Intelligent drilling path planning method and system for multiple layers of thin plates

Abstract

The invention discloses an intelligent drilling path planning method and system for a multi-layer thin plate, and relates to the field of intelligent path planning. Firstly, task analysis is conducted on hole sites according to material attributes and drilling parameters, and single-hole generation heat and a temperature attenuation function are calculated through thermophysical model parameterization; and thus, a minimum cooling interval time matrix of the hole site set is obtained. On the basis, the tool moving speed and the drilling time consumption are comprehensively considered, a time sequence diagram fused with the cooling constraint is constructed, and global path searching and optimization are conducted through a space-time A * algorithm. According to the method, a traditional static planning problem which purely pursues the shortest geometric distance is converted into a spatio-temporal dynamic optimization problem which meets a thermal safety threshold value, cooling waiting time and moving travel time are automatically balanced through an algorithm, the problem of material performance degradation caused by local heat accumulation in the prior art is effectively solved, and the service life of the material is prolonged. The drilling quality and efficiency of the multi-layer thin plate are both improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of path intelligent planning, and more specifically, to a drilling path intelligent planning method for multi-layered thin plates and a system thereof. BACKGROUND

[0002] Multi-layered thin plate structures, especially the laminated structures composed of carbon fiber reinforced polymer (CFRP) and metal (such as titanium alloy), are widely used in high-end manufacturing fields such as aerospace due to their excellent mechanical properties, for example, the manufacturing of aircraft wing skins. When a large number of holes are drilled in such large-sized components, the thermal effect in the drilling process is a key problem affecting the processing quality and structural integrity. Drilling is essentially a process of intense heat injection. Due to the difference in material properties and heat conduction limitations, the cutting heat generated by single-hole processing cannot be dissipated to the surrounding medium in time, and a heat-affected zone is easily formed around the hole wall. If adjacent holes are drilled continuously in a short period of time, the local heat cannot be effectively dissipated and the superposition effect occurs, causing the local temperature of the workpiece to rise rapidly and exceed the critical damage temperature of the material (such as the glass transition temperature of the composite material resin matrix), and then causing irreversible material performance degradation problems such as ablation, carbonization, and delamination of the matrix, which seriously threatens the connection strength.

[0003] However, existing drilling path planning schemes usually simplify the problem as a static two-dimensional traveling salesman problem (TSP), and the core algorithm (such as ant colony algorithm, etc.) is mainly devoted to minimizing the total Euclidean distance of tool idle travel. This strategy, which takes the shortest geometric distance as the only goal, tends to prioritize completing all drilling tasks in locally dense areas, forming a cluster-like processing sequence. Although this path planning theoretically shortens the moving distance, it completely ignores the physical heat effect in the processing process and the cooling needs in the time dimension, leading to rapid accumulation of heat in the local area, which exactly induces the above-mentioned thermal damage problem. In order to solve this contradiction, the engineering site currently adopts empirical strategies such as jump drilling or zoned cooling, i.e., artificially forcing the tool to reciprocate between large areas to wait for local cooling. However, this static preset rule lacks adaptability, and when faced with irregular hole distribution, it is difficult to accurately control the heat threshold of each area, and it also leads to a waste of a large amount of time in the invalid idle travel of the tool, significantly reducing the processing efficiency. In the prior art, there is a lack of a mathematical model that can uniformly quantify the analysis of the pair of contradictions of thermal safety cooling and processing efficiency, and it is unable to answer the question of how to plan the path and timing to achieve the shortest total processing time (including movement and necessary cooling waiting) under the premise of ensuring that each hole site meets the thermal-physical cooling constraints.

[0004] Therefore, there is an urgent need for a drilling path intelligent planning method for multi-layered thin plates to maximize production efficiency while ensuring material thermal safety. SUMMARY

[0005] To solve the problems in the prior art, according to an aspect of the present application, a multi-layer sheet drilling path intelligent planning method is provided, which comprises:

[0006] obtaining a hole position set, the hole position set being a set containing three-dimensional coordinates of all holes to be drilled;

[0007] based on material properties and drilling parameters, task analysis and thermal physical model parameterization are performed on the hole position set to obtain single-hole generated heat and temperature decay function;

[0008] based on the ambient reference temperature and the temperature decay function, a minimum cooling interval time matrix of the hole position set is calculated;

[0009] based on the minimum cooling interval time matrix, the time required for drilling a single hole, the tool idle stroke movement speed and the hole position set, a timing diagram is constructed;

[0010] the starting hole in the hole position set is searched and optimized in the timing diagram based on the space-time A* algorithm to obtain an optimal path sequence;

[0011] based on the optimal path sequence, the hole position set and the drilling parameters, numerical control code is generated.

[0012] According to another aspect of the present application, a multi-layer sheet drilling path intelligent planning system is provided, which comprises:

[0013] a hole input module for obtaining a hole position set, the hole position set being a set containing three-dimensional coordinates of all holes to be drilled;

[0014] a thermal physical modeling and parameterization module for performing task analysis and thermal physical model parameterization on the hole position set based on material properties and drilling parameters to obtain single-hole generated heat and temperature decay function;

[0015] a cooling interval time calculation module for calculating a minimum cooling interval time matrix of the hole position set based on the ambient reference temperature and the temperature decay function;

[0016] a timing diagram construction module for constructing a timing diagram based on the minimum cooling interval time matrix, the time required for drilling a single hole, the tool idle stroke movement speed and the hole position set;

[0017] a path search and optimization module for searching and optimizing the starting hole in the hole position set in the timing diagram based on the space-time A* algorithm to obtain an optimal path sequence;

[0018] a numerical control code generation module for generating numerical control code based on the optimal path sequence, the hole position set and the drilling parameters.

[0019] Compared with the prior art, the drilling path intelligent planning method for multi-layer sheet metal and the system thereof provided by the application introduce the thermal-physical effect of the drilling process into the path planning model. First, the hole positions are analyzed according to the material properties and the drilling parameters, the heat generated by a single hole and the temperature decay function are calculated by parameterizing the thermal-physical model, and thus the minimum cooling interval time matrix of the hole position set is obtained. On this basis, the tool moving speed and the drilling time consumption are comprehensively considered, the time sequence diagram integrated with the cooling constraint is constructed, and the space-time A* algorithm is used for global path search and optimization. The method converts the traditional static planning problem of simply pursuing the shortest geometric distance into the space-time dynamic optimization problem of meeting the thermal safety threshold, automatically balances the cooling waiting time and the moving travel time through the algorithm, effectively solves the material performance degradation problem caused by local heat accumulation in the prior art, avoids the efficiency loss caused by the artificial partition jump strategy, and realizes the dual improvement of the drilling quality and efficiency of the multi-layer sheet metal. BRIEF DESCRIPTION OF DRAWINGS

[0020] The above and other objects, features and advantages of the present application will become more apparent from the following detailed description of embodiments of the present application taken in conjunction with the accompanying drawings.

[0021] Figure 1 A flowchart of the drilling path intelligent planning method for multi-layer sheet metal according to an embodiment of the present application.

[0022] Figure 2 A data flow schematic diagram of the drilling path intelligent planning method for multi-layer sheet metal according to an embodiment of the present application.

[0023] Figure 3 A flowchart of step S3 in the drilling path intelligent planning method for multi-layer sheet metal according to an embodiment of the present application.

[0024] Figure 4 A flowchart of step S4 in the drilling path intelligent planning method for multi-layer sheet metal according to an embodiment of the present application.

[0025] Figure 5 A block diagram of the drilling path intelligent planning system for multi-layer sheet metal according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. It should be understood that the accompanying drawings and embodiments of the present disclosure are only for exemplary purposes, and are not intended to limit the protection scope of the present disclosure.

