Multi-axis linkage track optimization system of numerical control planer type milling machine

Abstract

The invention provides a numerical control planer type milling machine multi-axis linkage track optimization system, belongs to the technical field of numerical control planer type milling machine multi-axis linkage machining, and aims at solving the problems that an existing system is poor in track adaptability, insufficient in inter-axis synchronization, single in optimization dimension and complex in operation. The system comprises a data acquisition module, a trajectory planning module, a trajectory optimization module, an execution control module, a state monitoring module, a parameter storage module, a multi-axis cooperative compensation module and a man-machine interaction module, and all the modules are in closed-loop signal linkage. The data acquisition module acquires full-dimensional basic parameters, the trajectory planning module adapts to machining precision through NURBS interpolation, the trajectory optimization module gives consideration to precision, efficiency and inter-axis impact degree through multi-objective optimization, the multi-axis cooperative compensation module corrects errors in real time, and the parameter storage module achieves data reuse. The multi-axis linkage machining precision and stability can be improved, the operation threshold is lowered, and the multi-axis linkage machining method is suitable for high-precision complex workpiece machining.

Description

Technical Field

[0001] This invention relates to the field of multi-axis linkage machining technology for CNC gantry milling machines, and more specifically to a multi-axis linkage trajectory optimization system for CNC gantry milling machines. Background Technology

[0002] Currently, there are three key problems in multi-axis linkage machining on CNC gantry milling machines. First, the trajectory planning is not well-suited to actual machining requirements. Most systems use fixed interpolation algorithms to generate initial trajectories, which cannot be flexibly adjusted according to workpiece accuracy requirements, easily leading to trajectory redundancy or insufficient accuracy, affecting machining quality and efficiency. Second, the synchronization and error control capabilities of multi-axis motion are weak. Displacement differences easily arise during the movement of each axis due to hardware differences and load variations, and there is a lack of real-time error compensation mechanisms, leading to the accumulation of machining errors, especially noticeable in the machining of complex curved surfaces. Third, trajectory optimization is singular in dimension. Traditional systems often optimize only around the single objective of motion accuracy or efficiency, ignoring the impact of inter-axis impact on equipment lifespan. Furthermore, optimization algorithms require manual selection, demanding high levels of operator experience, and optimized parameters are difficult to reuse, increasing the time cost of repetitive machining. In addition, most systems lack intuitive human-machine interaction and real-time status monitoring, making it difficult for users to promptly grasp the equipment status during machining and to quickly intervene in abnormal situations, further restricting the stability and reliability of multi-axis linkage machining. Summary of the Invention

[0003] The present invention aims to solve the problems mentioned in the background art by providing a multi-axis linkage trajectory optimization system for CNC gantry milling machines.

[0004] The specific technical solution is as follows: A multi-axis linkage trajectory optimization system for a CNC gantry milling machine includes a data acquisition module, a trajectory planning module, a trajectory optimization module, an execution control module, a status monitoring module, and a parameter storage module. The output of the data acquisition module is signal-connected to the input of the trajectory planning module, used to transmit the acquired multi-axis motion basic parameters of the CNC gantry milling machine to the trajectory planning module. The output of the trajectory planning module is signal-connected to the input of the trajectory optimization module, used to generate an initial linkage trajectory based on the multi-axis motion basic parameters and transmit it to the trajectory optimization module. The output of the trajectory optimization module is signal-connected to the input of the execution control module, used to process the initial linkage trajectory. After the motion trajectory is optimized, a target linkage trajectory is generated and transmitted to the execution control module. The execution control module is signal-connected to the multi-axis drive unit of the CNC gantry milling machine and is used to control the movement of the multi-axis drive unit according to the target linkage trajectory. The output of the status monitoring module is signal-connected to the trajectory optimization module and the execution control module respectively, and is used to collect real-time status data of multi-axis motion and transmit it to the trajectory optimization module and the execution control module respectively. The output of the parameter storage module is signal-connected to the data acquisition module, the trajectory planning module and the trajectory optimization module respectively, and is used to store the basic parameters of multi-axis motion, the trajectory planning algorithm parameters and the trajectory optimization evaluation parameters.

[0005] In a preferred embodiment of the present invention, the data acquisition module includes a workpiece model import unit, a machining process parameter input unit, and a multi-axis hardware parameter acquisition unit; the workpiece model import unit is used to import three-dimensional model data of the workpiece, the machining process parameter input unit is used to input cutting speed, feed rate, and depth of cut parameters, and the multi-axis hardware parameter acquisition unit is used to acquire the travel, maximum speed, and acceleration parameters of each axis; the output terminals of the workpiece model import unit, the machining process parameter input unit, and the multi-axis hardware parameter acquisition unit are all connected to the total output terminal of the data acquisition module.

