Multi-layer PCB broken line feeding path planning method and system based on CAD

Abstract

The invention discloses a multi-layer PCB broken line feeding path planning method and system based on CAD, and relates to the technical field of broken line feeding path planning, and the method comprises the steps: extracting multi-layer PCB design data based on a CAD design drawing; processing area classification is carried out according to the extracted multi-layer PCB design data, and a processing distribution characteristic graph is constructed; carrying out feed parameter optimization configuration, and carrying out configuration labeling; and on the basis of the broken line feeding constraint condition of the configuration label, connection parameter transition processing is carried out on adjacent feeding so as to meet a connection path of feeding target maximization, and a broken line feeding planning path is constructed. According to the multi-layer PCB broken line feeding path planning method and device, the technical problems that in the prior art, multi-layer PCB feeding path planning lacks precise constraint, machining parameter adaptability is insufficient, and consequently machining precision is low and stability is poor are solved, and the technical effects that precise planning of the multi-layer PCB broken line feeding path is achieved, and the machining precision and stability of the multi-layer PCB are improved are achieved.

Description

Technical Field

[0001] This invention relates to the field of polyline toolpath planning technology, specifically to a method and system for polyline toolpath planning of multilayer PCBs based on CAD. Background Technology

[0002] With the rapid development of electronic devices towards high density and miniaturization, the application of multilayer PCBs is becoming increasingly widespread. Their processing accuracy, stability, and efficiency are crucial to product performance. Currently, in multilayer PCB processing, traditional toolpath planning relies heavily on empirical parameter configuration, lacking in-depth analysis and precise matching of key information such as multilayer structure, hole contours, and material properties from CAD design data. This results in ambiguous processing area classification, insufficient adaptability of toolpath parameters, and unclear path connection constraints during polygonal toolpath processing, easily leading to problems such as frequent tool lifting, disordered parameter switching, and high processing defect rates, making it difficult to meet the high-precision and high-stability processing requirements of multilayer PCBs.

[0003] In existing technologies, the tool path planning for multilayer PCBs lacks precise constraints and the adaptability of processing parameters is insufficient, resulting in technical problems such as low processing accuracy and poor stability. Summary of the Invention

[0004] This application provides a CAD-based method and system for planning multi-layer PCB toolpaths along polygonal lines, which addresses the technical problems of low machining accuracy and poor stability caused by the lack of precise constraints and insufficient adaptability of machining parameters in existing multi-layer PCB toolpath planning.

[0005] In view of the above problems, this application provides a method and system for planning toolpaths for multi-layer PCB polylines based on CAD.

[0006] The first aspect of this application provides a CAD-based method for planning toolpath routing for multi-layer PCBs with polygonal lines, the method comprising:

[0007] Multilayer PCB design data is extracted from CAD design drawings, including layer sequence relationships, thickness information, trace distribution, hole diameter and contour geometric features, and material information. Processing areas are categorized according to the extracted multilayer PCB design data, and a processing distribution feature map is constructed. Tool path parameters are optimized and configured based on the processing distribution feature map, and configuration annotations are added, including planar XY coordinate tool path annotations and height Z coordinate tool constraint annotations. Based on the configured polyline tool path constraints, connection parameter transition processing is performed on adjacent tool paths to maximize the tool path target, constructing a polyline tool path planning path, including path mapping tool path parameters.

[0008] A second aspect of this application provides a CAD-based multilayer PCB toolpath planning system, the system comprising:

[0009] The design data extraction module is used to extract multi-layer PCB design data based on CAD design drawings, including layer sequence relationships, thickness information, trace distribution, hole diameter and contour geometric features, and material information. The processing distribution feature map construction module is used to classify processing areas according to the extracted multi-layer PCB design data and construct a processing distribution feature map. The configuration annotation module is used to optimize the tool path parameters according to the processing distribution feature map and perform configuration annotation, including planar XY coordinate tool path annotation and height Z coordinate tool path constraint annotation. The planning path construction module is used to perform connection parameter transition processing on adjacent tool paths based on the configured annotation of polyline tool path constraints to maximize the connection path of the tool path objective and construct a polyline tool path planning path, including path mapping tool path parameters.

[0010] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0011] Multi-layer PCB design data is extracted from CAD design drawings. Processing areas are categorized according to the extracted multi-layer PCB design data, and a processing distribution feature map is constructed. Tool path parameters are optimized and configured based on the processing distribution feature map, and the configurations are annotated. Based on the annotated polyline tool path constraints, transitional processing of connection parameters is applied to adjacent tool paths to maximize the tool path objective, thus constructing a polyline tool path planning path, including path mapping tool path parameters. This achieves precise planning of multi-layer PCB polyline tool paths, improving the technical effect of increasing the accuracy and stability of multi-layer PCB processing. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 A schematic flowchart of a CAD-based multilayer PCB polyline toolpath planning method provided in an embodiment of this application;

[0014] Figure 2 A schematic diagram of a CAD-based multilayer PCB toolpath planning system provided in this application embodiment.

[0015] Figure labeling: Design data extraction module 10, processing distribution feature map construction module 20, configuration annotation module 30, planning path construction module 40. Detailed Implementation

[0016] This application provides a CAD-based method and system for planning multi-layer PCB toolpaths along polygonal lines, which addresses the technical problems of low machining accuracy and poor stability caused by the lack of precise constraints and insufficient adaptability of machining parameters in existing multi-layer PCB toolpath planning.

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0018] Example 1, as Figure 1 As shown, this application provides a CAD-based method for planning toolpaths for multi-layer PCB polylines, the method comprising:

[0019] Step S100: Extract multi-layer PCB design data based on CAD design drawings, including layer sequence relationship, thickness information, trace distribution, hole diameter and contour geometry features, and material information.

[0020] Specifically, using CAD design drawings of multi-layer PCBs as the core data source, CAD data parsing tools are used to extract structured and refined data from the design drawings, comprehensively capturing the key design data required for multi-layer PCB processing. This includes the layer sequence relationship between each PCB layer, the specific thickness information of each layer, the detailed routing distribution of circuits on the board surface, the aperture size of various through-holes / blind holes and the geometric feature parameters of the overall PCB outline, as well as the material property information of core components such as PCB substrate and copper plating. This ensures that the extracted data fully covers the core dimensions required for subsequent processing area classification, tool path parameter configuration, and path planning, providing accurate and comprehensive basic data support for the entire polyline tool path planning process.

[0021] Step S200: Classify the processing areas according to the extracted multilayer PCB design data and construct a processing distribution feature map.