[0027] To solve the technical problems in the background art, the present application provides a drilling path intelligent planning method for multi-layer sheet metal. Figure 1A flow chart of the drilling path intelligent planning method for multi-layer sheet according to the embodiment of the present application. Figure 2 A data flow schematic diagram of the drilling path intelligent planning method for multi-layer sheet according to the embodiment of the present application. As shown in Figure 1 and Figure 2 The drilling path intelligent planning method for multi-layer sheet according to the embodiment of the present application comprises: S1, obtaining a hole position set, the hole position set being a set containing three-dimensional coordinates of all holes to be drilled; S2, based on material properties and drilling parameters, performing task analysis and thermal physical model parameterization on the hole position set to obtain single-hole generated heat and temperature decay function; S3, based on the ambient reference temperature and the temperature decay function, calculating a minimum cooling interval time matrix of the hole position set; S4, based on the minimum cooling interval time matrix, the time required for drilling a single hole, the tool idle travel speed and the hole position set, constructing a timing diagram; S5, performing path search and optimization based on the space-time A* algorithm on the starting hole in the hole position set in the timing diagram to obtain an optimal path sequence; S6, based on the optimal path sequence, the hole position set and the drilling parameters, generating numerical control code.

[0028] In step S1, a hole position set is obtained, the hole position set being a set containing three-dimensional coordinates of all holes to be drilled. It should be understood that in the manufacturing process of large aerospace composite components, especially for the multi-layer sheet structure composed of carbon fiber composite material and titanium alloy such as wing skin, the workpiece surface often presents complex free-form surface characteristics rather than simple two-dimensional plane. This complex geometric shape determines that the real motion trajectory of the tool in space cannot be accurately described by relying on two-dimensional drawing coordinates, and the physical distance between holes cannot be truly reflected. Since the subsequent thermal physical model needs to accurately calculate the Euclidean distance between any two holes to evaluate the heat transfer and decay effect, and the path planning algorithm needs to calculate the idle travel time of the tool according to the real spatial distance, therefore, first, the processing object in the physical world is digitized, and an accurate three-dimensional space model is constructed to provide a unique geometric data reference for subsequent calculation of heat affected zone superposition degree and planning of optimal heat-avoiding path.

[0029] In one exemplary operation, the specific procedure of step S1 is as follows: achieved by parsing the digital design model of the part to be processed. The hole position set is defined as a structured data container, whose core architecture is an N x 3 numerical matrix or multidimensional array, where N represents the total number of holes to be drilled, and each row of data corresponds to an independent hole object, containing the X-axis, Y-axis and Z-axis coordinate values of the hole in the workpiece coordinate system. In the specific implementation process, first, the three-dimensional CAD model file of the multi-layer sheet component is read through the data interface of the computer-aided manufacturing software, which is in STEP or IGES format and contains the complete topological structure and geometric features of the workpiece. The algorithm program uses feature recognition technology to automatically traverse all geometric elements on the model surface, recognizes the round hole features or point features representing the drilling position, and extracts the coordinate values of the geometric centers of these features. Considering the difference between the machine coordinate system and the design coordinate system in actual processing, the original coordinate data needs to be mapped through a homogeneous transformation matrix to be unified into the absolute coordinate system of the machine tool worktable, ensuring that the path planning result can be directly used to generate numerical control instructions.

[0030] After the above extraction and conversion processing, the obtained data is encapsulated as a hole position set. In order to facilitate understanding, taking a specific aircraft wing skin processing task as an example, the workpiece is a laminated plate with double curvature characteristics, and the surface is distributed with 100 holes to be drilled. The algorithm first identifies the spatial positions of all holes and stores them in set P. Set P is in the form of where each element strictly corresponds to a three-dimensional coordinate vector . For example, the coordinates of the first hole in the set may be (150.5, 200.0, 45.2) in millimeters, representing that the hole is located at X-axis 150.5 mm, Y-axis 200.0 mm, and height Z-axis 45.2 mm; and the coordinates of the second hole may be (156.5, 203.0, 46.8). Note that the change in Z-axis coordinates (from 45.2 to 46.8) accurately reflects the curvature characteristics of the skin surface. If only two-dimensional coordinates are used, ignoring the Z-axis height difference, the calculated distance between holes will be smaller, and the heat propagation attenuation degree will be incorrectly evaluated, resulting in distorted calculation of the safety temperature threshold.

[0031] In addition, after the hole position set is constructed, it will also go through a data cleaning process to remove duplicate points and outliers, and be numbered according to the initial index order to form the final data set to be processed. This set not only contains position information, but also implicitly contains the total amount and initial distribution state of the processing task.

[0032] In step S2, based on the material properties and drilling parameters, the task analysis and thermal-physical model parameterization are performed on the hole position set to obtain the single-hole generated heat and temperature decay function. Accordingly, in the drilling process of multi-layer sheet structure, especially for carbon fiber composite materials and metal laminates with anisotropy and significant thermal-physical differences, the heat generated by mechanical drilling is the root cause of hole wall damage. Since the previous step has obtained the accurate three-dimensional geometric coordinates of all the holes to be processed, the spatial reference of the machining is established, but only geometric information cannot evaluate the risk of thermal damage. The occurrence of thermal damage depends on the game between the accumulation and dissipation speed of local heat, which is directly controlled by the thermal conductivity of the material and the energy input level of the cutting process. Without establishing a quantitative mapping relationship from process parameters to physical field changes, the subsequent path planning will lack physical basis to determine when the next hole can be safely drilled. Therefore, the purpose of this embodiment is to establish a thermal-physical quantitative model, convert the abstract drilling task into specific energy input values, and analyze the mathematical function describing the evolution of the temperature field with time and space. This process converts discrete process parameters into continuous physical field descriptions, thereby obtaining the single-hole generated heat and temperature decay function, which provides the core calculation kernel and boundary conditions for subsequent calculation of safe cooling intervals.

[0033] In one example operation, step S2, based on the material properties and drilling parameters, the task analysis and thermal-physical model parameterization are performed on the hole position set to obtain the single-hole generated heat and temperature decay function, including: S21, based on the material properties, drilling parameters and hole position set, the single-hole generated heat is determined by the following formula:

[0034]

[0035]

[0036]

[0037]

[0038] wherein, is the cutting torque, is the specific cutting force coefficient, is the tool diameter, is the feed per revolution, is the spindle speed, is the cutting power, is the single-hole drilling time, is the drilling depth, is the heat distribution coefficient, is the single-hole generated heat; S22, based on the material properties and the single-hole generated heat, a temperature decay function is constructed.

[0039] In the above exemplary operation, the specific process of step S2 is as follows: First, read and parse the preset drilling parameter set and material property set. The drilling parameter set is the machine tool instruction parameter determined according to the process specification, specifically including the spindle speed. (Unit: r / min) Feed per revolution (Unit: mm / r) Tool diameter (Unit: mm) and heat distribution coefficient Among them, the heat distribution coefficient This is a dimensionless empirical value used to describe the proportion of the total heat generated during cutting that is transferred into the workpiece rather than carried away by chips or transferred to the tool. For CFRP / Ti laminated materials with poor thermal conductivity, this value is calibrated experimentally. The material property set contains the equivalent physical parameters of the multilayer thin-plate structure, including specific cutting force coefficients. (Unit: N / mm²), Equivalent thermal conductivity (Unit: W / (m·K)), specific heat capacity (Unit: J / (kg·K)) and density (Unit: kg / m³). These parameters form the basis of the physical constants for analytical calculations.

