuit board hierarchical structure model;

[0009] Step S5: Perform electromagnetic interference simulation on the circuit board hierarchical structure model to obtain electromagnetic interference simulation data, and optimize the hierarchical structure thermal flow balance of the circuit board hierarchical structure model based on the electromagnetic interference simulation data to obtain the circuit board optimized structure model; perform circuit board design drawing parameter description on the circuit board optimized structure model to obtain the printed circuit board design drawing.

[0010] The present invention can more accurately understand and meet the requirements of specific customers through structured customer demand data, so as to design products that better meet market demand. Clustering technology can identify similar design demand patterns and provide references for designers, thereby reducing personalized differences in design and improving design efficiency and consistency. Through data clustering and analysis of historical designs, for similar design requirements, past successful cases can be used as reference, thereby reducing design errors and design cycles and improving the quality of preliminary designs. Through topological analysis of hierarchical wiring structures, effective layout structures can be obtained, thereby providing a good reference for subsequent designs and ensuring higher signal integrity and electrical performance. Quantifying wiring requirements can help designers make more scientific decisions, avoid over-design or under-design, and make circuit boards more performance and cost-effective. By matching the hierarchical wiring structure model, the compatibility of new designs in existing structures can be guaranteed, thereby improving wiring efficiency and reducing the number of modifications. Reasonable component layout and signal line planning can effectively reduce signal interference and delay, and improve the signal transmission quality of the overall circuit. Through fine layout design, the space of PCB can be better utilized, which helps to achieve miniaturized design and meet the trend of miniaturization of modern electronic products. Through electromagnetic interference simulation, possible electromagnetic compatibility problems can be identified in the early stages of design, reducing the cost and time of later modifications. Hierarchical structure heat flow balance optimization can improve the thermal performance of PCB, reduce the failure rate caused by overheating, extend the product life, and improve product reliability. Combining the above steps, through scientific data analysis, historical experience learning, quantitative evaluation, component layout optimization, electromagnetic and thermal simulation and other methods, the overall efficiency and effect of PCB design have been significantly improved. This not only helps designers improve the scientificity and effectiveness of the design, but also to a certain extent meets the market demand for high-performance, low-cost electronic products and achieves sustainable development.

[0011] Optionally, step S1 specifically includes:

[0012] Step S11: obtaining customer demand data, and cleaning the missing values ​​of the customer demand data, thereby obtaining cleaned customer demand data;

[0013] Step S12: classifying the cleaning customer demand data into customer demand data, thereby obtaining electrical characteristic demand data and physical size demand data;

[0014] Step S13: Performing physical dimension requirement structural modeling according to the physical dimension requirement data, thereby obtaining a physical dimension structure model;

[0015] Step S14: structurally integrating the electrical characteristic requirement data into circuit board design requirement data according to the physical size structure model, thereby obtaining circuit board design requirement data;

[0016] Step S15: clustering the circuit board design requirement patterns to obtain circuit board design requirement pattern data.

[0017] The present invention can ensure that the data based on which subsequent analysis and decision-making are based is more complete and accurate by cleaning missing values ​​of customer demand data. Cleaning missing values ​​can avoid deviations in the analysis process and make the analysis results more reliable. By obtaining clean data, the real needs of customers can be better identified, so as to formulate more targeted strategies. Dividing the needs into two categories, electrical characteristics and physical dimensions, can help the team identify key needs more clearly, which is helpful for subsequent design formulation. Classification can make the analysis and design links more systematic, which is convenient for different teams to conduct in-depth analysis and optimization for specific needs. After clear classification, resources and time can be allocated more reasonably, and efforts can be concentrated on solving the most critical demand problems. Structured modeling of physical size requirements can create a set of standardized design reference models, which is convenient for the execution and standardization of subsequent work. The structured model enables the design to quickly verify whether it meets customer needs in the subsequent design process, reducing the risk of design changes. The standardized model enables different departments such as R&D and production to work better together and improve overall efficiency. Integrating the needs of both parties can ensure that the circuit board design fully considers the physical and electrical characteristics and forms a comprehensive design solution. Through system integration, potential design conflicts can be identified in advance and the cost of later modifications can be reduced. After verifying the integration of requirements, the circuit board design can directly enter the implementation stage, improving the efficiency of project advancement. Through pattern clustering, the commonalities and trends in design requirements can be identified, helping the team to better understand market demand. The clustering results can provide a reference for the design team to optimize the circuit board design solution and enhance the market competitiveness of the product. By analyzing different patterns, the design team can discover potential innovations and promote the development of new products and the application of new technologies.

[0018] Optionally, step S14 is specifically:

[0019] Step S141: acquiring historical electrical simulation data of the circuit board, and extracting simulation parameter combinations from the historical electrical simulation data of the circuit board, thereby obtaining simulation physical parameter combinations and simulation electrical parameter combinations;

[0020] Step S142: performing physical-electrical characteristic correlation analysis on the simulated physical parameter combination and the simulated electrical parameter combination, thereby obtaining physical-electrical characteristic correlation data;

[0021] Step S143: mapping the physical dimension structure model and the electrical characteristic requirement data according to the physical-electrical characteristic association data, thereby obtaining a circuit board requirement structured model;

[0022] Step S144: Structuring the circuit board design requirement model to obtain circuit board design requirement data.

[0023] The present invention can form a rich database by collecting historical electrical simulation data to support subsequent analysis and design decisions. The historical accumulation of data can help designers understand the performance of previous designs and extract effective information from them. Various simulation parameters are combined to obtain a variety of physical and electrical parameter combinations. This combined extraction method makes the design more flexible, thereby improving the accuracy and pertinence of the design. By analyzing the correlation between physical parameters and electrical parameters, the relationship between them can be revealed, which is very important for optimizing the performance of circuit boards. The physical-electrical characteristic correlation data generated by analysis enables designers to make more scientific and reasonable design decisions based on data and reduce the risk of relying on empirical judgment. By mapping the physical size structure model with the electrical characteristic requirements, a clear demand structured model can be formed, which helps the design team better understand the relationship between customer requirements and design constraints. By structuring the requirements, effective communication and collaboration between departments (such as marketing, R&D, production, etc.) can be promoted to ensure that the goals of product design and manufacturing are consistent. Structuring the circuit board design requirements helps to establish a set of standardized design processes, ensure that all requirements are clear and traceable, and reduce misunderstandings and errors in the design process. Through structured design requirement data, the team can respond to market changes and customer feedback more quickly, effectively shorten the product development cycle, and improve the consistency and reusability of the design.

[0024] Optionally, step S15 is specifically:

[0025] Step S151: extracting circuit board level features and circuit board wiring features from the circuit board design requirement data, thereby obtaining circuit board requirement level data and circuit board requirement wiring data;

[0026] Step S152: performing circuit board required layer count statistics according to the circuit board required layer data, thereby obtaining circuit board required layer count data;

[0027] Step S153: performing circuit board wiring density calculation on the circuit board required wiring data, thereby obtaining circuit board wiring density data; performing circuit board wiring curvature calculation on the circuit board required wiring data, thereby obtaining circuit board wiring curvature data;

[0028] Step S154: evaluating the wiring complexity of the circuit board according to the required number of layers of the circuit board, the wiring density data of the circuit board, and the wiring curvature data of the circuit board, thereby obtaining the wiring complexity data of the circuit board;

[0029] Step S155: clustering the circuit board design requirement data into design complexity requirement patterns according to the circuit board routing complexity data, thereby obtaining circuit board design requirement pattern data.

[0030] The present invention can clearly understand the functional requirements of each layer through the extraction of hierarchical features, which helps to reasonably allocate materials and costs. The extraction of wiring features can help designers identify complex signal paths and power paths, and reduce the risk of interference and signal attenuation. Knowing the required number of layers helps designers optimize the board layers during the design process and avoid overly complex designs that lead to increased production costs. By calculating the wiring density, the space utilization of the design can be evaluated, thereby optimizing the wiring layout in the design to prevent overcrowding. The evaluation of wiring curvature helps to ensure the propagation characteristics of the signal, improve signal integrity, and reduce reflections and losses. Evaluating wiring complexity through comprehensive data helps designers make judgments in the early stages of the design and avoid major design changes in the later stages. Complexity data can provide support for the design team and help formulate a reasonable project schedule and budget. Through cluster analysis, patterns of similar design requirements can be identified, design efficiency can be improved, and duplication of work can be avoided. The accumulation of design requirement pattern data can provide an important reference for future design processes and establish design specifications and standards.

[0031] Optionally, step S2 specifically includes:

[0032] Step S21: obtaining a circuit board historical design log, and performing circuit board hierarchical design clustering according to the circuit board historical design log, thereby obtaining historical circuit board hierarchical design data;

[0033] Step S22: extracting hierarchical structure features from historical circuit board hierarchical design data, thereby obtaining circuit board hierarchical structure data;

[0034] Step S23: performing hierarchical structure classification according to the hierarchical structure data of the circuit board, thereby obtaining hierarchical wiring structure data and hierarchical component structure data;

[0035] Step S24: performing spatial distribution statistics of the hierarchical components according to the hierarchical component structure data, thereby obtaining spatial distribution data of the hierarchical components;

[0036] Step S25: performing spatial association of hierarchical component electrical connection data with hierarchical component spatial distribution data and hierarchical wiring structure data, thereby obtaining hierarchical component electrical connection data;

[0037] Step S26: Performing a topological structure analysis of the circuit board hierarchical wiring structure according to the hierarchical component electrical connection data, thereby obtaining a circuit board hierarchical wiring structure model set.