[0022] Specifically, based on historical sample datasets, the process causal relationship between multi-layer PCB design data, such as layer sequence and thickness information, and tooling parameters is analyzed, along with the corresponding finished product probability and error probability. Based on this, a response relationship matrix is ​​established between design data and tooling parameters, including positive and negative relationships. The matrix elements represent the degree of influence of design features on corresponding tooling parameters. By comparing and analyzing the influence of each design feature on tooling parameters in the matrix, design features that have an influence on at least one tooling parameter higher than a preset threshold or that can cause changes in tooling parameters are identified as classification parameters. Multi-layer PCB design data is matched and identified according to the classification parameters to clarify the classification response parameters and response coefficients for each design data point. Finally, the processing areas are accurately classified based on the classification response parameters and response coefficients. Combining the distribution location relationships of each classification area, a processing distribution feature map that clearly presents the division and spatial correlation characteristics of the processing areas is constructed.

[0023] Step S300: Optimize the tool path parameters according to the machining distribution feature map and make configuration annotations, including plane XY coordinate tool path annotations and height Z coordinate tool constraint annotations.

[0024] Specifically, for each processing category region in the processing distribution feature map, adjustable parameters that influence the processing results corresponding to the tool path parameters are extracted as optimization variables, combining region type, layer information, and spatial distribution relationships. Based on these optimization variables, a preset evaluation function is used to fit historical tool path sample data, reflecting the processing effect of different tool path parameters under the corresponding optimization variable conditions. Candidate tool path parameters are evaluated and optimized to select the target optimization tool path parameters that achieve the best evaluation results for the optimization variables. The target optimization tool path parameters are split into horizontal plane tool path parameters and vertical height tool path parameters. Based on the horizontal plane tool path parameters in the XY coordinate plane, the tool path direction, polyline form, step distance, and path connection method are labeled as path attributes to the corresponding tool path segments and polyline corner positions, completing the plane XY coordinate tool path labeling. Based on the vertical height tool path parameters in the Z coordinate height, the tool path depth, layer constraints, and height change rules are labeled as height constraints to the start point, end point, or path interval of the corresponding tool path, completing the height Z coordinate tool path constraint labeling, realizing the precise configuration and visual labeling of tool path parameters.

[0025] Step S400: Based on the configured and labeled polyline tool path constraints, perform transition processing on the connection parameters of adjacent tool paths to maximize the connection path of the tool path objective, and construct the polyline tool path planning path, which includes the path mapping tool path parameters.

[0026] Specifically, firstly, based on the configuration annotations, the tool path parameters corresponding to each processing zone are extracted to construct a parameter constraint set. Then, combined with multilayer PCB design data, the process-sensitive attributes and corresponding sensitive constraint parameters of areas with high probability of processing defects affecting process stability are extracted. Simultaneously, based on the geometric characteristics of the polygonal tool path, the corner angles, path direction, and connection methods of the tool path are analyzed for routing constraints to extract polygonal tool path constraint parameters. The sensitive constraint parameters and polygonal tool path constraint parameters are integrated to form polygonal tool path constraint conditions. Based on these constraints, the tool path in each processing area is divided into path units carrying tool path direction, polygonal angle, and height constraint information. From the endpoints of the path units, endpoints that do not violate the tool path direction constraint and height entry condition are selected to construct a candidate starting point set. Through evaluation... The process considers the number of tool lifts, path continuity, and tool path parameter switching. The endpoint with fewer tool lifts and higher parameter continuity is selected as the machining start point. Starting from the machining start point, the execution order of adjacent path units is optimized using parameterized transition. If a forward connection does not meet the constraints, a reverse connection is attempted. If the reverse connection still does not meet the constraints, the second tool path is limited to return along the original path of the first tool path. If the machining area is a strip hole or a linear structure, continuous operation in a single direction is adopted, and the connection direction consistency is constrained. Connection methods requiring additional tool lifts or violating constraints are filtered out to form a continuous tool path. Finally, the path is edited using CAM software to convert the continuous tool path into a CNC execution path containing a sequence of machining coordinate points. This completes the construction of a polyline tool path planning path that includes path mapping tool parameters and maximizes the tool path objective.

[0027] In one possible implementation, step S200 further includes:

[0028] Step S210: Establish the response relationship between each design data and tool feed parameters, and filter and classify parameters.

[0029] Step S220: Match and identify the multilayer PCB design data according to the classification parameters to determine the classification response parameters and response coefficients of each design data.

[0030] Step S230: Classify the processing area based on the classification response parameters and response coefficients, and construct the processing distribution feature map according to the distribution location relationship of the classification areas.

[0031] Specifically, based on historical sample datasets, the process causal relationships between multilayer PCB design data, such as layer sequence, thickness information, and trace distribution, and tooling parameters are analyzed in depth, while the corresponding finished product probability and error probability are clarified. Based on these process causal relationships, finished product probability, and error probability, a response relationship, including positive and negative relationships, is established between design data and tooling parameters to reflect the type of tooling influence of process parameters on design data. Then, a response relationship matrix is ​​constructed based on this response relationship, with matrix elements representing the degree of influence of each design feature on the corresponding tooling parameter. Based on a comparative analysis of the influence degree of each design feature on the response relationship matrix, design features whose influence on at least one tooling parameter exceeds a preset threshold or that can cause changes in the corresponding tooling parameter are identified as classification parameters for processing areas.

[0032] An algorithm combining K-nearest neighbor feature matching and multiple linear regression is employed. First, the selected classification parameters are used as core feature dimensions to construct a standardized feature space. Then, extracted multilayer PCB design data, such as layer sequence relationships and thickness information, undergo feature normalization. This data is then input into the feature space and the feature templates corresponding to the classification parameters for K-nearest neighbor matching. By calculating the Euclidean distance, the K most similar historical sample features to each design data are selected. The tool path parameter correlation attributes corresponding to these samples are determined as the classification response parameters for that design data. Simultaneously, based on the process causal relationship between design data and classification parameters in historical samples, a multiple linear regression model is constructed, using design data feature values, corresponding finished product probabilities, and error probabilities as independent variables, and the influence degree of the tool path parameters corresponding to the classification response parameters as the dependent variable. The model coefficients are solved using the least squares method. After normalization, these coefficients become the response coefficients of each design data under the corresponding classification response parameters. The absolute value of the coefficient represents the influence intensity, with positive and negative values ​​corresponding to positive or negative response relationships, thus achieving accurate determination of the classification response parameters and response coefficients.