[0040] After obtaining the above basic data, the first stage of single-hole heat generation is carried out. The quantitative calculation implementation step S21 follows the law of conservation of energy, converting mechanical cutting work into heat energy. Specifically, taking a typical aerospace laminate drilling scenario as an example, the set drilling parameters are: tool diameter... =6.35mm, spindle speed =3000 r / min, feed rate per revolution =0.08mm / r, drilling depth =10mm corresponds to the total thickness of the multilayer board, heat distribution coefficient =0.6, meaning 60% of the heat is transferred to the workpiece. Regarding material properties, the weighted average cutting force coefficient of the laminated structure is used. =3000 N / mm². The first step in the calculation is to determine the cutting torque. This refers to the torque required for the cutting tool to overcome resistance when removing material. According to the formula... Calculations were performed. This formula shows that the cutting torque is proportional to the square of the tool diameter, reflecting the significant impact of increasing the hole diameter on cutting resistance. Substituting the values, we get: = =1209.67 N·mm. Convert this to SI units, i.e. =1.21 N·m. The second step is to convert the cutting torque into cutting power. , i.e. the energy output of the tool per unit time. According to the formula , the calculation is carried out. Here , the rotational speed is converted from revolutions per minute to revolutions per second, , the revolutions are converted to radians. Substituting the numerical values, we get: =1.21 x 3000 x 6.283 / 60 = 380.1 W. This indicates that the tool continuously outputs mechanical energy at a power of about 380 watts during drilling. The third step is to calculate the single-hole drilling time , i.e. the duration of continuous heat injection. According to the formula , the denominator represents the axial feed speed of the tool (mm / s). Substituting the numerical values, we get: feed speed = 0.08 x 3000 / 60 = 4 mm / s. =10 / 4 = 2.5 s, i.e. it takes 2.5 seconds to complete a hole drilling. Finally, the single-hole generated heat is calculated based on the above results. This refers to the total amount of heat energy actually transmitted to the workpiece during a complete drilling operation. According to the formula , the calculation is carried out. Substituting the numerical values, we get: =380.1 x 2.5 x 0.6 = 570.15 J, which will be solidified as a thermal intensity constant in the subsequent thermal physical model, representing the initial heat energy level carried by each hole at the moment of processing completion.

[0041] After completing the heat source quantification, the second stage of constructing the temperature decay function is implemented in step S22. Then S22 is entered. First, the medium thermal diffusion property is calculated, i.e. the equivalent thermal diffusivity is solved. This parameter measures the ability of the material to tend to uniform temperature, directly determining the speed of heat dissipation. If the material properties are obtained as: equivalent thermal conductivity =4.0 W / (m·K), density =4500 kg / m³, specific heat capacity =500 J / (kg·K). According to the formula , the calculation is carried out. Substituting the numerical values, we get: =4.0 / (4500 x 500) = 1.78 x 10^{-6} m² / s. The smaller this value, the easier heat accumulates locally and the longer the cooling time; otherwise, the faster the heat dissipation. Finally, based on the single-hole generated heat and the equivalent thermal diffusivity obtained above, the instantaneous point heat source model function, i.e. the temperature decay function , is constructed. Since the single-hole drilling time The time of 2.5 seconds is much shorter than the cooling time required for the heat to dissipate completely (which can be tens of seconds to several minutes). Therefore, in macroscopic heat conduction analysis, the drilling process can be approximated as an instantaneous release of heat in an infinitely large medium. The point heat source. Based on the analytical solution of the three-dimensional heat conduction theory, the formula is constructed as follows:

[0042]

[0043] In this function model, Indicates the distance from the borehole center meters away, time elapsed Temperature rise after seconds It is a natural exponential function. The first half of the formula... The decay law of the peak temperature rise over time is described. As the value increases, the denominator increases, and the peak temperature rise decreases rapidly, reflecting the process of heat diffusion to the surrounding areas leading to a decrease in the core temperature. The latter part of the formula... It is a Gaussian distribution term that describes the spatial distribution of the temperature field. Being in the negative term of the exponent indicates that as the distance... With the increase of , the temperature rise decreases exponentially; while the denominator This indicates that over time, the extent of the heat-affected zone (i.e., the width of the Gaussian wave packet) gradually expands, and the temperature distribution tends to level off. The specific values ​​obtained from the aforementioned calculations... Substituting these values ​​into the formula yields a specific functional expression containing only the variables r and t. This temperature decay function is encapsulated as a standard software object or function handle. This temperature decay function forms the thermophysical core of the entire intelligent planning method, transforming discrete material and process parameters into a continuously computable spatiotemporal temperature field model, providing a precise mathematical tool for calculating the minimum cooling interval matrix.

[0044] In step S3, the minimum cooling interval time matrix of the hole location set is calculated based on the ambient reference temperature and temperature decay function. It is understandable that in automated drilling operations on multi-layer thin plate structures, although the preceding steps have completed the accurate extraction of hole spatial coordinates and the parameterized modeling of the thermophysical process of single-hole drilling, establishing the heat source intensity and the heat diffusion law under ideal conditions, this information only remains at the level of static physical property description. The actual machining process is a dynamic spatiotemporal evolution process; the drilling of each hole will leave a residual temperature field inside the workpiece that decays over time. When subsequent holes are within the influence radius of this residual temperature field, the newly generated cutting heat will physically superimpose with the background residual heat. If this superimposed local instantaneous temperature exceeds the tolerance limit of the material (especially the resin matrix in carbon fiber composites), it will directly lead to glass transition, delamination, or microcrack propagation in the material. Therefore, this application transforms the continuously changing physical field constraints into hard time constraints between discrete processing tasks. That is, through quantitative numerical calculation, a fully connected time constraint network is established to accurately answer the core question of how long to wait before safely processing the next specific hole after completing the current hole, thereby constructing the minimum cooling interval time matrix to guide the path planning algorithm for heat avoidance optimization.

[0045] In one exemplary operation Figure 3 This is a flowchart of step S3 in the intelligent drilling path planning method for multilayer thin plates according to an embodiment of this application. Figure 3 As shown, step S3, based on the ambient reference temperature and the temperature decay function, calculates the minimum cooling interval time matrix of the hole location set, including: S31, calculating the Euclidean distance between any two holes in the hole location set to obtain the hole distance matrix; S32, determining the safe temperature rise threshold based on the ambient reference temperature and the critical damage temperature; S33, solving for the minimum cooling time between holes in the hole distance matrix based on the safe temperature rise threshold and the temperature decay function to obtain the minimum cooling interval time matrix.

[0046] In the above exemplary operation, the specific process of step S3 is as follows: First stage: Constructing the distance matrix between holes (implementing step S31). The purpose of this stage is to transform the physical geometric features of the workpiece into distance field data required for heat conduction analysis. In the preceding step S1, a set of hole positions containing N holes to be drilled has been obtained. Each element All contain precise three-dimensional coordinates To evaluate the thermal interaction between any two apertures, the program first initializes a real-valued zero matrix of dimension N×N in memory; in this application, N is 100, denoted as . The algorithm then initiates a double loop traversal logic to calculate any two hole pairs in the hole location set. The spatial distance between them. It should be noted that, due to the complex hyperbolic shape of multi-layered thin plates in aerospace applications (such as wing skin), a simple two-dimensional projected distance cannot reflect the actual path length of heat conduction within the material; therefore, a three-dimensional Euclidean distance formula is used for calculation. For each pair of indices... ,in ,extract coordinates and coordinates Substitute into the following formula: Taking the example data in step S1, such as the hole position... The coordinates are (150.5, 200.0, 45.2) mm, hole position. The coordinates are (156.5, 203.0, 46.8) mm. Therefore, the difference between the two points along the X-axis is 6.0 mm, along the Y-axis is 3.0 mm, and along the Z-axis is 1.6 mm. The calculation process is as follows: ≈6.896 mm. To maintain consistency in physical units for subsequent substitution into the standard heat conduction formula, this distance value was then converted to the standard SI unit, meter (m), i.e. =0.006896m. (Calculated value) The corresponding positions to be filled in the matrix By utilizing the symmetry of spatial distance (i.e., the distance from A to B is equal to the distance from B to A), the program synchronously assigns values. For diagonal elements where i=j, the physical distance is 0, but in the heat conduction model, this is marked as infinity or specially treated to avoid self-reference errors; in this embodiment, it is retained as 0. After a complete traversal calculation, the resulting inter-hole distance matrix is... It fully maps the spatial topological relationships between all holes to be processed.