[0038] The present invention obtains the historical design logs of the circuit board, which provides valuable reference materials for existing designs. The design changes, problems and solutions recorded in these logs can help designers understand the successes and shortcomings of previous designs. At the same time, analyzing these historical data helps to identify common design patterns and trends, and provide guidance for future designs. By extracting features from the historical circuit board hierarchical design data, key design features and rules can be extracted. This process can simplify complex design data and help designers better understand and master the hierarchical structure of the circuit board. This not only improves the efficiency of the design, but also provides data support for subsequent design decisions. Classifying the hierarchical structure can classify different types of wiring structures and component structures for easy management and comparison. The classified data can help designers quickly find design structures that meet specific needs, promote standardization and modularization of the design, which is of great help to subsequent design optimization. The spatial distribution statistics of hierarchical components can reveal the distribution of each component in the physical position. This analysis can help designers optimize component layout, reduce wiring complexity, and improve the performance and reliability of the circuit board. The rationality of spatial distribution also has an important impact on heat dissipation, anti-interference performance, etc. Spatial correlation analysis of the electrical connections of hierarchical components can provide the connection relationship and relative position between the components. This analysis not only helps to optimize the routing strategy, but also identifies potential electrical interference problems in advance to ensure the best performance of the circuit board in actual use. Topological analysis of the hierarchical routing structure of the circuit board can help designers understand the overall structure and logical relationship of the routing. This analysis can reveal the advantages and disadvantages of the design and provide a basis for design optimization. By building a model set, designers can make effective references in future designs, thereby improving the efficiency and accuracy of the design.

[0039] Optionally, step S25 is specifically:

[0040] Step S251: integrating component structure function description features on hierarchical component structure data, thereby obtaining component structure function description data;

[0041] Step S252: clustering component structure function descriptions according to the component structure function description data, thereby obtaining component structure function clustering data;

[0042] Step S253: performing wiring density statistics according to the hierarchical wiring structure data to obtain wiring density data, and performing high wiring density structure division on the hierarchical wiring structure data according to the wiring density data to obtain high density wiring structure data;

[0043] Step S254: dividing the hierarchical component spatial distribution data into component-intensive areas, thereby obtaining hierarchical component-intensive area data;

[0044] Step S255: performing a spatial structure intersection operation on the high-density wiring structure data and the hierarchical component dense area data, thereby obtaining hierarchical component functional module structure data;

[0045] Step S256: defining the component function module functions of the hierarchical component function module structure data according to the component structure function description data, thereby obtaining hierarchical module division data;

[0046] Step S257: Integrate the electrical connection relationship of the module components of the hierarchical module division data to obtain hierarchical component electrical connection data.

[0047] The present invention integrates the functional description features, and can classify and describe the functional features of different components, making the subsequent analysis more systematic. Through feature integration, redundancy and contradictions in the functional description are reduced, making the structural data clearer. Through cluster analysis, components with similar functions can be identified, which helps to optimize the design and reduce production costs. The clustering results can help designers select suitable components for combination or replacement more quickly. Through statistics and analysis of wiring density, potential wiring problems can be identified, and wiring schemes can be optimized to reduce signal interference and improve heat dissipation. High-density structural division can help designers identify key areas, which is convenient for more effective maintenance and troubleshooting. The division of component-dense areas can provide a spatial layout basis for product design, which is convenient for realizing the reasonable layout of functional modules. By clarifying dense areas, space can be reasonably utilized to reduce the volume or weight of the design. The spatial intersection operation helps to combine the relationship between wiring and component layout, realize the coordinated optimization of function and space, and can more accurately identify interacting components, thereby improving the accuracy and reliability of the overall design. Defining functional modules helps to clearly understand the role of each module in the system, making the subsequent design and development direction clearer. Clearly defined modules can support modular design concepts and facilitate subsequent updates and maintenance. The integration of electrical connection relationships makes circuit design clearer and helps optimize electrical connections at the system level. By integrating electrical connection data, fault points can be quickly located to improve system reliability.

[0048] Optionally, step S3 specifically includes:

[0049] Step S31: extracting design requirement pattern features based on the circuit board design requirement pattern data, thereby obtaining hierarchical design requirement pattern data and wiring design requirement pattern data;

[0050] Step S32: performing hierarchical structure quantization on the hierarchical design requirement pattern data, thereby obtaining a hierarchical design structure quantization model, and performing wiring requirement numerical quantization on the wiring design requirement data according to the hierarchical design structure quantization model, thereby obtaining circuit board wiring requirement data;

[0051] Step S33: extracting hierarchical wiring features from the circuit board hierarchical wiring structure model set, thereby obtaining a circuit board hierarchical wiring structure data set;

[0052] Step S34: performing wiring similarity calculation on the circuit board hierarchical wiring structure data set and the circuit board wiring requirement data, thereby obtaining wiring similarity data;

[0053] Step S35: selecting a circuit board level wiring structure for the circuit board level wiring structure model set according to the wiring similarity, thereby obtaining a circuit board matching level wiring structure model.

[0054] The present invention can integrate the originally scattered design requirement information to form a clear hierarchical structure by extracting the design requirement pattern features. This structured information helps to better understand the relationship between each design parameter. Through the clear demand pattern, it helps the design engineer to meet the requirements more accurately in the subsequent steps, reduce the design error and the number of iterations. The quantitative construction of the hierarchical design can provide a quantitative basis for design decisions, making the design process more scientific and standardized. By numerically quantifying the wiring requirement data, a specific guidance basis can be provided for the subsequent wiring design, so that the wiring planning and adjustment can be carried out more effectively. After completing the hierarchical wiring feature extraction, a structured wiring data set can be obtained, which is very important for subsequent analysis and optimization. The standardization of the data set makes the subsequent processing more efficient. By obtaining a variety of hierarchical wiring structure data, a variety of options can be provided for different design requirements, and the flexibility and adaptability of the design can be improved. By calculating the wiring similarity, the wiring method similar to the existing design can be identified, thereby realizing the reuse of the design, reducing duplication of work, and improving the design efficiency. The similarity data can help designers quickly find a wiring structure that meets the requirements, reducing the time cost of finding a suitable solution in the design process. Selecting the most appropriate wiring structure model based on wiring similarity can speed up design decisions and ensure a smooth design process. The best matching hierarchical wiring structure can be selected to help improve the electrical performance and mechanical stability of the final PCB design, ensuring the high quality and reliability of the product.

[0055] Optionally, step S4 is specifically:

[0056] Step S41: extracting circuit board component requirement features according to the circuit board design requirement data, thereby obtaining circuit board component requirement data, and integrating component function description features of the circuit board component requirement data, thereby obtaining requirement component function description data;

[0057] Step S42: extracting hierarchical module description features from the hierarchical wiring structure model set of the circuit board, thereby obtaining hierarchical module description data;

[0058] Step S43: classifying the required component function description data into component function modules according to the hierarchical module description data, thereby obtaining required component function module data;

[0059] Step S44: extracting hierarchical wiring structure features according to the matching hierarchical wiring structure model of the circuit board, thereby obtaining matching hierarchical wiring structure data;

[0060] Step S45: performing functional module layout on the matching hierarchical wiring structure data according to the required component functional module data, thereby obtaining functional module layout data, and optimizing component connectivity on the functional module layout data, thereby obtaining circuit board hierarchical component layout data;

[0061] Step S46: planning the signal line directions of the circuit board components according to the circuit board matching hierarchical wiring structure model according to the circuit board hierarchical component layout data, thereby obtaining the circuit board hierarchical structure model.

[0062] The present invention can clearly define the requirements of each component on the circuit board by extracting the circuit board design requirement data, so that the design is more targeted. Integrating the component function description helps designers consider the functionality of each component during design and improve the overall performance and reliability of the circuit board. Extracting the hierarchical module description features helps to effectively manage the hierarchical structure of the circuit board, ensure that each module in the design has a clear function and position, make the design process more modular, and facilitate subsequent testing, maintenance and updating. Classifying the required components into modules makes the design scheme have a clear structure at all levels, which is convenient for communication between team members. According to the classification of different functional modules, resources can be reasonably allocated to ensure that key modules are given priority and reduce design redundancy. Extracting the hierarchical wiring structure features allows designers to more effectively arrange the direction of signal lines, optimize the wiring method, and reduce interference and signal attenuation. Feature extraction provides a basis for the development of subsequent wiring automation tools, which helps to speed up the design process. Connectivity optimization is carried out according to the functional module layout to ensure the efficiency of signal transmission and reduce performance problems caused by improper layout. Reasonable module layout can effectively reduce material waste, reduce production costs, and improve overall economic benefits. By planning the signal line direction according to the layout data and ensuring that the signal line direction is reasonable, it helps to improve signal integrity and board-level reliability. Good signal direction planning can provide guarantee for subsequent design verification and testing, reduce the possibility of rework, and shorten the time to market.