[0033] An algorithm based on fuzzy C-means clustering is adopted. The classification response parameters corresponding to each design data are used as clustering feature dimensions, and the response coefficients are used as feature weights to construct a weighted feature vector. Using the weighted feature vector as input, the cluster center is determined by iteratively optimizing the objective function. PCB areas corresponding to design data with feature similarity higher than the clustering threshold are divided into the same processing category, achieving accurate clustering and classification of processing areas. After classification, the spatial coordinate information of each processing category is combined to sort out the distribution location, boundary range and mutual adjacency relationship of different category areas on the PCB board. Layer visualization technology is used to overlay classification labels, area boundary lines and category attribute labels on the CAD design drawing to construct a processing distribution feature map that can intuitively present the processing area classification results, spatial distribution characteristics and correlation relationships, providing a clear visual reference for subsequent tooling parameter configuration and path planning.

[0034] In one possible implementation, step S210 further includes:

[0035] Step S211: Based on the historical sample dataset, analyze the process causal relationship between each design data and tool path parameters, as well as the corresponding finished product probability and error probability.

[0036] Step S212: Based on the process causal relationship and the corresponding finished product probability and error probability, establish the response relationship between the design data and the tool feed parameters, including positive and negative relationships, to reflect the type of tool feed influence of process parameters on the design data.

[0037] Specifically, the process begins by collecting a historical processing sample dataset covering multilayer PCBs of different specifications. This dataset must fully include the design data for each sample, such as layer sequence relationships, thickness information, trace distribution, aperture and contour geometry, material information, and corresponding machining tooling parameters, such as tooling speed, step distance, depth, polygonal angle, and tool lift-off height. It also includes the finished product's quality inspection results and detailed records of machining errors, such as dimensional deviations, trace damage, and interlayer misalignment, along with their quantified values. Subsequently, a combination of data mining and process mechanism analysis is used to perform multi-dimensional decomposition and correlation analysis of the historical sample data. The process logic clarifies the inherent causal relationship between each design data item and tool feed parameters, such as the matching logic between material hardness data and tool feed speed, the matching relationship between hole diameter and tool feed depth, and the corresponding rules between layer sequence relationship and height constraint parameters. At the same time, for each combination of design data and tool feed parameters, the percentage of qualified finished products is statistically analyzed to determine the probability of finished products, and the percentage of machining errors and the severity of errors are statistically analyzed to determine the probability of errors. Finally, a structured list of process causal relationships and a statistical matrix of finished product probability-error probability are formed, providing accurate and comprehensive data support for the establishment of subsequent response relationships.

[0038] Based on the causal relationship between the design data and tool feed parameters obtained from analysis, this paper constructs a response relationship system between design data and tool feed parameters, combining the corresponding statistical results of finished product probability and error probability. When a certain design data, such as an increase in material hardness or an increase in hole diameter, changes, if the corresponding tool feed parameters, such as a decrease in tool feed speed or an increase in tool feed depth, need to be adjusted in a specific direction to improve the finished product probability and reduce the error probability, and this conforms to the causal logic of the process, then the design data and tool feed parameters are determined to have a positive relationship. If a design data, such as an increase in line density or a decrease in plate thickness, changes, if the tool feed parameters, such as a decrease in step distance or a decrease in tool feed pressure, need to be adjusted in the opposite direction to ensure processing quality and process stability, and this is consistent with the causal logic of the process, then the two are determined to have a negative relationship. Through this method, the paper systematically sorts out the correlation types between all design data and tool feed parameters, clarifies the specific influence rules of different design data on tool feed parameters, and forms a complete response relationship system.

[0039] In one possible implementation, step S210 further includes:

[0040] Step S213: Based on the response relationship, construct a response relationship matrix, where the matrix elements are used to characterize the degree of influence of the design features on the corresponding tool feed parameters.

[0041] Step S214: Based on the response relationship matrix, compare and analyze the degree of influence of each design feature on the tool path parameter. When the degree of influence of the design feature on at least one tool path parameter is higher than the preset threshold, or causes the corresponding tool path parameter to change, the design feature is determined as the classification parameter for the processing area classification.

[0042] Specifically, based on the established positive and negative response relationships between design data and tooling parameters, a structured two-dimensional response relationship matrix is ​​constructed. The row dimension of the matrix clearly corresponds to various design features of multilayer PCBs, covering layer sequence relationships, thickness information, trace distribution, hole diameter and contour geometry features, material information, etc. The column dimension corresponds to various tooling parameters required for processing, including tooling speed, step distance, tooling depth, polygonal angle, tool lift-off height, etc. Each element in the matrix is ​​quantitatively assigned to accurately represent the degree of influence, using a numerical range of [-1, 1], where positive values ​​correspond to positive response relationships and negative values ​​correspond to negative response relationships. The absolute value of the value directly reflects the strength of the influence of the design feature on the corresponding tooling parameter. The closer the value is to 1 or -1, the more significant the influence. 0 represents that the design feature has no significant process influence on the corresponding tooling parameter. Finally, a response relationship matrix is ​​formed that can systematically and quantitatively present the correlation between design features and tooling parameters.

[0043] Based on the constructed response relationship matrix, the numerical quantification analysis of matrix elements is used to systematically analyze and compare the influence values ​​of all tooling parameters, such as tooling speed and step distance, corresponding to each design feature, such as hierarchical relationships and material information. This clarifies the differences in the intensity of influence of each design feature on different tooling parameters. A preset threshold for the degree of influence is set, determined based on historical machining process requirements and quality control standards. If the absolute value of the influence of a design feature on at least one tooling parameter is higher than the preset threshold, it indicates that it has a significant impact on the tooling parameter and should be included in the classification parameters. Simultaneously, combined with the actual process logic, if a change in a design feature directly triggers an adaptive adjustment of the corresponding tooling parameter (e.g., a change in hole diameter requires a simultaneous adjustment of the tooling depth), even if its influence does not reach the preset threshold, it is considered that the design feature plays a key role in the classification of the machining area and is determined as a classification parameter. Finally, all design features that meet the requirements are screened through the above dual judgment criteria to form a set of classification parameters for machining area classification.

[0044] In one possible implementation, step S300 further includes:

[0045] Step S310: For each processing category region in the processing distribution feature map, based on the region type, layer information and spatial distribution relationship, extract optimization variables. The optimization variables are adjustable parameters that have an influence relationship with the processing results corresponding to the tool feed parameters.

[0046] Step S320: Based on the optimization variables, the candidate tool path parameters are evaluated and optimized using a preset evaluation function to determine the target tool path parameters. The target tool path parameters are the tool path parameters that yield the best evaluation results for the optimization variables. The evaluation function is obtained by evaluating and fitting based on historical tool path sample data and is used to reflect the processing effect of different tool path parameters under the corresponding optimization variable conditions.