[0047] Phase Two: Determining the Safe Temperature Rise Threshold (Step S32). To ensure that the drilling process does not damage material properties, a clear temperature threshold needs to be set. The program first reads two key parameters through the human-machine interface or process database: ambient reference temperature. and the critical damage temperature of the material Ambient reference temperature This refers to the ambient temperature of the workshop or the initial equilibrium temperature of the workpiece before processing. For example, in a standard constant-temperature machining workshop, this value is set at 20°C, or 293.15K. Critical damage temperature. This depends on the material property with the weakest heat resistance in the multilayer sheet. For carbon fiber reinforced polymer (CFRP) composites, this temperature is determined by the glass transition temperature of the resin matrix. Decision. To ensure absolute safety, the project will... Based on this, a safety margin is set. For example, CFRP. The initial critical damage temperature was set at 180℃, but considering the risk of heat accumulation during continuous processing, the actual critical damage temperature was set accordingly. It could be 150℃. Based on these two parameters, the program calculates the safe temperature rise threshold. This threshold represents the maximum temperature increment that the workpiece is allowed to accept at its current position due to an external heat source (i.e., other previously machined holes) without causing the total temperature to exceed the limit. In an exemplary operation, step S32, determining the safe temperature rise threshold based on the ambient reference temperature and the critical damage temperature, includes: determining the safe temperature rise threshold using the following formula:

[0048]

[0049] in, The critical damage temperature The ambient reference temperature This represents the safe temperature rise threshold. Substitute the values ​​from the example above: =150-20=130℃, or 130K, because the temperature difference is numerically equal on both the Celsius and Kelvin scales. This value has a clear physical meaning: if the residual temperature rise caused by the heat generated during drilling at the previous hole position still exceeds 130K when conducted to the current hole position, it means that the actual temperature of the current hole position has exceeded 20+130=150℃. If drilling is forced at this point, the newly generated cutting heat superimposed on the already critical high temperature will inevitably lead to material ablation. Therefore, This constitutes the boundary condition for solving the minimum cooling time.

[0050] Phase 3: Solving the minimum cooling interval time matrix (Step S33). This is the core calculation step in this embodiment, aiming to map the spatial distance matrix into a time constraint matrix. The program first initializes an N×N minimum cooling interval time matrix with the same dimensions as the distance matrix. The algorithm initializes all elements to 0. Then, it iterates through all ordered hole pairs. ,in For each pair of apertures, the program first retrieves the physical distance between them from the distance matrix. As mentioned above, 0.006896m. Simultaneously, the temperature decay function generated in step S2 is invoked. This function describes the heat generated in a single pore. Under the influence of the heat source Location, Time The subsequent temperature rise. The specific form of the function is: ,in For heat generated by a single pore, such as 570.15 J, Thermal diffusivity, such as 1.78 × 10^{-6} m² / s and The volumetric heat capacity is a constant determined in step S2. For a given distance... Temperature rise Only with time Changes. To find the minimum cooldown time, it is necessary to solve for the time... transcendental equations: Because the equation contains power function terms and exponential terms Since an analytical solution cannot be directly obtained, this embodiment uses a numerical analysis method to solve the problem. The specific implementation logic is as follows: First, peak temperature is predicted. According to the heat conduction theory, the distance from the heat source... The temperature at that location does not decrease monotonically, but rather first rises and then falls (due to the heat wave conduction effect). The moment the temperature reaches its peak... It can be obtained from the fact that the derivative is 0, and the formula is: Substitute the numerical values ​​into the calculation: This means that after drilling the hole... After that, the heat wave will be conducted to approximately 4.45 seconds later. The temperature reaches its maximum. The program then calculates... Peak temperature rise at time There are two scenarios at this point: Scenario 1: If the calculated peak temperature rise... This indicates that even at the moment of most intense thermal impact, the temperature increase at this location did not exceed the safe threshold. Physically, this means that the two holes are far enough apart, or the material dissipates heat quickly enough, so the heat from the first hole does not pose a threat to the second. In this case, there is no need to wait; proceed directly... =0. Case 2: If This indicates that the heat wave peak has exceeded the safety threshold, and we need to wait for the temperature to drop. At this point, the equation... There is a unique solution within the interval. The algorithm uses either the binary search method or Newton's iteration method within the interval. , This can be set to a relatively large empirical value, such as finding the root within 1000 seconds. In the example above, considering the strong anisotropic thermal conductivity of the CFRP / Ti laminate structure and the thermal reflection effect at the interlayer interfaces, the heat decay rate in the plane is significantly lower than that of an ideal isotropic medium, resulting in a local actual temperature rise that is approximately 2 to 3 times the theoretically calculated value. Therefore, a dimensionless empirical correction factor is introduced during the calculation. The temperature data were obtained by comparing the measured temperature data of thermocouples at different locations with the theoretical model values ​​through pre-conducted standard sample drilling experiments, and then using the least squares method for regression analysis calibration. For example, taking... =2.5 is directly multiplied by the theoretical calculation result, that is If the corrected predicted peak temperature rise is approximately 145K, exceeding the threshold of 130K, the algorithm initiates an iterative solution, continuously approximating the time point at which the function value equals 130K. After multiple iterations and convergence, the solution yields t≈6.5s. The physical meaning of this value is: after drilling... After that, at least 6.5 seconds must pass before the hole... Only when the residual temperature rise drops from its peak and falls below 130K will the next drilling operation be allowed. The program assigns the calculated t=6.5 to the matrix element. It is important to note that, due to the isotropic assumption of heat conduction, Approximately equal to However, when considering the processing sequence, this matrix explicitly represents the constraints from i to j. By traversing all hole pairs through the above process, the minimum cooling interval time matrix is ​​finally generated. It is a fully connected digital constraint network. Non-zero elements in the matrix (such as 6.5 seconds, 8.10 seconds, etc.) precisely mark the forced cooling time required for hole pairs that are too close together and have the risk of thermal overlap, while zero elements mark the free processing combinations outside the thermal safety distance.

[0051] Specifically, the aforementioned thermal safety assessments often focus only on the static environment before drilling, assuming that as long as the initial local temperature of the workpiece (including ambient temperature and residual temperature conducted from surrounding machined holes) plus the safe temperature rise threshold does not exceed the material's critical damage temperature before drilling begins, the operation is safe. However, this logic ignores the fact that drilling itself is a violent heat-generating process. The true peak temperature does not occur before drilling, but rather during or immediately after drilling. If no heat reserve is made for the upcoming drilling action, then when the ambient temperature plus residual temperature is already close to the material's limit, the total temperature of the workpiece will inevitably exceed the critical value once the instantaneous high temperature generated by drilling itself is added, leading to material ablation. Therefore, the purpose of implementing this optimization strategy is to eliminate the systematic underestimation of thermal safety that may exist at the algorithm level, by redefining the safe temperature rise threshold by reserving a budget for the self-temperature rise of each target hole. This means that the new safe temperature rise threshold (i.e., the dynamic safe residual temperature rise threshold) is no longer the entire available temperature rise space, but rather the portion remaining after deducting the expected peak temperature rise generated by drilling itself from the total allowable temperature rise space. It represents the maximum amount of residual external heat from other holes that the current hole position can tolerate, provided that the final superposition temperature does not exceed the limit.

[0052] Based on this, in a preferred exemplary operation, step S3, calculating the minimum cooling interval time matrix of the hole location set based on the ambient reference temperature and the temperature decay function, includes: S3-1, calculating the Euclidean distance between any two holes in the hole location set to obtain the hole distance matrix; S3-2, calculating the peak temperature rise based on the temperature decay function; S3-3, calculating the safe temperature rise threshold based on the ambient reference temperature, the critical damage temperature, and the peak temperature rise; S3-4, calculating the minimum waiting time equation on the hole distance matrix based on the safe temperature rise threshold and the temperature decay function to obtain the minimum cooling waiting time matrix as the minimum cooling interval time matrix.

[0053] Specifically, step S3-1 is executed first. This step converts the discretely distributed holes on the workpiece into geometric topological data required for heat conduction analysis. Since the attenuation of heat in a solid material is exponentially related to the square of the propagation distance, accurate distance information is fundamental for all subsequent thermal calculations. The specific operation is consistent with the aforementioned basic embodiment: traversing each pair of holes in the hole location set and calculating their Euclidean distance using three-dimensional coordinates. For example, for hole P1 with coordinates (150.5, 200.0, 45.2) mm and hole P2 with coordinates (156.5, 203.0, 46.8) mm, the straight-line distance between them is calculated to be approximately 6.9 mm (0.0069 m). All calculated distance values ​​are stored in the hole distance matrix as input variables for subsequent calculations of the temperature attenuation function. .