[0063] Optionally, step S5 specifically includes:

[0064] Step S51: extracting working condition requirement features from the circuit board design requirement data, thereby obtaining the circuit board working condition requirement data, and setting simulation boundary conditions according to the circuit board working condition requirement data, thereby obtaining simulation boundary conditions;

[0065] Step S52: performing electromagnetic interference simulation on the circuit board hierarchical structure model according to the simulation boundary conditions, thereby obtaining electromagnetic interference simulation data;

[0066] Step S53: performing circuit board current distribution analysis according to the electromagnetic interference simulation data to obtain electromagnetic simulation current distribution data, and performing circuit board thermal simulation on the electromagnetic simulation current distribution data to obtain circuit board thermal simulation data;

[0067] Step S54: Visualizing the heat flow distribution of the circuit board according to the thermal simulation data of the circuit board, thereby obtaining the heat flow distribution data of the circuit board, and identifying the hot spot area of ​​the heat flow distribution data of the circuit board, thereby obtaining the hot spot area data of the circuit board;

[0068] Step S55: extracting circuit board level component layout features from the circuit board level structure model to obtain circuit board level component layout data, and adjusting the circuit board level component layout data for heat flow balance components according to the circuit board hot spot area data to obtain heat flow balance component layout data;

[0069] Step S56: Optimizing the circuit board hierarchical structure model according to the heat flow balancing component layout data to obtain the circuit board optimized structure model, and describing the circuit board design drawing parameters of the circuit board optimized structure model to obtain the printed circuit board design drawing.

[0070] The present invention can ensure the performance of the design under a real operating environment by extracting the working condition demand characteristics from the circuit board design demand data. This step enables engineers to accurately understand the requirements of the circuit board under different working conditions, so as to set appropriate simulation boundary conditions. This helps to obtain more realistic and reliable results in subsequent simulations and reduce the number of design iterations. Electromagnetic interference simulation based on the set simulation boundary conditions can help engineers identify and analyze potential electromagnetic interference problems, which is an important step to ensure that the product complies with the electromagnetic compatibility (EMC) standard, avoid interference and functional failure in practical applications, and improve the reliability and stability of the circuit board. The current distribution data obtained through electromagnetic interference simulation can deeply understand the current flow on the circuit board, which is crucial to evaluating the performance of the circuit. The subsequent thermal simulation can predict the temperature changes of each part during the working process, which is of great significance to the heat dissipation design, thereby improving the thermal management capability of the overall design and reducing the damage to components caused by overheating. Visualizing the heat flow distribution of the circuit board helps design engineers to intuitively grasp the distribution and concentration of heat. By identifying the hot spot area, engineers can take targeted design measures, such as adding a radiator or improving air circulation, to ensure the safety and performance of key components and optimize the durability and efficiency of the overall product. After extracting the layout features of the components at the circuit board level, the heat flow balance component layout adjustment combined with the hot spot area data can effectively reduce the risk of local overheating. This layout optimization not only improves the heat dissipation performance, but also may improve the current flow path, thereby improving circuit performance and reliability. The model obtained by optimizing the circuit board hierarchical structure will have a significant improvement in performance and thermal management. The generated printed circuit board design will contain a more reasonable layout and parameters, which will directly affect production efficiency, reduce production costs and improve the market competitiveness of the final product.

[0071] Optionally, the present specification also provides a system for generating a printed circuit board design drawing, which is used to execute the method for generating a printed circuit board design drawing as described above, and the system for generating a printed circuit board design drawing includes:

[0072] The design requirement pattern clustering module is used to obtain customer requirement data, and structure the circuit board design requirements according to the customer requirement data, thereby obtaining the circuit board design requirement data; and cluster the design requirement patterns of the circuit board design requirement data, thereby obtaining the circuit board design requirement pattern data;

[0073] A topology analysis module is used to obtain the historical design log of the circuit board, and perform circuit board hierarchical design clustering according to the historical design log of the circuit board, so as to obtain the historical circuit board hierarchical design data; perform circuit board hierarchical wiring structure topology analysis based on the historical circuit board hierarchical design data, so as to obtain the circuit board hierarchical wiring structure model set;

[0074] A hierarchical wiring structure matching module is used to quantify the wiring requirements of the circuit board based on the circuit board design requirement pattern data, thereby obtaining the wiring requirement data of the circuit board, and to match the hierarchical wiring structure of the circuit board with the hierarchical wiring structure model set of the circuit board according to the wiring requirement data of the circuit board, thereby obtaining the matching hierarchical wiring structure model of the circuit board;

[0075] The component layout planning module is used to perform circuit board component layout on the circuit board matching hierarchical wiring structure model according to the circuit board design requirement data, thereby obtaining circuit board hierarchical component layout data; and to perform circuit board component signal line direction planning on the circuit board matching hierarchical wiring structure model according to the circuit board hierarchical component layout data, thereby obtaining the circuit board hierarchical structure model;

[0076] The hierarchical heat flow balance optimization module is used to perform electromagnetic interference simulation on the hierarchical structure model of the circuit board to obtain electromagnetic interference simulation data, and to perform hierarchical heat flow balance optimization on the hierarchical structure model of the circuit board based on the electromagnetic interference simulation data to obtain the optimized structure model of the circuit board; and to perform circuit board design drawing parameter description on the optimized structure model of the circuit board to obtain the printed circuit board design drawing.

[0077] The system for generating a printed circuit board design drawing of the present invention can implement any method for generating a printed circuit board design drawing of the present invention, and is used to combine the operation and signal transmission medium between various modules to complete the method for generating a printed circuit board design drawing. The internal modules of the system cooperate with each other, thereby improving the efficiency of circuit board design. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

[0079] Figure 1 A schematic flow chart of the steps of a method for generating a printed circuit board design drawing of the present invention;

[0080] Figure 2 Detailed step flow diagram of step S1 in the present invention;

[0081] Figure 3 Detailed step flow diagram of step S2 in the present invention;

[0082] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0083] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0084] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0085] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0086] To achieve this, please refer to Figures 1 to 3 The present invention provides a method for generating a printed circuit board design drawing, the method comprising the following steps:

[0087] Step S1: Obtain customer demand data, and structure circuit board design demand according to the customer demand data, thereby obtaining circuit board design demand data; cluster the circuit board design demand data into design demand patterns, thereby obtaining circuit board design demand pattern data;

[0088] In this embodiment, first, the customer's specific requirements for the circuit board, such as size, function, material, cost constraints, etc., are obtained through questionnaires, interviews or online platforms. These demand data will be organized into a structured format, such as a table or database record. Next, a clustering algorithm (such as K-means or hierarchical clustering) is used to analyze the customer demand data, and similar requirements are divided into different modes to identify the category of design requirements. For example, a customer wants to design a circuit board with high-frequency signal transmission, while another customer requires low power consumption characteristics. After analysis, a "high-frequency design mode" and a "low-power design mode" are obtained.

[0089] Step S2: Obtain the historical design log of the circuit board, and perform circuit board hierarchical design clustering according to the historical design log of the circuit board, so as to obtain the historical circuit board hierarchical design data; perform circuit board hierarchical wiring structure topology analysis based on the historical circuit board hierarchical design data, so as to obtain the circuit board hierarchical wiring structure model set;

[0090] In this embodiment, past circuit board design logs, including design files, modification records, and customer feedback, are collected and organized by the circuit board manufacturer. The logs are clustered into hierarchical designs using similarity metrics (such as cosine similarity or Euclidean distance). For example, designs with the same number of layers and similar layout structures are clustered together to form multiple historical design groups. Through these clusters, the common hierarchical structures in past designs can be better understood. Subsequently, a topological analysis of the wiring structure is performed based on these historical data to identify effective signal directions, ground line distribution, etc., to form a set of structural models. For example, it is found that a certain design usually has better signal strength on the third layer.

[0091] Step S3: quantifying the wiring requirements of the circuit board based on the circuit board design requirement model data, thereby obtaining the wiring requirement data of the circuit board, and matching the wiring structure of the circuit board hierarchical wiring structure model set with the wiring structure of the circuit board according to the wiring requirement data of the circuit board, thereby obtaining the matching wiring structure model of the circuit board;

[0092] In this embodiment, the design requirement pattern data is converted into quantitative indicators, such as the width, spacing, layer configuration, etc. of each signal line. These quantitative requirements are analyzed and matched with the historical wiring structure model set obtained by clustering. The goal is to find the structural model that best meets the current design requirements to ensure the optimization of performance. For example, for high-frequency design requirements, the wiring structure model for the purpose of optimizing signal integrity can be matched first to obtain a "hierarchical wiring structure model that meets high-frequency design requirements."