[0047] Step S330: Extract the horizontal plane parameters and vertical height parameters of the optimized target tool path parameters, and configure and label them in the machining distribution feature map based on the extracted horizontal plane parameters and vertical height parameters. The horizontal plane parameters correspond to the tool path label in the plane XY coordinate, and the vertical height parameters correspond to the tool constraint label in the height Z coordinate.

[0048] Specifically, for each processing area already classified in the processing distribution feature map, and combined with the specific type of each area, such as aperture processing area, trace engraving area, contour cutting area, etc., and the multi-layer PCB layer information to which it belongs, including layer sequence position, inter-layer relationship, spatial distribution position of each area on the PCB board, relative position and overlap of adjacent areas, we identify the key factors affecting processing quality, efficiency and stability, and accurately extract the processing results corresponding to the tool path parameters, such as processing accuracy, surface roughness, and finished product pass rate, which have a direct impact and can be flexibly adjusted according to processing needs, as optimization variables. For example, area processing accuracy threshold, line density adaptation coefficient, inter-layer switching transition parameters, adjacent area avoidance margin, etc., to ensure that the extracted optimization variables can comprehensively cover the core impact dimensions of tool path parameter adjustment on processing effect, providing precise constraints and target guidance for subsequent tool path parameter optimization.

[0049] A parameter optimization approach based on a genetic algorithm is employed. Extracted optimization variables, such as machining accuracy thresholds and line density adaptation coefficients, are used as constraints to construct a population of candidate toolpath parameters, including dimensions such as toolpath speed, step distance, toolpath depth, and polygonal angle. A pre-defined evaluation function is used as the fitness function. This function is obtained by weighted fitting of multiple machining effect indicators, such as machining accuracy, efficiency, and finished product qualification rate, from a large amount of historical toolpath sample data. This accurately quantifies the comprehensive machining performance of different toolpath parameters under the corresponding optimization variable conditions. The candidate toolpath parameter population is iteratively optimized through selection, crossover, and mutation operations of the genetic algorithm. In each iteration, the evaluation results of each candidate parameter are calculated based on the fitness function, and the parameter individuals with better evaluation results are selected to enter the next generation of the population. This process continues until the preset number of iterations is reached or the evaluation results stabilize. Finally, the candidate toolpath parameter with the highest fitness, i.e., the best evaluation result, is determined as the target toolpath parameter, achieving precise adaptation between the toolpath parameters, optimization variables, and machining effects.

[0050] First, a parameter dimension decomposition algorithm is used to structurally decompose the determined optimization target toolpath parameters, accurately extracting the horizontal plane parameters used to define the movement trajectory in the PCB board plane, including toolpath direction, polyline type, step size, path connection method, etc., and the vertical height parameters used to control the vertical processing requirements, including toolpath depth, layer constraint range, height change transition rules, etc. Then, based on the coordinate system of the processing distribution feature map, on the XY coordinate plane, the toolpath direction arrows, polyline type identifiers (such as right angle / rounded corner), step size values, and path connection modes corresponding to the horizontal plane parameters are accurately marked to the corresponding toolpath segments and polyline corner positions, completing the visual annotation of the toolpath in the XY coordinate plane. At the same time, in the height Z coordinate, the toolpath depth values, layer adaptation identifiers (such as top / bottom layer exclusive annotations and height switching rule descriptions) corresponding to the vertical height parameters are marked to the start point, end point, or specific path interval of the corresponding toolpath, realizing a clear presentation of the height Z coordinate toolpath constraints, ensuring that the optimization target toolpath parameters are accurately implemented through coordinate annotation.

[0051] In one possible implementation, step S330 further includes:

[0052] Step S331: Decompose the optimized target tool path parameters into transverse plane tool path parameters and longitudinal height tool path parameters.

[0053] Step S332: Based on the transverse plane tool path parameters, on the XY coordinate plane, mark the tool path direction, polyline form, step distance, and path connection method as path attributes to the corresponding tool path segments and polyline corner positions.

[0054] Step S333: Based on the longitudinal height tool path parameters, in the height Z coordinate, mark the tool path depth, layer constraints, and height change rules as height constraints to the start point, end point, or path interval of the corresponding tool path.

[0055] Specifically, a parameter-dimensional structured decomposition method is adopted, using processing dimension attributes as the basis for division, to systematically decompose the determined optimization target toolpath parameters. Among them, the parameters related to defining the toolpath in the plane of the multi-layer PCB board are classified as horizontal plane toolpath parameters, covering core attributes such as toolpath direction, polyline form, step size, and path connection method. The parameters related to controlling the processing requirements in the vertical direction are classified as vertical height toolpath parameters, including key contents such as toolpath depth, layer constraint range, and height change transition rules. Through clear dimensional division, the toolpath parameters are accurately decomposed, laying the foundation for the subsequent configuration and annotation of the sub-coordinate system.

[0056] Based on the horizontal plane tool path parameters obtained from the decomposition, and relying on the planar XY coordinate system of the machining distribution feature map, a visual annotation technology is used to accurately mark the tool path direction with arrow symbols at the central axis position of the corresponding tool path segment. The arrow points in the same direction as the actual tool path movement. Polyline forms, such as right-angled polylines and rounded polylines, are marked with exclusive graphic symbols, such as right-angle symbols and arc symbols, at the corners of the polylines. The step distance is marked with specific values ​​on the side of the tool path segment and aligned parallel to the segment. The path connection method, such as continuous connection, segmented connection, and overlapping connection, is marked with specific association symbols at the junction of adjacent tool path segments. This ensures that the core path attributes, such as tool path direction, polyline form, step distance, and path connection method, are accurately bound to the corresponding tool path segments and polyline corners, achieving a clear and visual presentation of the tool path attributes in the planar XY coordinate system, providing an intuitive basis for subsequent tool path execution and verification.

[0057] Based on the vertical height toolpath parameters obtained from the decomposition, and relying on the height Z-coordinate system of the processing distribution feature map, a layered constraint annotation mechanism is adopted. The specific quantitative values ​​of the toolpath depth, the multi-layer PCB layer identifiers corresponding to the layer constraints (such as top layer L1, middle layer L3, bottom layer L6, etc.), and the height change rules (such as the gradual transition height during layer switching, fixed value jump mode, prohibited height range, etc.) are used as key height constraint information. These are accurately annotated to the starting point of the corresponding toolpath, thus clarifying the initial processing height and the ending point (i.e., clarifying the termination processing height or specific path range), thus clarifying the height control requirements of this path segment. By combining annotation symbols and values, the vertical processing standards of different path segments are clearly defined, ensuring that the height dimension constraint requirements during the toolpath process can be accurately identified and implemented without ambiguity. This provides a clear basis for the continuous execution and inter-layer adaptation of the subsequent polyline toolpath.