[0054] The next step, S3-2, quantifies the temperature rise that drilling a single hole will generate, providing a quantitative basis for thermal budget deduction. Without this calculation, it's impossible to accurately assess the required safety margin. Specifically, the temperature decay function constructed in step S2 is used to estimate the maximum temperature rise that can be achieved at the hole wall at the end of single-hole drilling. The calculation formula is as follows:

[0055]

[0056] In the formula, This represents the peak temperature rise of a single orifice, expressed in Kelvin (K) or Celsius (°C). The diameter of the cutting tool is in meters (m). The time required for drilling a single hole is expressed in seconds (s). This is the temperature decay function. The reason for choosing this is... (i.e., at the hole wall) rather than the hole center, because the mathematical model is in The thermal properties will diverge at the surface, and the hole wall is the interface where material thermal damage first occurs, which aligns with engineering practice. Taking a specific parameter setting as an example: Let the tool diameter... =0.00635 meters, single-hole drilling time Seconds. Substitute these values ​​and the thermophysical constants determined in the preceding steps into the temperature decay function for calculation. It should be noted that for anisotropic composite laminate structures, the actual thermal conductivity is more complex than the ideal model, and thermal reflection effects occur at the interlayer interfaces. Therefore, in practical engineering calculations, the results of the theoretical model are usually corrected. For example, after calculation and correction, the peak temperature rise of a single pore is obtained. It is approximately 60K, or 60℃. This value indicates that even without external interference, drilling a hole will cause the local temperature to rise by 60℃ instantaneously.

[0057] Next, step S3-3 is executed. This step is the core of this preferred strategy, which tightens the originally lenient safety standards and defines a dynamic safety residual temperature rise threshold to ensure that the total temperature does not exceed the limit. The specific calculation formula is as follows: In the formula, This is the corrected safe temperature rise threshold, i.e., the maximum allowable external residual temperature rise; The critical damage temperature of the material, such as the glass transition temperature of CFRP, is set to 150℃. The ambient reference temperature is set to 20℃. The peak temperature rise of a single orifice (60℃) calculated in step S3-2. Substitute the example value into the formula: =150-20-60=70℃, or 70K. Compared to the traditional calculation method (only 150-20=130℃), the new threshold is significantly reduced from 130℃ to 70℃. This has a clear physical meaning: before drilling the next hole, it must be ensured that the existing temperature at that location (ambient + residual heat) does not exceed 20+70=90℃. Only in this way, after adding the 60℃ temperature rise generated by the new drilling, the total temperature of 90+60=150℃ just barely stays above the critical red line, preventing ablation.

[0058] Finally, step S3-4 is executed. This step is implemented to translate the stricter temperature threshold into specific time constraints, guiding subsequent path planning. Because... The smaller size requires a cooler surface to drill through, naturally necessitating a longer cooling time, which physically compels safety improvements. This is achieved by solving the following transcendental equation: In the formula, These are elements in the hole-to-hole distance matrix; The minimum cooling wait time to be solved; The threshold (70K) calculated in step S3-3. Continuing with the example above, for two holes only 6.9 mm apart, the original threshold of 130K would have allowed only 6.5 seconds to reduce the residual temperature to a safe level. However, now that the threshold is reduced to 70K, it means further heat dissipation and a further temperature reduction are required. The calculated value is obtained by numerically iterating through this equation. This could increase to 15 seconds or even longer. This result is stored in the minimum cooldown interval time matrix. This is the calculated... The values ​​in the matrix generally increase, making it difficult to determine the spatial proximity of holes (time of movement). The transfer cost (i.e., waiting time) increases significantly when the hole is relatively small. Thus, subsequent spatiotemporal A* algorithms, when searching for the optimal path, are reluctant to continuously visit neighboring holes due to the high parking waiting cost, and are instead forced to choose holes that are spatially farther away but whose thermal effects have decayed to zero (i.e., smaller). =0) aperture positions. This large-span jump behavior, automatically generated by the algorithm, realizes the transformation from pursuing the shortest geometric distance to optimizing spatiotemporal efficiency, perfectly matching the physical intuition of thermal management without human intervention. In addition, by adjusting With computational models (such as those incorporating safety factors), engineers can flexibly control the conservatism of path planning according to different processing requirements, providing a scientific quantitative means for process optimization.

[0059] In step S4, a timing diagram is constructed based on the minimum cooling interval time matrix, the time required to drill a single hole, the tool's idle travel speed, and the set of hole positions. It should be understood that in the previous steps, by establishing a thermophysical model of the drilling process in multi-layer thin plates, the heat input characteristics of single-hole machining have been successfully analyzed, and the minimum cooling interval time matrix between hole positions based on thermal safety constraints has been calculated. While this matrix precisely quantifies the time that must be waited to prevent thermal damage, it only reflects thermodynamic constraints and does not yet include the kinematic costs of the machining process. In actual CNC machining, the tool needs physical time to move from the current hole position to the next, and this movement time itself is a natural cooling process. If only thermal constraints are considered while ignoring the mechanical movement time, or if the two are viewed separately, the actual operating time that matches the production cycle cannot be obtained. To provide a unified cost evaluation standard that encompasses both mechanical motion and thermophysical constraints for subsequent path optimization algorithms, this application constructs a comprehensive time series graph that couples discrete spatial distances, machine tool motion performance, and thermophysical cooling requirements together. This transforms the simple single-objective problem of minimizing distance or waiting time into a complex spatiotemporal cost optimization problem of minimizing total processing cycle, thus providing a mathematical foundation for the algorithm to find the global optimal solution.

[0060] In one exemplary operationFigure 4 This is a flowchart of step S4 in the intelligent drilling path planning method for multilayer thin plates according to an embodiment of this application. Figure 4 As shown, in an exemplary operation, step S4, based on the minimum cooling interval time matrix, the time required to drill a single hole, the tool idle travel speed, and the hole position set, constructs a timing diagram, including: S41, generating a pure travel time matrix based on the hole distance matrix and the tool idle travel speed; S42, constructing the timing diagram based on the pure travel time matrix, the time required to drill a single hole, and the minimum cooling interval time matrix.

[0061] In the above exemplary operation, the specific process of step S4 is as follows: First stage: Generating a pure movement time matrix. Step S41 converts the distance information in the geometric space into the time cost of the machine tool motion axis. In the preceding step S3, a hole distance matrix that accurately describes the topological relationship between hole positions has been generated. Its elements Represents the hole position and The three-dimensional Euclidean distance between them. However, path planning algorithms (such as the A* algorithm) require time as the unit of measurement for their search in the time domain, thus necessitating the introduction of machine tool dynamics parameters for conversion. First, the key parameter of the tool's idle travel speed is determined, denoted as . This parameter is not the cutting feed rate during drilling, but rather the average traverse speed of the machine tool spindle during rapid positioning between two machining positions. In actual operation of a CNC machining center, this corresponds to the execution speed of the G00 command. This value is a scalar constant, directly derived from the specific machine tool manual or process setting document. For example, for high-speed gantry milling machines or drilling machines used in the aerospace manufacturing field, the rapid traverse speeds of their X / Y / Z axes are set at a high level to improve efficiency. For ease of subsequent calculations and illustrative examples, the tool idle travel speed of the drilling equipment used in this embodiment is set to... =100mm / s, or 6000mm / min, approximately 0.1m / s. This data is obtained by reading the machine tool parameter configuration file of the CNC system or by the process engineer through preset input in the human-machine interface. After determining the speed parameters, the program initializes an N×N pure movement time matrix with the same dimension as the hole distance matrix. The initial values ​​are all zero. Then, the algorithm starts by checking the distance matrix between holes. The full traversal operation. For each element of the matrix. Calculate the pure movement time using the formula for uniform motion. The calculation formula is as follows: In this formula, The Euclidean distance (in meters) calculated in the previous steps. The above-mentioned moving speed (unit: m / s) is used. This calculation assumes that the machine tool moves at an average speed along a straight path between two points, ignoring extremely short acceleration and deceleration transient processes, which is a reasonable approximation in macroscopic path planning. Using the specific data from the previous embodiment, the hole positions are known. and Distance between =0.006896m. This distance is compared with the set speed. Substituting 0.1 m / s into the formula, we get: =0.006896 / 0.1=0.06896s. This calculation result shows that the tool moves from the hole position... After processing is complete, it takes only about 0.07 seconds to physically reach the hole. Above. The program fills the matrix with this value. The corresponding positions [1][2]. Consider another pair of holes that are farther apart, such as the hole positions... and Distance between =0.5m, which is 500mm. Calculate similarly: =0.5 / 0.1=5.0s. This means the tool takes 5 seconds to traverse a long distance. By iterating through all i and j in this way, the final pure movement time matrix is ​​generated. It fully quantifies the minimum purely physical time required for a machine tool to switch between any two points without considering any thermal limitations.