[0093] Step S4: Layout the circuit board components on the circuit board matching hierarchical wiring structure model according to the circuit board design requirement data, thereby obtaining circuit board hierarchical component layout data; plan the signal line direction of the circuit board components on the circuit board matching hierarchical wiring structure model according to the circuit board hierarchical component layout data, thereby obtaining the circuit board hierarchical structure model;

[0094] In this embodiment, the layout of the circuit board components is carried out according to the obtained design requirements and matching model information. The design tool (such as Altium Designer or Eagle) will automatically generate a preliminary layout plan according to the requirements. After the layout is completed, the direction of the signal line is planned based on the layout data to ensure that electromagnetic interference is reduced during the transmission process and meet the design specifications. For example, core components such as microprocessors and memory chips need to be as close as possible, and signal lines should avoid crossing power lines to ensure signal integrity.

[0095] Step S5: Perform electromagnetic interference simulation on the circuit board hierarchical structure model to obtain electromagnetic interference simulation data, and optimize the hierarchical structure thermal flow balance of the circuit board hierarchical structure model based on the electromagnetic interference simulation data to obtain the circuit board optimized structure model; perform circuit board design drawing parameter description on the circuit board optimized structure model to obtain the printed circuit board design drawing.

[0096] In this embodiment, electromagnetic interference (EMI) simulation is performed on the hierarchical structure model of the circuit board, and tools such as HFSS or ADS are used to analyze possible interference problems. According to the simulation results, the source of electromagnetic interference and the sensitive areas affected by it are identified. To this end, measures are taken to optimize the design, such as strengthening the isolation of power lines and optimizing the ground line layout. When achieving heat flow balance optimization, the thermal distribution of each component is evaluated through thermal analysis tools (such as ANSYS or Fluent) to ensure that the heat can be effectively dissipated and avoid overheating. After the optimization is completed, the final structural model of the circuit board is obtained, and a detailed circuit board design drawing parameter description is performed to form a design drawing of the printed circuit board.

[0097] Optionally, step S1 specifically includes:

[0098] Step S11: obtaining customer demand data, and cleaning the missing values ​​of the customer demand data, thereby obtaining cleaned customer demand data;

[0099] In this embodiment, customer demand data is collected through various channels such as questionnaires, user feedback, and market research. Then, a data cleaning tool (such as Python's Pandas library) is used to detect missing values, for example, df.isnull().sum() is used to identify missing data. For missing value processing, methods such as mean filling, median filling, or deleting missing data rows can be used. Finally, ensure that the cleaned data obtained is complete and consistent, for example, by checking the data distribution through a visualization tool.

[0100] Step S12: classifying the cleaning customer demand data into customer demand data, thereby obtaining electrical characteristic demand data and physical size demand data;

[0101] In this embodiment, when classifying the cleaned customer demand data, the natural language processing technology in machine learning (such as TF-IDF or Word2Vec) can be used to vectorize the text data. Combined with a clustering algorithm (such as K-means), the data is classified to divide the requirements into electrical characteristic requirements (such as voltage, power) and physical size requirements (such as length, width, height, and weight). For example, by setting a predefined keyword list, requirements containing keywords such as "voltage" and "power consumption" can be classified into the electrical characteristics category.

[0102] Step S13: Performing physical dimension requirement structural modeling according to the physical dimension requirement data, thereby obtaining a physical dimension structure model;

[0103] In this embodiment, after obtaining the physical dimension requirement data, CAD (computer-aided design) software (such as AutoCAD) is used to model the physical dimension requirements. First, the dimension data is extracted and converted into a format suitable for modeling (such as DXF or STEP format). Next, the structural model is automatically generated through a programming interface (such as Python's ezdxf library) to ensure that the model accurately reflects customer needs. The goal of this step is to create a three-dimensional model for subsequent design verification, such as generating a housing shape of a specific size.

[0104] Step S14: structurally integrating the electrical characteristic requirement data into circuit board design requirement data according to the physical size structure model, thereby obtaining circuit board design requirement data;

[0105] In this embodiment, after the physical size structure model is completed, the electrical characteristic requirement data is integrated through the design software (such as Altium Designer or KiCAD). The specific method is to map the electrical characteristic requirements (such as layout, component distance) into the structure model. Interface programming (such as Altium's script interface) can be used to import electrical data to generate circuit board design requirements that meet the physical size. For example, a corresponding PCB layout diagram is generated according to the actual size.

[0106] Step S15: clustering the circuit board design requirement patterns to obtain circuit board design requirement pattern data.

[0107] In this embodiment, cluster analysis techniques (such as DBSCAN or hierarchical clustering) are applied to perform pattern recognition on circuit board design requirement data. First, the key features of the design requirement data (such as the number of components, wiring density, number of layers, etc.) are extracted through feature engineering, and then cluster analysis is performed using the scikit-learn library. The goal is to identify different circuit board design patterns, such as the requirements for low-density wiring and high-density wiring. The results can be displayed through visualization tools (such as Matplotlib or Seaborn), thereby providing a basis for subsequent design decisions.

[0108] Optionally, step S14 is specifically:

[0109] Step S141: acquiring historical electrical simulation data of the circuit board, and extracting simulation parameter combinations from the historical electrical simulation data of the circuit board, thereby obtaining simulation physical parameter combinations and simulation electrical parameter combinations;

[0110] In this embodiment, historical electrical simulation data of the circuit board is collected by the circuit board manufacturer, and these data are usually stored in the database of the circuit board manufacturer. According to specific simulation conditions (such as temperature, pressure and current), the combination of different simulation parameters in the historical data is extracted. For example, the signal transmission results of different combinations of resistance values ​​and capacitance values ​​can be extracted. Next, the extracted data is classified by a data analysis algorithm (such as cluster analysis or principal component analysis) to identify physical parameter combinations (for example, optimal circuit layout and material parameters) and electrical parameter combinations (for example, optimal signal integrity parameters) with better performance, thereby providing valuable reference for subsequent steps.

[0111] Step S142: performing physical-electrical characteristic correlation analysis on the simulated physical parameter combination and the simulated electrical parameter combination, thereby obtaining physical-electrical characteristic correlation data;

[0112] In this embodiment, after obtaining the simulated physical parameter combination and the simulated electrical parameter combination, a physical-electrical characteristic correlation analysis is performed. This step usually involves the use of regression analysis or machine learning algorithms (such as random forests or support vector machines) to identify and quantify the relationship between physical characteristics (such as PCB thickness, dielectric materials) and electrical performance (such as impedance, signal delay). By performing covariance analysis on the collected simulation results, detailed physical-electrical characteristic correlation data can be output. These data provide empirical evidence for optimizing the design. For example, improving the PCB thickness may improve signal quality or reduce reflection loss.

[0113] Step S143: mapping the physical dimension structure model and the electrical characteristic requirement data according to the physical-electrical characteristic association data, thereby obtaining a circuit board requirement structured model;

[0114] In this embodiment, based on the physical-electrical characteristic association data, the physical dimension structure model and the electrical characteristic requirement data are mapped. Using data visualization tools (such as MATLAB or Python's Matplotlib library), the physical dimensions (such as length, width, number of layers, etc.) and electrical requirements (such as operating frequency, maximum current carrying capacity) are presented in a list or chart to establish a linear mapping relationship model. By comparing the characteristics of different design schemes, a structured model is generated to clarify which physical changes will directly affect electrical performance, providing specific guidance for product design.

[0115] Step S144: Structuring the circuit board design requirement model to obtain circuit board design requirement data.

[0116] In this embodiment, the circuit board requirement structured model is used to structure the circuit board design requirements. With the help of the built-in API of modern CAD software (such as Altium Designer or Eagle), the above mapping relationship is converted into actual design specifications and requirements. For example, based on the obtained physical requirements (such as thickness, material) and electrical requirements (such as impedance matching), a specific design parameter document is generated, covering design rules, bill of materials, and manufacturing process requirements. This structured output can be directly used as a benchmark for subsequent design processes and promote communication and collaboration between teams to ensure the consistency and effectiveness of design goals.

[0117] Optionally, step S15 is specifically:

[0118] Step S151: extracting circuit board level features and circuit board wiring features from the circuit board design requirement data, thereby obtaining circuit board requirement level data and circuit board requirement wiring data;

[0119] In this embodiment, feature engineering technology can be used to extract features from circuit board design requirement data. When extracting circuit board hierarchical features, it is first necessary to identify the types of different layers (such as signal layer, ground layer, power supply layer, etc.) from the circuit board design requirement data, and record the thickness, material and function of these layers. Wiring feature extraction includes calculating information such as line width, spacing, and line direction. For example, analyze the length and number of turns of the signal line in a circuit board, and record these data to form "requirement hierarchical data" and "requirement wiring data."

[0120] Step S152: performing circuit board required layer count statistics according to the circuit board required layer data, thereby obtaining circuit board required layer count data;

[0121] In this embodiment, based on the extracted demand level data, data aggregation technology can be used to count the number of layers of each type in the circuit board. For example, by writing a Python script, reading the layer information of the PCB design file, and using a dictionary or list to count the number of each layer, a summary table of "circuit board required layer number data" is finally generated. This step not only helps to confirm the design specifications, but also provides basic data for subsequent complexity assessment.