[0058] In one possible implementation, step S400 further includes:

[0059] Step S410: Based on the configuration annotations, extract the corresponding annotation tool path parameters for each machining partition and construct a parameter constraint set.

[0060] Step S420: Based on the parameter constraint set and the design data, extract the regional process-sensitive attributes and the corresponding sensitive constraint parameters. The regional process-sensitive attributes are attributes that have a high probability of affecting the process stability of the processing area and the existence of processing defects.

[0061] Step S430: Based on the geometric characteristics of the polyline tool path, perform path constraint analysis on the polyline corner angle, path direction and connection method, and extract the polyline tool path constraint parameters.

[0062] Step S440: Integrate the sensitive constraint parameters with the polyline tool path constraint parameters to obtain the polyline tool path constraint conditions.

[0063] Specifically, the data source is the already completed planar XY coordinate toolpath annotations and height Z coordinate toolpath constraint annotations in the machining distribution feature map. The annotation parameter extraction is adopted, and the annotation toolpath parameters corresponding to each machining zone are filtered and extracted one by one. These parameters cover the toolpath direction, polyline form, step distance, path connection method in the horizontal plane, and the toolpath depth, layer constraint, height change rules in the vertical height. These parameters are classified and organized according to the machining zone to form a structured parameter constraint set.

[0064] Based on the established parameter constraint set, and integrating the multilayer PCB design data extracted from the initial CAD design drawings, covering core information such as layer sequence relationships, material hardness, hole size, trace density, and contour geometry, an algorithm combining process sensitivity analysis and defect risk assessment is employed. By mining the intrinsic correlation between design data, parameter constraints, and process stability and defect risk, process-sensitive attributes affecting process stability, such as tool path smoothness and interlayer compatibility, and those with high probability of processing defects, such as short circuits, interlayer misalignment, and surface damage, are identified. Examples include trace spacing compatibility attributes in high-density trace areas, tool pressure compatibility attributes in brittle material areas, height transition attributes in multilayer board interlayer switching areas, and tool depth compatibility attributes in small-diameter hole processing areas. Simultaneously, for each selected process-sensitive attribute, corresponding sensitive constraint parameters are extracted by combining historical processing defect cases and process optimization experience. These include upper limit constraints on step distance for trace spacing, lower limit constraints on tool speed and pressure threshold constraints for brittle materials, height change rate constraints for interlayer switching, and tool depth accuracy constraints for small-diameter holes, forming a structured set of sensitive constraint parameters.

[0065] Based on the geometric characteristics of polygonal toolpaths, a geometric constraint analysis algorithm is employed to systematically analyze the core geometric elements of the toolpath. For polygonal corner angles, by analyzing machining process feasibility and equipment movement limits, the minimum allowable corner angle is determined to avoid equipment jamming or machining accuracy deviations, and the maximum corner transition radius is determined to adapt to the machining space requirements of different areas. These two key constraint parameters are extracted. For path direction, based on the spatial distribution of the machining area and the positional relationship of adjacent path units, the direction deviation threshold of adjacent path units is defined to ensure smooth path connection, and the directional consistency requirement for continuous toolpaths is defined to reduce frequent parameter switching. These two key constraint parameters are extracted. For path connection methods, considering machining quality and efficiency requirements, allowed connection types include direct straight-line connections and arc transition connections, while prohibited connection modes include cross connections and sharp-angle hard connections, which are prone to machining defects. These key constraint parameters are extracted. Through the above multi-dimensional geometric constraint analysis, polygonal toolpath constraint parameters covering corner angles, path direction, and connection methods are accurately extracted, providing rigid geometric constraints for subsequent constraint integration and path optimization.

[0066] A constraint parameter fusion algorithm is employed to integrate sensitive constraint parameters and polyline toolpath constraint parameters. First, the specific content of both types of parameters is comprehensively reviewed, eliminating duplicate or conflicting constraints to ensure the integrated parameter system is free of redundancy and contradictions. Next, constraint parameters are categorized and merged according to constraint type, classifying all parameters into different categories such as process stability constraints, geometric constraints, and machining quality constraints, making the constraint logic clearer and more orderly. Then, the priority of each constraint parameter is determined, with constraints affecting machining accuracy having higher priority than those affecting machining efficiency, ensuring that core machining requirements are met first. Through this series of processes, a multi-dimensional, logically unified, and clearly prioritized polyline toolpath constraint condition is ultimately formed, encompassing process-sensitive constraints, geometric constraints, and parameter adaptation constraints.

[0067] In one possible implementation, step S400 further includes:

[0068] Step S450: Based on the machining zones and the corresponding tool path parameter configuration annotations, the tool path in each machining area is divided into path units carrying tool path direction, polyline angle and height constraint information.

[0069] Step S460: Under the premise of satisfying the polyline tool path constraint, select endpoints from the endpoints of the path unit that do not violate the tool path direction constraint and height entry condition, and construct a candidate starting point set.

[0070] Step S470: For the candidate starting point set, evaluate based on the number of tool lifts, path continuity, and tool path parameter switching, and search for the endpoint with fewer tool lifts and higher parameter continuity as the machining starting point.

[0071] Step S480: Starting from the machining start point, perform parameterized transition optimization on the execution order of adjacent path units, filter out connection methods that require additional tool lifting or violate tool travel direction constraints, and form a continuous tool travel path as the polyline tool travel planning path; wherein, it also includes: using CAM software to edit the path and convert the polyline tool travel planning path into a CNC execution path containing a sequence of machining coordinate points.

[0072] Specifically, based on the defined machining zones, and combined with the completed toolpath parameter configuration annotations within each zone, covering toolpath annotations in the XY coordinates and toolpath constraint annotations in the Z coordinate, a path unit structured decomposition algorithm is employed to accurately decompose the complete toolpath within each machining area. During the decomposition process, it is ensured that each formed independent path unit fully carries key machining information, including a clear toolpath direction, specific polygonal angles, and corresponding height constraint requirements. This ensures that each path unit possesses both independent geometric attributes and clear constraint specifications, providing a standardized basic unit for subsequent path unit selection, connection, and optimization.