[0062] Phase Two: Constructing the Comprehensive Timing Diagram (Step S42). This phase includes two subdivided logical steps: calculating the effective transfer time and calculating the total time-space cost. In an exemplary operation, step S42, based on the pure movement time matrix, the time required to drill a single hole, and the minimum cooling interval time matrix, constructs the timing diagram, including: S421, calculating the effective transfer time matrix based on the pure movement time matrix and the minimum cooling interval time matrix; S422, adding the elements at each position in the effective transfer time matrix to the time required to drill a single hole to obtain the timing diagram.

[0063] First, execute step S421 to calculate the effective transition time matrix. The program first creates an N×N empty matrix. For any pair of holes... The algorithm simultaneously extracts data from the pure moving-time matrix. Read from and the minimum cooling interval time matrix generated from the preceding step S3. Read from These two time values ​​represent two completely different constraints: It is a capability constraint, indicating the fastest speed the machine tool can run; This is a safety constraint, representing the shortest time required to prevent material ablation. To ensure both reaching the target location and meeting thermal safety requirements, the actual transfer time must satisfy both conditions simultaneously. Therefore, the system uses the maximum value logic for determination. In an exemplary operation, step S421, based on the pure movement time matrix and the minimum cooling interval time matrix, calculates the effective transfer time matrix, including: calculating the effective transfer time matrix using the following formula:

[0064]

[0065] in, For pure travel time, Minimum cooling interval time, To find the maximum value function, For effective transfer time. The physical meaning of this logic: Case A (thermal limitation dominant): with aperture position arrive For example, the previous calculation showed that mechanical movement only requires... =0.06896s. However, the calculation results of step S3 show that due to the close proximity of the two holes, the heat-affected zones overlap significantly, and it is necessary to wait 6.5s before drilling the next hole. Substituting into the formula: =max(0.06896,6.5)=6.5s. This means that although the tool arrives in just over 0.07 seconds, it must remain suspended in the air or in place until the total time reaches 6.5 seconds, allowing the temperature to drop to a safe threshold before it can be lowered. This extra time (6.5-0.06896) is the forced cooling penalty. Case B (Movement Restriction Dominant): Based on Hole Position arrive For example, mechanical movement requires... =5.0s. Due to the considerable distance (0.5m), the heat cannot travel that far, as calculated in step S3 for the cooling waiting time. =0 or a minimum value. Substitute into the formula: =max(5.0,0)=5.0s. This means that within 5 seconds of long-distance movement, the hole position... The heat generated has dissipated naturally or has no effect whatsoever. The tool is safe as soon as it arrives, requiring no further waiting. At this point, the movement itself acts as a cooling process. Through this element-by-element comparison and selection, the program fills the effective transition time matrix. This matrix does not include the time of the drilling operation itself; it only represents the transition cost from the end of the previous hole to the start of the next hole.

[0066] Then, step S422 is executed to combine the effective transfer time with the drilling action time to obtain the final timing diagram weight matrix. Before proceeding, it is necessary to determine the parameter required to drill a single hole, denoted as . This is a scalar value representing the actual cutting time required to drill any one hole. This value is directly derived from the thermophysical parameterization process in step S2, such as calculating the drilling time for a single hole as... =2.5s. This time is a fixed process cost; regardless of the path planning, drilling each hole consumes 2.5 seconds. To construct a complete timing diagram, the algorithm needs to calculate the total process time increment from completing hole i to completing hole j. The program initializes a spacetime cost matrix of size N×N. And iterate through all of them again. Combine and execute the cumulative formula: Specifically, using the example above, the calculation is performed: for closely spaced hole pairs... : =6.5 + 2.5 = 9s. This value of 9s will be used as the weight of the directed edge from node 1 to node 2 in the sequence graph. It tells the path planning algorithm that if it chooses to drill hole 2 immediately after drilling hole 1, it will take a total of 9 seconds, including 0.07s of movement, 6.43s of forced waiting, and 2.5s of drilling. For long-distance hole pairs... : =5.0 + 2.5 = 7.5s. Its weight is 7.5s. Through this specific numerical comparison, a highly valuable phenomenon can be discovered: although the hole... Just in Kong Next to (only 7 mm away), and the hole Drilling a hole half a meter away, but due to thermal safety constraints, is not possible. On the contrary, it is better than drilling a hole nearby. This saves more overall time (7.5s < 9s). After the double loop traversal is complete, the generated spatiotemporal cost matrix... This constitutes a timeline diagram. The complete adjacency weight matrix. In this graph, each hole is a node, and there is a directed edge between any two nodes, with the edge weight... It accurately reflects the time cost while satisfying all physical and technological constraints. This fully connected directed weighted graph contains spatial location information (represented by travel time), thermophysical field information (represented by waiting time), and process execution information (represented by drilling time).

[0067] In step S5, the starting hole positions in the hole position set are searched and optimized using a spatiotemporal A* algorithm on the time sequence graph to obtain the optimal path sequence. Correspondingly, in the time sequence graph, the connection weight between any two hole positions is not merely a measure of distance, but a comprehensive spatiotemporal cost incorporating mechanical movement time, thermophysical cooling waiting time, and actual cutting time. At this point, the problem is transformed into finding a path that traverses all nodes and minimizes the total weight in such a complex directed weighted graph. This is a typical variant of the Traveling Salesman Problem (TSP). Due to the added time-varying heat and cooling constraints (i.e., the edge weights may change with the implicit waiting time based on the access order, but this has been statically fixed in this scheme through pre-calculated maximum values), the solution space is extremely large. Using a simple greedy algorithm easily leads to local optima, resulting in low overall processing efficiency; using brute force enumeration results in an exponential explosion of computational complexity. Therefore, in order to plan a drilling sequence that satisfies all thermal safety constraints and maximizes global efficiency within a reasonable time, this step introduces the spatiotemporal A* algorithm with heuristic search capabilities to intelligently guide the search direction and quickly converge to the optimal solution.

[0068] In an exemplary operation, the specific process of step S5 is as follows: In this embodiment, the process of performing path search and optimization based on the spatiotemporal A* algorithm on the starting hole positions in the hole position set to obtain the optimal path sequence is a graph theory-based heuristic optimization process. This process directly utilizes the spatiotemporal cost matrix output in step S4. As a search map, through a finely defined state space, cost evaluation function, and search strategy, it ultimately outputs an ordered list of hole indexes.

[0069] First, define the input and initialization conditions for the algorithm. The algorithm requires a specified starting hole position, denoted as . The hole position is specified by the process engineer from the hole position set obtained in step S1, based on the workpiece clamping position or the machine tool tool change point. For example, the hole position with index 1 is specified. This serves as the starting point for machining. Unless otherwise specified, the hole position geometrically closest to the machine tool origin is used by default. Furthermore, the algorithm requires a data structure to record the machining progress. Therefore, this embodiment employs bitmasking to efficiently represent which holes have been drilled. If the total number of holes is 4 (for ease of manual calculation demonstration, the actual number can reach hundreds), then the bitmask is a 4-bit binary number. Initially, only the starting bit is set to 1.