[0122] Step S153: performing circuit board wiring density calculation on the circuit board required wiring data, thereby obtaining circuit board wiring density data; performing circuit board wiring curvature calculation on the circuit board required wiring data, thereby obtaining circuit board wiring curvature data;

[0123] In this embodiment, the wiring density calculation can be achieved by decomposing the wiring path of the PCB into straight and curved parts, and calculating the length of the wiring per unit area. For example, the wiring diagram can be converted into a grid, and the number of wirings in each cell in the grid is counted to obtain the wiring density. The wiring curvature requires the use of geometric analysis to calculate the turning radius of the line, which requires the use of a computational geometry library such as Shapely. For example, analyze the curved section in a design and calculate its average curvature value to obtain the "circuit board wiring curvature data".

[0124] Step S154: evaluating the wiring complexity of the circuit board according to the required number of layers of the circuit board, the wiring density data of the circuit board, and the wiring curvature data of the circuit board, thereby obtaining the wiring complexity data of the circuit board;

[0125] In this embodiment, based on the obtained "circuit board required layer number data", "wiring density data" and "wiring curvature data", a weighted average model or other complexity algorithms can be used for evaluation. For example, an evaluation formula is set to allow the number of layers, wiring density and curvature to affect the final complexity score, and the complexity of the design is quantitatively analyzed by adjusting the weights. Finally, a complexity scoring system is generated to help designers judge the complexity of the design in the early stages and make corresponding design adjustments.

[0126] Step S155: clustering the circuit board design requirement data into design complexity requirement patterns according to the circuit board routing complexity data, thereby obtaining circuit board design requirement pattern data.

[0127] In this embodiment, based on the evaluated "circuit board wiring complexity data", the clustering algorithm in machine learning (such as K-means clustering) can be used to classify the circuit board design requirements. For example, the design requirements with different complexity scores are grouped by category, and each group represents a specific type of design requirement pattern. By analyzing these clustering results, design engineers can identify which design requirements are common in the industry and which are abnormal, so as to optimize the process for different types of designs.

[0128] Optionally, step S2 specifically includes:

[0129] Step S21: obtaining a circuit board historical design log, and performing circuit board hierarchical design clustering according to the circuit board historical design log, thereby obtaining historical circuit board hierarchical design data;

[0130] In this embodiment, the circuit board manufacturer reads the historical design log of the CAD software (such as AltiumDesigner or Eagle, etc.) to obtain the design change record of the circuit board, including the timestamp, modification content and designer of each design. Technically, this can be achieved through API interface or log file parsing. Python scripts can be used to automatically extract, store design change information by date, and record key parameters of each design version (such as the number of wiring layers, the number of components). With this information, similar designs can be clustered and analyzed to identify common design patterns and errors.

[0131] Step S22: extracting hierarchical structure features from historical circuit board hierarchical design data, thereby obtaining circuit board hierarchical structure data;

[0132] In this embodiment, after obtaining the historical design log, hierarchical structure feature extraction is performed, mainly including component type, connection method and electrical characteristics. By establishing a data model, the components in each design version are classified (such as resistors, capacitors, ICs, etc.), and their relative positions and connection relationships in the circuit are recorded. Machine learning algorithms (such as clustering algorithms) can be used to extract these features, and the hierarchical structure of each design is described by feature vectors to form a structural feature database.

[0133] Step S23: performing hierarchical structure classification according to the hierarchical structure data of the circuit board, thereby obtaining hierarchical wiring structure data and hierarchical component structure data;

[0134] In this embodiment, a classification algorithm (such as a decision tree, a random forest, or a support vector machine) is used to classify the extracted hierarchical structure features. The extracted feature vector is used as input data to train the classification model to distinguish between hierarchical wiring structures (such as power layers, signal layers) and hierarchical component structures (such as chips, passive components). The accuracy and stability of the classification model are ensured through cross-validation and hyperparameter tuning. Ultimately, the model can output different categories of wiring structures and component structures for subsequent analysis and optimization.

[0135] Step S24: performing spatial distribution statistics of the hierarchical components according to the hierarchical component structure data, thereby obtaining spatial distribution data of the hierarchical components;

[0136] In this embodiment, the spatial distribution statistics are performed on the hierarchical component structure data extracted from the classification results. It is necessary to analyze the layout of the components on the PCB, including the X, Y coordinates of the components and their sizes. Statistical software (such as MATLAB or Pandas library in Python) is used to visualize the spatial distribution and calculate the statistical characteristics of the density distribution and distance distribution of each component on the layout board, so as to identify common layout patterns and potential space utilization problems.

[0137] Step S25: performing spatial association of hierarchical component electrical connection data with hierarchical component spatial distribution data and hierarchical wiring structure data, thereby obtaining hierarchical component electrical connection data;

[0138] In this embodiment, the electrical connection relationship between components is analyzed using the spatial distribution data of hierarchical components and the hierarchical wiring structure data. A graph theory method is used to construct a component connection diagram to identify the electrical path and connection strength between each component. The graph can be constructed using MATLAB or Python, and a network analysis algorithm can be used to identify key nodes (i.e., important components or connections). Ultimately, hierarchical component electrical connection data is formed to provide a clear view of the interaction between components.

[0139] Step S26: Performing a topological structure analysis of the circuit board hierarchical wiring structure according to the hierarchical component electrical connection data, thereby obtaining a circuit board hierarchical wiring structure model set.

[0140] In this embodiment, a topological analysis of the hierarchical wiring structure of the circuit board is performed based on the electrical connection data of the hierarchical components. At this stage, a topological analysis tool (such as Graphviz or Gephi) is used to analyze the connectivity, redundant connections and critical paths of the circuit board. The network analysis technology in graph theory (such as the minimum spanning tree algorithm) can also be used to construct a hierarchical wiring structure model of the circuit board. By combining and analyzing the electrical connection data and the wiring data, the topological features of the circuit board, such as connectivity, loops, path efficiency, etc., are extracted. The generated set of hierarchical wiring structure models of the circuit board will provide a basis for design improvements and provide a reference for future new designs.

[0141] Optionally, step S25 is specifically:

[0142] Step S251: integrating component structure function description features on hierarchical component structure data, thereby obtaining component structure function description data;

[0143] In this embodiment, the type, size, material and other features of the components included in the hierarchical component structure data are classified and integrated, for example, the description text is analyzed using natural language processing technology to extract key functional characteristics (such as heat dissipation, strength, etc.). Then, a machine learning model (such as a support vector machine or a clustering algorithm) is applied to classify these features to generate component structure function description data. For example, the power module, signal processing module, etc. are classified according to functional characteristics to form a corresponding data set for subsequent analysis.

[0144] Step S252: clustering component structure function descriptions according to the component structure function description data, thereby obtaining component structure function clustering data;

[0145] In this embodiment, based on the obtained component structure function description data, a clustering algorithm (such as K-means or DBSCAN) is used to cluster the data. In the clustering process, firstly, appropriate clustering parameters (such as distance metric) are selected, and then components with similar functions are clustered into one category. Taking multiple components of a circuit board as an example, components with similar functions (such as filters and amplifiers) will be clustered into the same group. Finally, the output component structure function clustering data contains the feature description of each cluster and the corresponding component list, which is convenient for subsequent function analysis and optimization.

[0146] Step S253: performing wiring density statistics according to the hierarchical wiring structure data to obtain wiring density data, and performing high wiring density structure division on the hierarchical wiring structure data according to the wiring density data to obtain high density wiring structure data;

[0147] In this embodiment, based on the hierarchical wiring structure data (such as cable wiring diagrams, connection points, etc.), the density of the wiring is first counted. The density can be quantified by calculating the number of wiring lines and the wiring length per unit area. Then, a density threshold is set (such as more than 10 wiring lines per square meter), and the wiring data is divided into high-density areas to generate high-density wiring structure data. For example, for complex circuit boards, high-density areas (such as power supply areas) are identified for subsequent wiring optimization or spatial layout adjustment.

[0148] Step S254: dividing the hierarchical component spatial distribution data into component-intensive areas, thereby obtaining hierarchical component-intensive area data;

[0149] In this embodiment, the component-intensive area is divided according to the spatial distribution data of the hierarchical components (such as a 3D model or a two-dimensional plan). First, the spatial coordinate data of the components is analyzed by a spatial analysis tool (such as GIS software), and the density is calculated (for example, the number of components in each area). Then, according to the set density standard (such as the number of components per cubic meter exceeding 5), the space is divided into dense areas and sparse areas, and finally the hierarchical component dense area data is output to facilitate subsequent design and optimization.

[0150] Step S255: performing a spatial structure intersection operation on the high-density wiring structure data and the hierarchical component dense area data, thereby obtaining hierarchical component functional module structure data;

[0151] In this embodiment, high-density wiring structure data and hierarchical component dense area data are used to perform spatial intersection operations. Through a spatial database or computational geometry method, the intersection of wiring and component dense areas is found. Taking PCB design as an example, it is identified which high-density wiring areas just pass through component dense areas. Finally, hierarchical component functional module structure data is generated, which will provide a basis for subsequent modular design and function optimization.