[0073] Under the premise of strictly adhering to the integrated polyline toolpath constraints, a comprehensive verification was conducted on each endpoint of all path units that were split and carried with toolpath direction, polyline angle, and height constraint information. During the verification process, the focus was on checking whether each endpoint met the preset toolpath direction constraints, ensuring that the toolpath direction corresponding to the endpoint was consistent with the constraints. Simultaneously, the height parameters of the endpoints were meticulously verified to ensure that they met the height entry standards during machining, guaranteeing smooth startup of subsequent machining. After verification, all endpoints that violated the toolpath direction constraints or did not meet the height entry conditions were eliminated. The remaining endpoints that met the constraints were systematically summarized and organized to construct a standardized set of candidate starting points.

[0074] For each endpoint in the constructed candidate starting point set, a comprehensive evaluation system is established with the number of tool lifts, path continuity, and tool path parameter switching as core dimensions. The comprehensive evaluation score for each endpoint is generated by quantitatively calculating the tool lift frequency, path continuity, and parameter switching frequency. The fewer the tool lifts, the more continuous the path, and the smoother the tool path parameter switching, the higher the evaluation score. Based on the comprehensive evaluation results of each endpoint, a ranking and comparison are performed, and endpoints with fewer tool lifts and higher tool path parameter continuity are selected as the final machining starting point to minimize non-machining time loss during machining and improve tool path stability and machining efficiency.

[0075] Starting from the selected machining starting point, parametric transition optimization is performed on the execution sequence of adjacent path units. During the optimization process, the connection schemes between different path units are comprehensively checked, and connection methods that require additional tool lifting operations or violate preset tool path constraints are strictly filtered out. Connection modes that can achieve smooth transitions are prioritized, and all path units are gradually connected to form an uninterrupted continuous tool path. This continuous tool path is the final polyline tool path planning path. Simultaneously, CAM software is used to professionally edit the constructed polyline tool path planning path. Through the software's coordinate transformation and data processing functions, the planned path is accurately converted into a CNC execution path containing a series of continuous machining coordinate point sequences, ensuring that the path can directly adapt to the operating logic of the CNC machining equipment and meet the precise execution requirements of actual machining.

[0076] In one possible implementation, step S480 further includes:

[0077] Step S481: After determining the execution order of adjacent path units, determine whether the forward connection between adjacent path units according to the current execution order satisfies the polyline tool path constraint condition.

[0078] Step S482: When the forward connection does not satisfy the polyline tooling constraint, determine whether the reverse connection between adjacent path units satisfies the polyline tooling constraint.

[0079] Step S483: When the reverse connection still does not meet the polyline tooling constraint conditions, the second tooling path is restricted to return along the original path of the first tooling path to ensure that the tooling direction, polyline angle and height constraints are not violated.

[0080] Step S484: When the processing area is identified as a strip hole or a linear structure area, the broken line tool path is limited to continuous operation in a single direction, and a consistency constraint is applied to the connection direction of adjacent path units, so that the tool path is executed continuously from left to right or along a preset direction.

[0081] Specifically, after clarifying the execution order of adjacent path units, a comprehensive and detailed verification is conducted on the connection scheme for forward connection of these two adjacent path units according to the currently determined execution order, against the previously integrated polyline toolpath constraints. During the verification process, the forward connection scheme is checked one by one from multiple core dimensions, including consistency of toolpath direction, compliance of polyline angle, matching degree of height constraints, and adaptability of path connection method, to accurately determine whether the forward connection of adjacent path units according to the current execution order can meet the various specifications and standards of polyline toolpath, providing a clear basis for the selection of subsequent path connection methods.

[0082] After comprehensive verification, if it is determined that adjacent path units are connected in a forward direction according to the current predetermined execution order, and there are instances where the forward connection fails to meet the polyline toolpath constraints in core dimensions such as toolpath direction consistency, polyline angle compliance, height constraint matching, and path connection method adaptability—meaning the forward connection cannot satisfy all constraint requirements—then the execution order of the adjacent path units remains unchanged, and a feasibility verification is performed on the reverse connection scheme for these two adjacent path units. The verification process will follow the same standards as the forward connection, checking one by one whether the parameters such as toolpath direction, polyline angle, height constraint, and path connection method in the reverse connection mode all meet the polyline toolpath constraints. This will determine whether the reverse connection can achieve compliant connection of adjacent path units, providing a feasible connection scheme reference for subsequent path optimization.

[0083] After a comprehensive verification of the reverse connection scheme for adjacent path units, it was found that there were still cases where the reverse connection could not meet the constraints of the polyline tool path in core dimensions such as consistency of tool path direction, compliance of polyline angle, matching degree of height constraint, and adaptability of path connection method. In other words, the reverse connection could not meet all the constraint requirements. In order to avoid disrupting the preset tool path direction, polyline angle, and height constraint specifications during the tool path and to ensure the stability and accuracy of the machining process, a specific path connection strategy was adopted. It was clearly stipulated that the second tool path must return along the original path of the first tool path. Through this backtracking connection method, it was ensured that the various constraints during the tool path remained unchanged and no violations occurred, providing a compliant path connection guarantee for the smooth progress of subsequent machining.

[0084] During the parametric transition optimization of the execution sequence of adjacent path units, the structural type of the processing area is identified and judged simultaneously. When the processing area is detected to be a strip hole or a linear structure area, in order to ensure the consistency of processing accuracy, efficiency and quality of such areas, the broken line tool path is explicitly limited to a single-direction continuous operation mode. At the same time, strict consistency constraints are applied to the connection direction of adjacent path units to avoid direction confusion or frequent switching. This ensures that the tool path can be continuously executed in the default direction from left to right or in a pre-set fixed direction, thereby reducing the processing error and time loss caused by direction switching and improving the overall processing effect.

[0085] Example 2, based on the same inventive concept as the CAD-based multilayer PCB toolpath planning method in the previous examples, such as... Figure 2 As shown, this application provides a CAD-based multilayer PCB toolpath planning system. The system and method embodiments in this application are based on the same inventive concept. The system includes:

[0086] Design data extraction module 10 is used to extract multi-layer PCB design data based on CAD design drawings, including layer sequence relationship, thickness information, trace distribution, hole diameter and contour geometry features, and material information.

[0087] The processing distribution feature map construction module 20 is used to classify processing areas according to the extracted multi-layer PCB design data and construct a processing distribution feature map.

[0088] The configuration annotation module 30 is used to optimize the tool path parameters according to the machining distribution feature map and to perform configuration annotation, including plane XY coordinate tool path annotation and height Z coordinate tool path constraint annotation.

[0089] The planning path construction module 40 is used to perform transition processing on the connection parameters of adjacent tool paths based on the configured and labeled polyline tool path constraints, so as to maximize the connection path of the tool path objective and construct the polyline tool path planning path, which includes the path mapping tool path parameters.