[0070] The core of the algorithm lies in the definition of state nodes. Each search state is defined as a triple. . This indicates the hole index that the current tool has just finished machining, such as 1, 2, ..., N. It is an integer whose binary form identifies the set of completed holes. For example, binary 0101 indicates that holes 1 and 3 are completed, and holes 2 and 4 are not completed. This represents the total actual time consumed from the start of the entire task to the current state, determined through iterative accumulation. Its value originates from the spatiotemporal cost matrix constructed in step S4. This corresponds to the A* algorithm. Value. The search process starts from the initial state node. Starting with (10001_2, 0.0), it is placed into a priority queue. This queue is based on the node's overall evaluation value. Sort them from smallest to largest. Defined as: ,in That is , This is the heuristic function value, an estimate of how much time is needed to complete all remaining undrilled holes. To ensure the efficiency of the algorithm and the validity of the solution, the heuristic function... The design is crucial. This embodiment employs the Minimum Spanning Tree (MST) strategy to compute... The specific implementation is as follows: For all unvisited hole positions in the current state (i.e., the holes corresponding to the bits that are 0 in the bitmask), the algorithm extracts their distance relationships in pure geometric space and constructs a minimum spanning tree (MST). The total side length of this MST represents the minimum physical distance required to connect all remaining points. Then, divide that distance by the tool's idle travel speed. This yields the minimum time limit required from a purely movement perspective. The formula is: ,in, This is the number of remaining holes. While this estimate ignores the warm wait time (i.e., it's an optimistic estimate that satisfies the A* algorithm's acceptability condition), it effectively guides the search towards remaining points that are closer and more concentrated. A simplified search step demonstration is performed using data from previous steps: For example, currently in the initial state (1,0001_2,0.0). At this point, there is only one node in the queue; it is removed and expanded. Since there are a total of 4 holes, starting from hole 1, the possible next targets are hole 2, hole 3, or hole 4. The algorithm generates three child nodes: Child node A (to drill hole 2): Refer to the spatiotemporal cost matrix generated in step S4. Read =9s (calculated value above, including cooldown time). Updated status: =2, =0011_2, meaning that 1 and 2 have been drilled. =0.0 + 9 = 9. Calculate. The remaining undrilled holes are 3 and 4. If the distance between holes 3 and 4 is large, and movement takes 5 seconds, then... ≈5.0 + 2 × 2.5 = 10.0. Overall Rating =9 + 10.0 = 19. Child node B, drill hole 50, simplified to hole 3 here: consult the matrix. Read =7.5s (calculated value above; cooling occurs during movement). Updated status: =3, =0101_2, =0.0 + 7.5 = 7.5. Calculate. The remaining undrilled holes are 2 and 4. If they are far apart, it will take 6 seconds to move them. ≈6.0 + 5.0 = 11.0. Overall Rating =7.5 + 11.0 = 18.5. At this point, the priority queue contains node A (f=19) and node B (f=18.5). Comparing their combined evaluation values, node B's value is clearly lower (18.5 < 19.0). Therefore, the algorithm will prioritize expanding node B in this round (i.e., drilling hole 50). This decision-making process vividly demonstrates the intelligence of the spatiotemporal A algorithm. It keenly captures that although drilling hole 3 (node ​​B) is physically farther away, its total time cost is lower than that of the nearby hole 2 (node ​​A) because it does not incur the high cost of heat cooling. The algorithm is not misled by local geometric proximity but makes the correct choice that maximizes global efficiency. As the search continues, the algorithm will continuously remove nodes from the priority queue. The smallest node is expanded to generate a new sub-state, until the removed node satisfies the condition that all holes have been visited. All values ​​are 1. At this point, the path backtracking chain recorded by this node is the optimal path sequence.

[0071] The final output optimal path sequence is an ordered list, such as [1, 50, 2, ...]. This sequence is not only a geometric arrangement but also a precise timetable. It tells the machine tool: first drill hole 1, then use a long-distance movement to drill hole 50 (while allowing hole 1 to cool down), and after hole 50 is drilled, return to drill hole 2 (at this point, hole 1 has completely cooled down and will not cause heat accumulation on hole 2). In this way, the algorithm automatically avoids the forced cooling time calculated in step S3, transforming ineffective waiting in place into effective "path movement," thereby minimizing the total processing time.

[0072] In step S6, CNC code is generated based on the optimal path sequence, the set of hole positions, and drilling parameters. That is, after the complex calculations of the preceding steps, the thermophysical constraints, mechanical motion costs, and spatial topological relationships in the drilling process of multi-layer thin plates have been successfully analyzed and transformed into a mathematically optimal logical sequence. However, this optimal path sequence stored in computer memory is merely an abstract string of numerical indices. The controller of the CNC machine tool cannot directly understand this logical arrangement, nor can it directly perceive the underlying thermal safety avoidance strategy. To transform this theoretically optimal planning result into a practically feasible manufacturing action in the physical world, this application needs to map the abstract hole position indices back to specific three-dimensional coordinates and solidify the drilling process parameters into standardized instruction codes, thereby driving the servo axes and spindle to execute precisely, ensuring that the machine tool moves strictly according to the spatiotemporal rhythm planned by the algorithm, achieving a dual guarantee of efficiency and thermal safety in physical terms. Therefore, this embodiment performs the CNC code generation step to construct an executable file that the machine tool can directly recognize.

[0073] In an exemplary operation, the specific process of step S6 is as follows: The code generator first creates an empty program file and writes an initialization instruction block for the program header information, which includes the absolute coordinate programming instruction (G90), the workpiece coordinate system selection instruction (G54), and the spindle start instruction. Based on the parameters set in step S2, the spindle speed... The speed is 3000 r / min, therefore the command M03 S3000 is generated, and according to the formula... Calculate the feed rate, given the feed per revolution. If the feed rate is 0.08 mm / r, then the feed rate is... =3000×0.08=240mm / min. These global process parameters are temporarily stored for later use.

[0074] Subsequently, the algorithm enters the core sequence traversal and instruction conversion stage. The program pointer sequentially reads each element in the optimal path sequence. Taking the first element index 1 in the sequence as an example, the algorithm uses this index to search in the hole position set in step S1 and extracts the corresponding three-dimensional coordinates (150.5, 200.0, 45.2). Based on this, the first set of motion instructions is generated: first is the rapid positioning instruction G00 X150.5 Y200.0, which drives the tool to move at maximum speed. In step S4, the tool rapidly moves to above the hole at a speed of 100 mm / s. Immediately afterwards, a safety height descent command G00 Z55.2 is generated, where the safety plane is 10 mm above the workpiece surface. Then, a linear interpolation drilling command G01 Z35.2 F240 is generated, where the Z-axis target value of 35.2 is obtained by subtracting the drilling depth h = 10 mm from the current hole height of 45.2, and F240 is the previously calculated feed rate. After drilling is completed, a retraction command G00 Z55.2 is generated, marking the end of the first hole machining cycle.

[0075] Next, the algorithm reads the second element index 50 from the sequence. This jump is precisely the ingenious manifestation of the spatiotemporal A* algorithm of this invention: to avoid heat accumulation around hole 1, the algorithm does not choose the nearby hole 2, but instead chooses the distant hole 50. The code generator is unaware of the thermophysical reasons behind this decision; it simply faithfully performs the mapping: extracting the coordinates of index 50, such as... The command G00 X650.5 Y200.0 is generated. During this long-distance movement, physical time naturally elapses by approximately 5 seconds, or 500mm / 100mm / s. This time during which the machine tool executes the G00 command precisely covers the heat dissipation cooling time required for hole 1 calculated in step S3. Subsequently, the same drilling cycle command G01Z... and retraction command are generated for hole 50.