[0152] Step S256: defining the component function module functions of the hierarchical component function module structure data according to the component structure function description data, thereby obtaining hierarchical module division data;

[0153] In this embodiment, the hierarchical component functional module structure data is functionally defined based on the generated component structure functional description data. In this process, the main functions of each module (such as signal processing, data storage, etc.) are first identified, and the modules are named based on the clustering results. Then, the input and output interfaces and their working principles are defined for each module. For example, the signal processing module can be defined as receiving data from a sensor and performing real-time processing, and finally outputting the processed signal to generate the corresponding hierarchical module division data.

[0154] Step S257: Integrate the electrical connection relationship of the module components of the hierarchical module division data to obtain hierarchical component electrical connection data.

[0155] In this embodiment, the obtained hierarchical module division data is used to integrate the electrical connection relationship between the modules. The wiring connection relationship between the modules reflected by the wiring structure of the circuit board can be used to clarify the electrical connection of each module. A data structure (such as an adjacency matrix or a graph structure) can be used to represent the connection relationship between modules. For example, the connection type (such as a DC connection) between the power module and the processing module is defined according to the wiring structure. Finally, the electrical connection data of the hierarchical components is output to form a complete electrical connection diagram for circuit simulation and subsequent verification.

[0156] Optionally, step S3 specifically includes:

[0157] Step S31: extracting design requirement pattern features based on the circuit board design requirement pattern data, thereby obtaining hierarchical design requirement pattern data and wiring design requirement pattern data;

[0158] In this embodiment, data mining technology is used to extract features for specific circuit board design requirement pattern data. Then, principal component analysis (PCA) is used to extract key features of the circuit board design requirement pattern data, such as wiring width, wire spacing, number of layers, etc. These features can be further classified by machine learning algorithms (such as decision trees) to generate hierarchical design requirement pattern data and wiring design requirement pattern data. For example, by analyzing thousands of circuit board design instances, a hierarchical requirement model containing different application scenarios can be constructed to better guide the subsequent design process. The hierarchical design features and wiring design features contained in the circuit board design requirement pattern data that have been analyzed can also be extracted.

[0159] Step S32: performing hierarchical structure quantization on the hierarchical design requirement pattern data, thereby obtaining a hierarchical design structure quantization model, and performing wiring requirement numerical quantization on the wiring design requirement data according to the hierarchical design structure quantization model, thereby obtaining circuit board wiring requirement data;

[0160] In this embodiment, the hierarchical design requirement pattern data is quantified. Using structured data analysis tools, each design requirement is converted into quantitative indicators, such as priority scores and complexity indexes. In order to achieve hierarchical structure quantification, a hierarchical analysis method (AHP) model can be constructed to quantify the design requirements according to their relative importance. On this basis, the quantitative model is also applied to the wiring design requirement data to establish a numerical indicator system for wiring requirements, such as minimizing wiring paths, reducing crosstalk, etc., so as to generate operational circuit board wiring requirement data. These quantitative results will provide a basis for subsequent wiring decisions.

[0161] Step S33: extracting hierarchical wiring features from the circuit board hierarchical wiring structure model set, thereby obtaining a circuit board hierarchical wiring structure data set;

[0162] In this embodiment, the extracted circuit board hierarchical wiring structure model set is further processed. A cluster analysis method is used to classify similar wiring structure features. By analyzing various wiring methods (such as star, ring, tree, etc.), the advantages and disadvantages of various structures are identified. In addition, a wiring structure diagram can be generated using a graphical tool for easy visualization. Finally, a comprehensive circuit board hierarchical wiring structure data set will be obtained, which includes wiring feature information at different levels, which is convenient for designers to make subsequent selections and optimizations.

[0163] Step S34: performing wiring similarity calculation on the circuit board hierarchical wiring structure data set and the circuit board wiring requirement data, thereby obtaining wiring similarity data;

[0164] In this embodiment, similarity calculation is performed on the wiring structure data set and wiring requirement data at the circuit board level. Cosine similarity, Euclidean distance and other algorithms can be used for quantitative comparison. For example, by analyzing the feature vectors of different wiring structures, the similarity scores between wiring patterns are calculated. Based on this, a wiring similarity matrix can be constructed to facilitate subsequent model selection. In practical applications, similarity calculation is implemented using tools such as Python or MATLAB to quickly analyze and process large-scale data.

[0165] Step S35: selecting a circuit board level wiring structure for the circuit board level wiring structure model set according to the wiring similarity, thereby obtaining a circuit board matching level wiring structure model.

[0166] In this embodiment, the selection of the circuit board hierarchical wiring structure model is performed based on the wiring similarity data. A weighted selection algorithm is used to select the most matching wiring structure model based on the wiring similarity data and the design requirement priority. The specific method includes setting a threshold, and only models with a similarity score exceeding the threshold are considered. In addition, combined with the actual circuit function requirements, a genetic algorithm can be introduced for optimization selection to ensure that the selected model has the best balance between performance and cost. Ultimately, the obtained circuit board matching hierarchical wiring structure model will provide a reliable basis for actual circuit board design, reduce the design cycle, and improve design efficiency.

[0167] Optionally, step S4 is specifically:

[0168] Step S41: extracting circuit board component requirement features according to the circuit board design requirement data, thereby obtaining circuit board component requirement data, and integrating component function description features of the circuit board component requirement data, thereby obtaining requirement component function description data;

[0169] In this embodiment, a machine learning algorithm (e.g., a decision tree or a random forest) is used to analyze the circuit board design requirement data to extract the required characteristics of the circuit board components. For example, by parsing the requirement document, the required capacitors, resistors, IC chip types and other information are extracted. This information will form a required component database, in which each component contains not only the name and type, but also electrical characteristics (such as rated voltage, power consumption, etc.). Then, these components can be functionally described, such as "filter component", "amplifier component", etc., and these descriptions can be integrated for subsequent use.

[0170] Step S42: extracting hierarchical module description features from the hierarchical wiring structure model set of the circuit board, thereby obtaining hierarchical module description data;

[0171] In this embodiment, the module description contained in the hierarchical wiring structure model of the circuit board is searched by a string through the Aho-Corasick algorithm to extract the interconnection relationship and function of each module. The description of each module will be organized into hierarchical module description data, including information such as module name, function, input and output interface and its priority. These description data will provide a basis for the subsequent classification of component function modules.

[0172] Step S43: classifying the required component function description data into component function modules according to the hierarchical module description data, thereby obtaining required component function module data;

[0173] In this embodiment, based on the extracted data, the required components are classified according to predefined classification criteria (such as function, performance, etc.). Clustering algorithms (such as K-means clustering or hierarchical clustering) can be used to classify components with similar functions. For example, all components related to signal processing are classified as "signal processing modules", while components related to power management are classified as "power modules". The output of this step is the required component functional module data, which lists each module and its corresponding component list.

[0174] Step S44: extracting hierarchical wiring structure features according to the matching hierarchical wiring structure model of the circuit board, thereby obtaining matching hierarchical wiring structure data;

[0175] In this embodiment, the wiring structure included in the established circuit board matching layer wiring structure model is extracted to extract the direction, crossover and signal delay of each layer of wiring, and finally generate matching layer wiring structure data and record it in the database for subsequent analysis and optimization.

[0176] Step S45: performing functional module layout on the matching hierarchical wiring structure data according to the required component functional module data, thereby obtaining functional module layout data, and optimizing component connectivity on the functional module layout data, thereby obtaining circuit board hierarchical component layout data;

[0177] In this embodiment, the functional module layout is performed using the required component functional module data and the matching hierarchical wiring structure data. An optimization algorithm (such as a genetic algorithm or a particle swarm optimization algorithm) can be used to determine the optimal position of each functional module under the premise of satisfying physical constraints and electrical performance. After layout, component connectivity optimization is performed to ensure the shortest signal path and minimum interference, and finally the circuit board level component layout data is generated. The layout is implemented using professional PCB design software (such as KiCAD), and simulation is performed to verify its feasibility.

[0178] Step S46: planning the signal line directions of the circuit board components according to the circuit board matching hierarchical wiring structure model according to the circuit board hierarchical component layout data, thereby obtaining the circuit board hierarchical structure model.

[0179] In this embodiment, signal lines are planned according to the layout data. A finite state machine (FSM) model can be used to simulate the signal direction of each component to determine the best line direction and ensure the timing and integrity of the signal. For example, a hierarchical wiring algorithm (such as the RIPUP physical wiring method) is used to handle the interference problem between different signals and optimize the direction of the signal line, and finally generate a circuit board hierarchical structure model that meets all design requirements.