[0090] Furthermore, the system is also used to implement the following functions:

[0091] Establish the response relationship between each design data and tooling parameters, and filter classification parameters; match and identify the multilayer PCB design data according to the classification parameters to determine the classification response parameters and response coefficients of each design data; classify the processing area based on the classification response parameters and response coefficients, and construct the processing distribution feature map according to the distribution location relationship of the classification areas.

[0092] Furthermore, the system is also used to implement the following functions:

[0093] Based on historical sample datasets, the process causal relationship between each design data and tool feed parameters, as well as the corresponding finished product probability and error probability, are analyzed. According to the process causal relationship and the corresponding finished product probability and error probability, the response relationship between the design data and tool feed parameters is established, including positive and negative relationships, to reflect the type of tool feed influence of process parameters on design data.

[0094] Furthermore, the system is also used to implement the following functions:

[0095] Based on the response relationship, a response relationship matrix is ​​constructed, where the matrix elements are used to characterize the degree of influence of the design feature on the corresponding tool path parameter. Based on the response relationship matrix, the degree of influence of each design feature on the tool path parameter is compared and analyzed. When the degree of influence of the design feature on at least one tool path parameter is higher than a preset threshold, or causes a change in the corresponding tool path parameter, the design feature is determined as the classification parameter for the processing area classification.

[0096] Furthermore, the system is also used to implement the following functions:

[0097] For each processing category region in the processing distribution feature map, optimization variables are extracted based on region type, layer information, and spatial distribution relationship. These optimization variables are adjustable parameters that have an impact on the processing results corresponding to the tool path parameters. Based on these optimization variables, candidate tool path parameters are evaluated and optimized using a preset evaluation function to determine the target tool path parameters. The target tool path parameters are the tool path parameters that yield the best evaluation results for the optimization variables. The evaluation function is obtained by evaluation fitting based on historical tool path sample data and is used to reflect the processing effect of different tool path parameters under the corresponding optimization variable conditions. The target tool path parameters are extracted for horizontal plane parameters and vertical height parameters, and the extracted horizontal plane parameters and vertical height parameters are configured and labeled in the processing distribution feature map. The horizontal plane parameters correspond to the plane XY coordinate tool path label, and the vertical height parameters correspond to the height Z coordinate tool path constraint label.

[0098] Furthermore, the system is also used to implement the following functions:

[0099] The optimized target toolpath parameters are broken down into horizontal plane toolpath parameters and vertical height toolpath parameters. Based on the horizontal plane toolpath parameters, the toolpath direction, polyline form, step distance, and path connection method are labeled as path attributes on the XY coordinate plane and marked at the corresponding toolpath segments and polyline corner positions. Based on the vertical height toolpath parameters, the toolpath depth, layer constraints, and height change rules are labeled as height constraints on the start point, end point, or path interval of the corresponding toolpath in the Z coordinate height.

[0100] Furthermore, the system is also used to implement the following functions:

[0101] Based on the configuration annotations, corresponding annotation toolpath parameters are extracted for each machining zone to construct a parameter constraint set. Based on the parameter constraint set and the design data, regional process-sensitive attributes and corresponding sensitive constraint parameters are extracted. These regional process-sensitive attributes are those that significantly affect the process stability of the machining area and have a high probability of machining defects. Based on the geometric characteristics of the polygonal toolpath, the polygonal corner angles, path direction, and connection methods of the toolpath are analyzed to extract polygonal toolpath constraint parameters. The sensitive constraint parameters and the polygonal toolpath constraint parameters are integrated to obtain the polygonal toolpath constraint conditions.

[0102] Furthermore, the system is also used to implement the following functions:

[0103] Based on the machining zones and corresponding toolpath parameter configuration annotations, the toolpaths within each machining area are divided into path units carrying toolpath direction, polygonal angle, and height constraint information. Under the premise of satisfying the polygonal toolpath constraints, endpoints that do not violate the toolpath direction constraints and height entry conditions are selected from the endpoints of the path units to construct a candidate starting point set. For the candidate starting point set, evaluation is performed based on the number of tool lifts, path continuity, and toolpath parameter switching, searching for endpoints with fewer tool lifts and higher parameter continuity as machining starting points. Starting from the machining starting point, the execution order of adjacent path units is optimized using parameterized transition, filtering out connection methods requiring additional tool lifts or violating toolpath direction constraints to form a continuous toolpath, which serves as the polygonal toolpath planning path. This also includes: using CAM software to edit the path, converting the polygonal toolpath planning path into a CNC execution path containing a sequence of machining coordinate points.

[0104] Furthermore, the system is also used to implement the following functions:

[0105] After determining the execution order of adjacent path units, it is determined whether a forward connection between adjacent path units in the current execution order satisfies the polygonal tool path constraint condition. If the forward connection does not satisfy the polygonal tool path constraint condition, it is determined whether a reverse connection between adjacent path units satisfies the polygonal tool path constraint condition. If the reverse connection still does not satisfy the polygonal tool path constraint condition, the second tool path is restricted to return along the original path of the first tool path to ensure that the tool path direction, polygonal angle, and height constraints are not violated. When the processing area is identified as a strip hole or a linear structure area, the polygonal tool path is restricted to continuous operation in a single direction, and a consistency constraint is applied to the connection direction of adjacent path units to ensure that the tool path is executed continuously from left to right or along a preset direction.

[0106] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0107] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0108] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application intends to include such modifications and variations.

Claims

1. A CAD-based method for planning toolpath paths for multi-layer PCB polylines, characterized in that, include: Extracting multilayer PCB design data based on CAD design drawings, including layer sequence relationships, thickness information, trace distribution, hole diameter and contour geometry features, and material information; Based on the extracted multilayer PCB design data, the processing areas are classified, and a processing distribution feature map is constructed. The tool path parameters are optimized and configured based on the machining distribution feature map, and the configuration is marked, including the tool path marking in the XY coordinate plane and the tool constraint marking in the Z coordinate height. Based on the configuration-annotated polyline tool path constraints, the connection parameters of adjacent tool paths are processed to achieve the connection path that maximizes the tool path objective, thus constructing a polyline tool path planning path, which includes path mapping tool path parameters.

2. The CAD-based multilayer PCB toolpath planning method according to claim 1, characterized in that, Based on the extracted multilayer PCB design data, the processing areas are classified, and a processing distribution feature map is constructed, including: Establish the response relationship between various design data and tool feed parameters, and filter and classify parameters; The multilayer PCB design data is matched and identified according to the classification parameters to determine the classification response parameters and response coefficients of each design data. The processing areas are classified based on the classification response parameters and response coefficients, and the processing distribution feature map is constructed according to the distribution location relationship of the classified areas.