[0076] Next, the algorithm reads the third element index 2 in the sequence. At this point, the tool will return from the position of hole 50 to hole 2 (coordinates 156.5, 203.0) near hole 1. The instruction G00 X156.5 Y203.0 is generated. When the machine executes this line of code and reaches above hole 2, because sufficient time has been consumed in the previous drilling of hole 50, the heat-affected zone left by hole 1 has cooled below a safe threshold. Therefore, the subsequent drilling instruction G01 can be safely executed without causing material ablation. While generating each instruction block, the program can also selectively use the cumulative time calculated in step S4. Embed as a comment at the end of the code line, for example (Est.Time:9s), so that field engineers can check the processing cycle.

[0077] This process is repeated until the last hole in the optimal path sequence is processed. Finally, the code generator writes the program end instructions M05 (spindle stop) and M30 (program end and reset). The generated complete CNC code file not only contains precise geometric trajectories, but also implicitly embeds complex thermal cooling time windows into the machine tool's physical movements through a specific access sequence. This enables high-quality continuous drilling of multi-layer thin plates using only the path strategy, without the need for any external auxiliary cooling equipment.

[0078] In summary, the intelligent drilling path planning method for multi-layer thin plates based on the embodiments of this application is explained. It incorporates the thermophysical effects of the drilling process into the path planning model. First, the hole positions are analyzed based on material properties and drilling parameters. The heat generated by a single hole and the temperature decay function are calculated parametrically using the thermophysical model, thereby obtaining the minimum cooling interval time matrix for the set of hole positions. Based on this, considering both tool movement speed and drilling time, a time series diagram incorporating cooling constraints is constructed, and a spatiotemporal A* algorithm is used for global path search and optimization. This method transforms the traditional static planning problem of simply pursuing the shortest geometric distance into a spatiotemporal dynamic optimization problem that satisfies thermal safety thresholds. By automatically balancing cooling waiting time and movement travel time through the algorithm, it effectively solves the material performance degradation problem caused by local heat accumulation in existing technologies, while avoiding the efficiency loss caused by manual partitioning and jumping strategies, achieving a dual improvement in drilling quality and efficiency for multi-layer thin plates.

[0079] Figure 5 This is a block diagram of an intelligent drilling path planning system for multilayer thin plates according to an embodiment of this application. Figure 5 As shown, the intelligent drilling path planning system 100 for multi-layer thin plates according to an embodiment of this application includes: a hole position input module 110, used to acquire a set of hole position locations, wherein the set of hole position locations is a set containing the three-dimensional coordinates of all holes to be drilled; a thermophysical modeling and parameterization module 120, used to perform task analysis and thermophysical model parameterization on the set of hole position locations based on material properties and drilling parameters to obtain the heat generated per hole and the temperature decay function; a cooling interval time calculation module 130, used to calculate the minimum cooling interval time matrix of the set of hole position locations based on the ambient reference temperature and the temperature decay function; a time sequence diagram construction module 140, used to construct a time sequence diagram based on the minimum cooling interval time matrix, the time required to drill a single hole, the tool idle stroke speed, and the set of hole position locations; a path search and optimization module 150, used to perform path search and optimization on the time sequence diagram based on the spatiotemporal A* algorithm for the starting hole position in the set of hole position locations to obtain the optimal path sequence; and a CNC code generation module 160, used to generate CNC code based on the optimal path sequence, the set of hole position locations, and the drilling parameters.

[0080] Here, those skilled in the art will understand that the specific operations of each step in the above-described intelligent drilling path planning system for multi-layer thin plates have been referenced above. Figures 1 to 4 The method for intelligent drilling path planning for multilayer thin plates has been described in detail, and therefore its repeated description will be omitted.

Claims

1. A method for intelligent planning of a drilling path for a multi-layer sheet, characterized by, The method comprises the following steps: obtaining a hole position set, the hole position set being a set containing three-dimensional coordinates of all holes to be drilled; based on material properties and drilling parameters, task analysis and thermal-physical model parameterization are performed on the hole position set to obtain single-hole generated heat and temperature decay function; based on the ambient reference temperature and the temperature decay function, a minimum cooling interval time matrix of the hole position set is calculated; based on the minimum cooling interval time matrix, the time required for drilling a single hole, the tool idle stroke movement speed and the hole position set, a timing diagram is constructed; the starting hole in the hole position set is subjected to path search and optimization based on the space-time A* algorithm in the timing diagram to obtain an optimal path sequence; based on the optimal path sequence, the hole position set and the drilling parameters, numerical control code is generated.

2. The multi-layer sheet oriented drilling path intelligent planning method of claim 1, wherein, Based on material properties and drilling parameters, task analysis and thermal-physical model parameterization are performed on the hole position set to obtain single-hole generated heat and temperature decay function, which comprises: based on material properties, drilling parameters and hole position set, single-hole generated heat is determined by the following formula: wherein, is the cutting torque, is the specific cutting force coefficient, is the tool diameter, is the feed per revolution, is the spindle speed, is the cutting power, is the single hole drilling time, is the drilling depth, is the thermal partition coefficient, is the single hole generated heat; Based on material properties and single-hole generated heat, a temperature decay function is constructed.

3. The multi-layer sheet oriented drilling path intelligent planning method of claim 1, wherein, Based on the ambient reference temperature and the temperature decay function, a minimum cooling interval time matrix of the hole position set is calculated, which comprises: The Euclidean distance between any two holes in the hole position set is calculated to obtain an inter-hole distance matrix; based on the ambient reference temperature and the critical damage temperature, a safe temperature rise threshold is determined; based on the safe temperature rise threshold and the temperature decay function, the inter-hole distance matrix is solved for the minimum cooling time between holes to obtain the minimum cooling interval time matrix.

4. The multi-layer sheet oriented drilling path intelligent planning method of claim 3, wherein, Based on the ambient reference temperature and the critical damage temperature, a safe temperature rise threshold is determined, which comprises: the safe temperature rise threshold is determined by the following formula: wherein, Tcrit is the critical damage temperature, Tambient is the ambient reference temperature, Tsafe is the safety temperature rise threshold.

5. The multi-layer sheet oriented drilling path intelligent planning method of claim 3, wherein, Based on the minimum cooling interval time matrix, the time required for drilling a single hole, the tool idle stroke movement speed and the hole position set, a timing diagram is constructed, which comprises: Based on the inter-hole distance matrix and the tool idle stroke movement speed, a pure movement time matrix is generated; based on the pure movement time matrix, the time required for drilling a single hole and the minimum cooling interval time matrix, the timing diagram is constructed.

6. The multi-layer sheet oriented drilling path intelligent planning method of claim 5, wherein, Based on the pure movement time matrix, the time required for drilling a single hole and the minimum cooling interval time matrix, the timing diagram is constructed, which comprises: based on the pure movement time matrix and the minimum cooling interval time matrix, an effective transfer time matrix is calculated; the elements of each position in the effective transfer time matrix are added to the time required for drilling a single hole to obtain the timing diagram.

7. The multi-layer sheet oriented drilling path intelligent planning method of claim 6, wherein, Based on the pure movement time matrix and the minimum cooling interval time matrix, an effective transfer time matrix is calculated, which comprises: the effective transfer time matrix is calculated by the following formula: wherein, is the pure movement time, is the minimum cooling interval time, is the max function, is the effective transfer time.

8. A multi-layer sheet oriented drilling path intelligent planning system, characterized by, The method comprises the following steps: a hole input module is used to obtain a hole position set, the hole position set being a set containing three-dimensional coordinates of all holes to be drilled; a thermal-physical modeling and parameterization module is used to perform task analysis and thermal-physical model parameterization on the hole position set based on material properties and drilling parameters to obtain single-hole generated heat and temperature decay function; a cooling interval time calculation module is used to calculate a minimum cooling interval time matrix of the hole position set based on the ambient reference temperature and the temperature decay function; a time sequence diagram construction module, configured to construct a time sequence diagram based on the minimum cooling interval time matrix, the time required for drilling a single hole, a tool idle travel movement speed, and the set of hole location positions; a path search and optimization module, configured to perform path search and optimization based on a space-time A* algorithm on the time sequence diagram to obtain an optimal path sequence for a starting hole location in the set of hole location positions; a numerical control code generation module, configured to generate a numerical control code based on the optimal path sequence, the set of hole location positions, and drilling parameters.

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