[0180] Optionally, step S5 specifically includes:

[0181] Step S51: extracting working condition requirement features from the circuit board design requirement data, thereby obtaining the circuit board working condition requirement data, and setting simulation boundary conditions according to the circuit board working condition requirement data, thereby obtaining simulation boundary conditions;

[0182] In this embodiment, the expected operating frequency, ambient temperature, and load current of the circuit board design requirement data are analyzed using a data mining algorithm to extract the operating condition requirement characteristics, such as current density and temperature variation range. Then, simulation boundary conditions are formulated based on these characteristics, such as setting the operating frequency to 2.4GHz, the ambient temperature to 25°C, and the maximum load current to 2A. In this way, the simulation conditions are closer to reality, and subsequent electromagnetic simulations can be performed more effectively.

[0183] Step S52: performing electromagnetic interference simulation on the circuit board hierarchical structure model according to the simulation boundary conditions, thereby obtaining electromagnetic interference simulation data;

[0184] In this embodiment, after setting the boundary conditions, electromagnetic field simulation software (such as ANSYS HFSS or CSTMicrowave Studio) is used to simulate the electromagnetic interference of the hierarchical structure model of the circuit board. The finite element method (FEM) is used to analyze the impact of electromagnetic interference of different frequencies on the circuit board, and obtain simulation data, including reflection loss, transmission loss, etc. These data are not only used to evaluate the electromagnetic compatibility (EMC) of the circuit board, but also provide a basis for the subsequent circuit board current distribution analysis.

[0185] Step S53: performing circuit board current distribution analysis according to the electromagnetic interference simulation data to obtain electromagnetic simulation current distribution data, and performing circuit board thermal simulation on the electromagnetic simulation current distribution data to obtain circuit board thermal simulation data;

[0186] In this embodiment, current distribution analysis is performed based on electromagnetic interference simulation data, and a current density calculation model is used to analyze the current flow direction of the input and output ends of the circuit. After obtaining the current distribution data, the current distribution data and the material property data of the circuit board are used to perform thermal simulation analysis of the circuit board. A heat conduction model is used to consider the location of the heat source and the current size, and the heat flow through different areas of the circuit board is simulated, and finally the thermal simulation data of the circuit board is obtained, providing the basis for hot spot identification.

[0187] Step S54: Visualizing the heat flow distribution of the circuit board according to the thermal simulation data of the circuit board, thereby obtaining the heat flow distribution data of the circuit board, and identifying the hot spot area of ​​the heat flow distribution data of the circuit board, thereby obtaining the hot spot area data of the circuit board;

[0188] In this embodiment, a visualization tool (such as MATLAB or Fluent) is used to process the thermal simulation data of the circuit board to present a two-dimensional or three-dimensional diagram of the heat flow distribution. After the heat flow distribution diagram is formed, the thermal threshold is set, and the hot spot area is identified according to the temperature distribution diagram, such as the part with a temperature exceeding 80°C, which is marked as a "hot spot area". This data lays the foundation for the subsequent heat flow balance adjustment.

[0189] Step S55: extracting circuit board level component layout features from the circuit board level structure model to obtain circuit board level component layout data, and adjusting the circuit board level component layout data for heat flow balance components according to the circuit board hot spot area data to obtain heat flow balance component layout data;

[0190] In this embodiment, the hierarchical component layout features of the circuit board are extracted, and a layout design tool (such as Altium Designer) can be used to analyze the component spacing, positioning and electrical connection. Combined with the hot spot area data, the heat flow balance component layout is adjusted. For example, high-power components are moved away from the hot spot area and their arrangement order is adjusted to ensure that the heat flow can be effectively dispersed and not concentrated in a certain area. The modified layout data is recorded as the heat flow balance component layout data.

[0191] Step S56: Optimizing the circuit board hierarchical structure model according to the heat flow balancing component layout data to obtain the circuit board optimized structure model, and describing the circuit board design drawing parameters of the circuit board optimized structure model to obtain the printed circuit board design drawing.

[0192] In this embodiment, the hierarchical structure of the circuit board is optimized according to the layout data of the heat flow balancing component. This may include changing the material, adding heat sinks or vents, etc. After optimizing the structural model, a complete circuit board design drawing is generated using PCB design software (such as Cadence or Eagle), and its parameters are described, such as the number of layers, material type and thickness of each layer, etc., to finally form a printed circuit board design drawing that meets production requirements.

[0193] Optionally, the present specification also provides a system for generating a printed circuit board design drawing, which is used to execute the method for generating a printed circuit board design drawing as described above, and the system for generating a printed circuit board design drawing includes:

[0194] The design requirement pattern clustering module is used to obtain customer requirement data, and structure the circuit board design requirements according to the customer requirement data, thereby obtaining the circuit board design requirement data; and cluster the design requirement patterns of the circuit board design requirement data, thereby obtaining the circuit board design requirement pattern data;

[0195] A topology analysis module is used to obtain the historical design log of the circuit board, and perform circuit board hierarchical design clustering according to the historical design log of the circuit board, so as to obtain the historical circuit board hierarchical design data; perform circuit board hierarchical wiring structure topology analysis based on the historical circuit board hierarchical design data, so as to obtain the circuit board hierarchical wiring structure model set;

[0196] A hierarchical wiring structure matching module is used to quantify the wiring requirements of the circuit board based on the circuit board design requirement pattern data, thereby obtaining the wiring requirement data of the circuit board, and to match the hierarchical wiring structure of the circuit board with the hierarchical wiring structure model set of the circuit board according to the wiring requirement data of the circuit board, thereby obtaining the matching hierarchical wiring structure model of the circuit board;

[0197] The component layout planning module is used to perform circuit board component layout on the circuit board matching hierarchical wiring structure model according to the circuit board design requirement data, thereby obtaining circuit board hierarchical component layout data; and to perform circuit board component signal line direction planning on the circuit board matching hierarchical wiring structure model according to the circuit board hierarchical component layout data, thereby obtaining the circuit board hierarchical structure model;

[0198] The hierarchical heat flow balance optimization module is used to perform electromagnetic interference simulation on the hierarchical structure model of the circuit board to obtain electromagnetic interference simulation data, and to perform hierarchical heat flow balance optimization on the hierarchical structure model of the circuit board based on the electromagnetic interference simulation data to obtain the optimized structure model of the circuit board; and to perform circuit board design drawing parameter description on the optimized structure model of the circuit board to obtain the printed circuit board design drawing.

[0199] The system for generating a printed circuit board design drawing of the present invention can implement any method for generating a printed circuit board design drawing of the present invention, and is used to combine the operation and signal transmission medium between various modules to complete the method for generating a printed circuit board design drawing. The internal modules of the system cooperate with each other, thereby improving the efficiency of circuit board design.

[0200] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0201] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for generating a printed circuit board design drawing, It is characterized in that The following steps are involved: Step S1: Obtain customer demand data, and structure circuit board design demand according to the customer demand data, thereby obtaining circuit board design demand data; The circuit board design requirement data is clustered into design requirement patterns, thereby obtaining the circuit board design requirement pattern data; step S1 is specifically as follows: Step S11: obtaining customer demand data, and cleaning the missing values ​​of the customer demand data, thereby obtaining cleaned customer demand data; Step S12: classifying the cleaning customer demand data into customer demand data, thereby obtaining electrical characteristic demand data and physical size demand data; Step S13: Performing physical dimension requirement structural modeling according to the physical dimension requirement data, thereby obtaining a physical dimension structure model; Step S14: structurally integrating the electrical characteristic requirement data into circuit board design requirement data according to the physical size structure model, thereby obtaining circuit board design requirement data; Step S15: clustering the circuit board design requirement data into design requirement patterns, thereby obtaining circuit board design requirement pattern data; Step S2: Obtaining a circuit board historical design log, and performing circuit board hierarchical design clustering according to the circuit board historical design log, thereby obtaining historical circuit board hierarchical design data; Based on the historical circuit board level design data, the circuit board level wiring structure topology structure analysis is performed to obtain the circuit board level wiring structure model set; step S2 is specifically: Step S21: obtaining a circuit board historical design log, and performing circuit board hierarchical design clustering according to the circuit board historical design log, thereby obtaining historical circuit board hierarchical design data; Step S22: extracting hierarchical structure features from historical circuit board hierarchical design data, thereby obtaining circuit board hierarchical structure data; Step S23: performing hierarchical structure classification according to the hierarchical structure data of the circuit board, thereby obtaining hierarchical wiring structure data and hierarchical component structure data; Step S24: performing spatial distribution statistics of the hierarchical components according to the hierarchical component structure data, thereby obtaining spatial distribution data of the hierarchical components; Step S25: performing spatial association of hierarchical component electrical connection data with hierarchical component spatial distribution data and hierarchical wiring structure data, thereby obtaining hierarchical component electrical connection data; Step S26: performing topological structure analysis of the circuit board hierarchical wiring structure according to the hierarchical component electrical connection data, thereby obtaining a circuit board hierarchical wiring structure model set; Step S3: quantifying the wiring requirements of the circuit board based on the circuit board design requirement model data, thereby obtaining the wiring requirement data of the circuit board, and matching the circuit board hierarchical wiring structure model set with the circuit board hierarchical wiring structure according to the circuit board wiring requirement data, thereby obtaining the circuit board matching hierarchical wiring structure model; Step S3 is specifically: Step S31: extracting design requirement pattern features based on the circuit board design requirement pattern data, thereby obtaining hierarchical design requirement pattern data and wiring design requirement pattern data; Step S32: performing hierarchical structure quantization on the hierarchical design requirement pattern data, thereby obtaining a hierarchical design structure quantization model, and performing wiring requirement numerical quantization on the wiring design requirement data according to the hierarchical design structure quantization model, thereby obtaining circuit board wiring requirement data; Step S33: extracting hierarchical wiring features from the circuit board hierarchical wiring structure model set, thereby obtaining a circuit board hierarchical wiring structure data set; Step S34: performing wiring similarity calculation on the circuit board hierarchical wiring structure data set and the circuit board wiring requirement data, thereby obtaining wiring similarity data; Step S35: selecting a circuit board level wiring structure for the circuit board level wiring structure model set according to the wiring similarity, thereby obtaining a circuit board matching level wiring structure model; Step S4: Layout the circuit board components on the circuit board matching hierarchical wiring structure model according to the circuit board design requirement data, thereby obtaining circuit board hierarchical component layout data; plan the signal line direction of the circuit board components on the circuit board matching hierarchical wiring structure model according to the circuit board hierarchical component layout data, thereby obtaining the circuit board hierarchical structure model; Step S5: performing electromagnetic interference simulation on the circuit board hierarchical structure model to obtain electromagnetic interference simulation data, and performing hierarchical structure heat flow balance optimization on the circuit board hierarchical structure model based on the electromagnetic interference simulation data to obtain an optimized structure model of the circuit board; The circuit board design drawing parameters are described for the circuit board optimization structure model, thereby obtaining the printed circuit board design drawing.