3. The CAD-based multilayer PCB toolpath planning method according to claim 2, characterized in that, Establish the response relationship between various design data and tool feed parameters, including: Based on historical sample datasets, we analyze the causal relationship between each design data and tool feed parameters, as well as the corresponding finished product probability and error probability. Based on the process causal relationship and the corresponding finished product probability and error probability, a response relationship between the design data and the tool feed parameters is established, including positive and negative relationships, to reflect the type of tool feed influence of process parameters on the design data.

4. The CAD-based multilayer PCB toolpath planning method according to claim 3, characterized in that, Establish the response relationship between various design data and tool feed parameters, and filter and categorize parameters, including: Based on the response relationship, a response relationship matrix is ​​constructed, where the matrix elements are used to characterize the degree of influence of the design features on the corresponding tool feed parameters; Based on the response relationship matrix, the influence of each design feature on the tool path parameter is compared and analyzed. When the influence of a design feature on at least one tool path parameter is higher than a preset threshold, or causes a change in the corresponding tool path parameter, the design feature is determined as the classification parameter for the processing area classification.

5. The CAD-based multilayer PCB toolpath planning method according to claim 1, characterized in that, Based on the machining distribution feature map, the tool path parameters are optimized and configured, and configuration annotations are performed, including: For each processing category region in the processing distribution feature map, optimization variables are extracted based on region type, layer information and spatial distribution relationship. The optimization variables are adjustable parameters that have an impact on the processing results corresponding to the tool feed parameters. Based on the optimization variables, the candidate tool path parameters are evaluated and optimized using a preset evaluation function to determine the target tool path parameters. The target tool path parameters are the tool path parameters that yield the best evaluation results for the optimization variables. The evaluation function is obtained by evaluating and fitting based on historical tool path sample data and is used to reflect the processing effect of different tool path parameters under the corresponding optimization variable conditions. The horizontal plane parameters and vertical height parameters are extracted from the optimized target tool path parameters, and the extracted horizontal plane parameters and vertical height parameters are configured and labeled in the machining distribution feature map. The horizontal plane parameters correspond to the tool path label in the plane XY coordinate, and the vertical height parameters correspond to the tool constraint label in the height Z coordinate.

6. The CAD-based multilayer PCB toolpath planning method according to claim 5, characterized in that, Based on the extracted horizontal plane parameters and vertical height parameters, configuration annotations are performed on the processing distribution feature map, including: The optimized target tool path parameters are broken down into transverse plane tool path parameters and longitudinal height tool path parameters; Based on the transverse plane tool path parameters, the tool path direction, polyline form, step distance, and path connection method are marked as path attributes on the XY coordinate plane and labeled to the corresponding tool path segments and polyline corner positions. Based on the longitudinal height tool path parameters, in the height Z coordinate, the tool path depth, layer constraints, and height change rules are marked as height constraints to the start point, end point, or path interval of the corresponding tool path.

7. The CAD-based multilayer PCB toolpath planning method according to claim 1, characterized in that, Prior to the configuration-annotated polyline toolpath constraints, the following are included: Based on the configuration annotations, extract the corresponding annotation tool path parameters for each machining zone and construct a parameter constraint set; Based on the parameter constraint set and the design data, regional process-sensitive attributes and corresponding sensitive constraint parameters are extracted. The regional process-sensitive attributes are attributes that have a high probability of affecting the process stability of the processing area and the existence of processing defects. Based on the geometric characteristics of the polyline tool path, the corner angle, path direction and connection method of the polyline tool path are analyzed for routing constraints, and the polyline tool path constraint parameters are extracted. The sensitive constraint parameters and the polyline tool path constraint parameters are integrated to obtain the polyline tool path constraint conditions.

8. The CAD-based multilayer PCB toolpath planning method according to claim 7, characterized in that, Based on the configured and labeled polyline toolpath constraints, the connection parameters of adjacent toolpaths are processed to ensure a connection path that maximizes the toolpath objective. This process constructs a polyline toolpath planning path, including: Based on the machining zones and the corresponding tool path parameter configuration labels, the tool path in each machining area is divided into path units carrying tool path direction, polyline angle and height constraint information; Under the premise of satisfying the polyline tool path constraint, the endpoints that do not violate the tool path direction constraint and height entry condition are selected from the endpoints of the path unit to construct a candidate starting point set; For the candidate starting point set, the evaluation is based on the number of tool lifts, path continuity, and tool path parameter switching. The endpoint with fewer tool lifts and higher parameter continuity is searched as the machining starting point. Starting from the machining start point, the execution order of adjacent path units is parametrically optimized, filtering out connection methods that require additional tool lifting or violate tool travel direction constraints, forming a continuous tool travel path as the polygonal tool travel planning path; it also includes: using CAM software to edit the path, converting the polygonal tool travel planning path into a CNC execution path containing a sequence of machining coordinate points.

9. The CAD-based multilayer PCB toolpath planning method according to claim 8, characterized in that, Transitional optimization is performed on the execution order of adjacent path units, including: After determining the execution order of adjacent path units, it is determined whether the forward connection between adjacent path units according to the current execution order satisfies the polyline tool path constraint condition. When the forward connection does not meet the polyline tooling constraint, determine whether the reverse connection between adjacent path units meets the polyline tooling constraint. When the reverse connection still does not meet the polyline tooling constraint conditions, the second tooling is limited to return along the original path of the first tooling path to ensure that the tooling direction, polyline angle and height constraints are not broken. When the processing area is identified as a strip hole or a linear structure area, the broken line tool path is limited to continuous operation in a single direction, and a consistency constraint is applied to the connection direction of adjacent path units, so that the tool path is executed continuously from left to right or along a preset direction.

10. A CAD-based multilayer PCB polyline toolpath planning system, characterized in that, The system is used to implement the CAD-based multilayer PCB toolpath planning method according to any one of claims 1-9, and the system includes: The design data extraction module is used to extract multi-layer PCB design data based on CAD design drawings, including layer sequence relationships, thickness information, trace distribution, hole diameter and contour geometric features, and material information; The processing distribution feature map construction module is used to classify processing areas according to the extracted multi-layer PCB design data and construct a processing distribution feature map. The configuration annotation module is used to optimize the tool path parameters according to the machining distribution feature map and to perform configuration annotation, including plane XY coordinate tool path annotation and height Z coordinate tool constraint annotation. The planning path construction module is used to perform transition processing on the connection parameters of adjacent toolpaths based on the configured and labeled polyline toolpath constraints, so as to maximize the connection path of the toolpath objective and construct the polyline toolpath planning path, which includes the path mapping toolpath parameters.

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