2. The method for generating a printed circuit board design drawing according to claim 1, It is characterized in that Step S14 is specifically as follows: Step S141: acquiring historical electrical simulation data of the circuit board, and extracting simulation parameter combinations from the historical electrical simulation data of the circuit board, thereby obtaining simulation physical parameter combinations and simulation electrical parameter combinations; Step S142: performing physical-electrical characteristic correlation analysis on the simulated physical parameter combination and the simulated electrical parameter combination, thereby obtaining physical-electrical characteristic correlation data; Step S143: mapping the physical dimension structure model and the electrical characteristic requirement data according to the physical-electrical characteristic association data, thereby obtaining a circuit board requirement structured model; Step S144: Structuring the circuit board design requirement model to obtain circuit board design requirement data.

3. The method for generating a printed circuit board design drawing according to claim 1, It is characterized in that Step S15 is specifically as follows: Step S151: extracting circuit board level features and circuit board wiring features from the circuit board design requirement data, thereby obtaining circuit board requirement level data and circuit board requirement wiring data; Step S152: performing circuit board required layer count statistics according to the circuit board required layer data, thereby obtaining circuit board required layer count data; Step S153: Calculating the wiring density of the circuit board based on the required wiring data of the circuit board, thereby obtaining the wiring density data of the circuit board; Calculating the curvature of the wiring of the circuit board based on the required wiring data of the circuit board, thereby obtaining the curvature data of the wiring of the circuit board; Step S154: evaluating the wiring complexity of the circuit board according to the required number of layers of the circuit board, the wiring density data of the circuit board, and the wiring curvature data of the circuit board, thereby obtaining the wiring complexity data of the circuit board; Step S155: clustering the circuit board design requirement data into design complexity requirement patterns according to the circuit board routing complexity data, thereby obtaining circuit board design requirement pattern data.

4. The method for generating a printed circuit board design drawing according to claim 1, It is characterized in that Step S25 is specifically as follows: Step S251: integrating component structure function description features on hierarchical component structure data, thereby obtaining component structure function description data; Step S252: clustering component structure function descriptions according to the component structure function description data, thereby obtaining component structure function clustering data; Step S253: performing wiring density statistics according to the hierarchical wiring structure data to obtain wiring density data, and performing high wiring density structure division on the hierarchical wiring structure data according to the wiring density data to obtain high density wiring structure data; Step S254: dividing the hierarchical component spatial distribution data into component-intensive areas, thereby obtaining hierarchical component-intensive area data; Step S255: performing a spatial structure intersection operation on the high-density wiring structure data and the hierarchical component dense area data, thereby obtaining hierarchical component functional module structure data; Step S256: defining the component function module functions of the hierarchical component function module structure data according to the component structure function description data, thereby obtaining hierarchical module division data; Step S257: Integrate the electrical connection relationship of the module components of the hierarchical module division data to obtain hierarchical component electrical connection data.

5. The method for generating a printed circuit board design drawing according to claim 1, It is characterized in that Step S4 is specifically as follows: Step S41: extracting circuit board component requirement features according to the circuit board design requirement data, thereby obtaining circuit board component requirement data, and integrating component function description features of the circuit board component requirement data, thereby obtaining requirement component function description data; Step S42: extracting hierarchical module description features from the hierarchical wiring structure model set of the circuit board, thereby obtaining hierarchical module description data; Step S43: classifying the required component function description data into component function modules according to the hierarchical module description data, thereby obtaining required component function module data; Step S44: extracting hierarchical wiring structure features according to the matching hierarchical wiring structure model of the circuit board, thereby obtaining matching hierarchical wiring structure data; Step S45: performing functional module layout on the matching hierarchical wiring structure data according to the required component functional module data, thereby obtaining functional module layout data, and optimizing component connectivity on the functional module layout data, thereby obtaining circuit board hierarchical component layout data; Step S46: planning the signal line directions of the circuit board components according to the circuit board matching hierarchical wiring structure model according to the circuit board hierarchical component layout data, thereby obtaining the circuit board hierarchical structure model.

6. The method for generating a printed circuit board design drawing according to claim 1, It is characterized in that Step S5 is specifically as follows: Step S51: extracting working condition requirement features from the circuit board design requirement data, thereby obtaining the circuit board working condition requirement data, and setting simulation boundary conditions according to the circuit board working condition requirement data, thereby obtaining simulation boundary conditions; Step S52: performing electromagnetic interference simulation on the circuit board hierarchical structure model according to the simulation boundary conditions, thereby obtaining electromagnetic interference simulation data; Step S53: performing circuit board current distribution analysis according to the electromagnetic interference simulation data to obtain electromagnetic simulation current distribution data, and performing circuit board thermal simulation on the electromagnetic simulation current distribution data to obtain circuit board thermal simulation data; Step S54: Visualizing the heat flow distribution of the circuit board according to the thermal simulation data of the circuit board, thereby obtaining the heat flow distribution data of the circuit board, and identifying the hot spot area of ​​the heat flow distribution data of the circuit board, thereby obtaining the hot spot area data of the circuit board; Step S55: extracting circuit board level component layout features from the circuit board level structure model to obtain circuit board level component layout data, and adjusting the circuit board level component layout data for heat flow balance components according to the circuit board hot spot area data to obtain heat flow balance component layout data; Step S56: Optimizing the circuit board hierarchical structure model according to the heat flow balancing component layout data to obtain the circuit board optimized structure model, and describing the circuit board design drawing parameters of the circuit board optimized structure model to obtain the printed circuit board design drawing.

7. A system for generating printed circuit board design drawings, It is characterized in that Used to execute the method for generating a printed circuit board design drawing as claimed in claim 1, the system for generating a printed circuit board design drawing comprises: The design requirement pattern clustering module is used to obtain customer requirement data, and structure the circuit board design requirements according to the customer requirement data, thereby obtaining the circuit board design requirement data; and cluster the design requirement patterns of the circuit board design requirement data, thereby obtaining the circuit board design requirement pattern data; A topology analysis module is used to obtain the historical design log of the circuit board, and perform circuit board hierarchical design clustering according to the historical design log of the circuit board, so as to obtain the historical circuit board hierarchical design data; perform circuit board hierarchical wiring structure topology analysis based on the historical circuit board hierarchical design data, so as to obtain the circuit board hierarchical wiring structure model set; A hierarchical wiring structure matching module is used to quantify the wiring requirements of the circuit board based on the circuit board design requirement pattern data, thereby obtaining the wiring requirement data of the circuit board, and to match the hierarchical wiring structure of the circuit board with the hierarchical wiring structure model set of the circuit board according to the wiring requirement data of the circuit board, thereby obtaining the matching hierarchical wiring structure model of the circuit board; The component layout planning module is used to perform circuit board component layout on the circuit board matching hierarchical wiring structure model according to the circuit board design requirement data, thereby obtaining circuit board hierarchical component layout data; and to perform circuit board component signal line direction planning on the circuit board matching hierarchical wiring structure model according to the circuit board hierarchical component layout data, thereby obtaining the circuit board hierarchical structure model; The hierarchical heat flow balance optimization module is used to perform electromagnetic interference simulation on the hierarchical structure model of the circuit board to obtain electromagnetic interference simulation data, and to perform hierarchical heat flow balance optimization on the hierarchical structure model of the circuit board based on the electromagnetic interference simulation data to obtain the optimized structure model of the circuit board; and to perform circuit board design drawing parameter description on the optimized structure model of the circuit board to obtain the printed circuit board design drawing.

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