[0006] As a preferred embodiment of the present invention, the trajectory planning module uses the NURBS curve interpolation algorithm to generate an initial linkage trajectory; the trajectory planning module is provided with an interpolation accuracy adjustment unit, which is used to adjust the interpolation node density of the NURBS curve according to the workpiece machining accuracy requirements, and the interpolation node density is positively correlated with the machining accuracy requirements.

[0007] In a preferred embodiment of the present invention, the trajectory optimization module includes a multi-objective optimization unit and an optimization algorithm selection unit; the multi-objective optimization unit constructs an objective function with trajectory motion accuracy, motion efficiency, and inter-axis impact as optimization objectives; the optimization algorithm selection unit incorporates a genetic algorithm, a particle swarm optimization algorithm, and a simulated annealing algorithm, and can automatically select a matching optimization algorithm based on the complexity of the initial linkage trajectory; the output of the optimization algorithm selection unit is connected to the input of the multi-objective optimization unit, and is used to transmit the selected optimization algorithm to the multi-objective optimization unit for trajectory optimization calculation.

[0008] In a preferred embodiment of the present invention, the execution control module includes a trajectory command conversion unit and an inter-axis synchronization control unit; the trajectory command conversion unit is used to convert the target linkage trajectory into pulse control commands that can be recognized by the multi-axis drive unit; the inter-axis synchronization control unit is used to calibrate the motion displacement difference of each axis in real time, so that the motion displacement difference of each axis is controlled within a preset synchronization error range; the output terminal of the trajectory command conversion unit is signal-connected to the input terminal of the inter-axis synchronization control unit, and the output terminal of the inter-axis synchronization control unit is signal-connected to the multi-axis drive unit.

[0009] As a preferred embodiment of the present invention, the status monitoring module includes a displacement sensor, a velocity sensor, and a vibration sensor; the displacement sensor is used to collect real-time displacement data of each axis, the velocity sensor is used to collect real-time velocity data of each axis, and the vibration sensor is used to collect equipment vibration data during multi-axis linkage; the output terminals of the displacement sensor, velocity sensor, and vibration sensor are all connected to the total output terminal of the status monitoring module, and the real-time status data transmission frequency is not less than 1kHz.

[0010] As a preferred embodiment of the present invention, the parameter storage module includes a data classification storage unit and a data update unit; the data classification storage unit stores the multi-axis motion basic parameters, trajectory planning algorithm parameters and trajectory optimization evaluation parameters in separate directories; the data update unit is used to update the optimal parameters generated in this optimization process to the corresponding storage directory after each trajectory optimization is completed, and retain historical parameter versions for retrospective recall.

[0011] As a preferred embodiment of the present invention, the multi-objective optimization unit has a built-in weight adjustment unit; the weight adjustment unit is used to adjust the optimization weights of motion accuracy, motion efficiency and inter-axis impact according to the processing requirements; when the processing requirement is high precision priority, the weight coefficient of motion accuracy is not less than 0.5; when the processing requirement is high efficiency priority, the weight coefficient of motion efficiency is not less than 0.5.

[0012] As a preferred embodiment of the present invention, it further includes a multi-axis collaborative compensation module; the input end of the multi-axis collaborative compensation module is connected to the output end of the state monitoring module, and the output end is connected to the input end of the trajectory optimization module; the multi-axis collaborative compensation module is used to calculate the cumulative error of each axis based on the real-time state data of multi-axis motion, and generate an error compensation amount which is transmitted to the trajectory optimization module, so that the trajectory optimization module incorporates the error compensation amount during the optimization process.

[0013] As a preferred embodiment of the present invention, it further includes a human-computer interaction module; the input end of the human-computer interaction module is connected to the data acquisition module, the trajectory optimization module and the status monitoring module respectively, and is used to receive and display the basic parameters of multi-axis motion, the target linkage trajectory and the real-time status data of multi-axis motion; the output end of the human-computer interaction module is connected to the execution control module, and is used to receive the motion start / stop command and parameter adjustment command input by the user and transmit them to the execution control module.

[0014] The present invention has the following beneficial effects: 1. End-to-end collaborative optimization to improve overall machining performance: The system's modules form a data and control closed loop. The data acquisition module comprehensively collects workpiece, process, and hardware parameters, providing a precise foundation for trajectory planning. The trajectory optimization module optimizes multiple objectives, including accuracy, efficiency, and inter-axis impact, to avoid machining imbalances caused by a single objective. The execution control and status monitoring modules work in real time, calibrating inter-axis synchronization errors and capturing equipment anomalies. Ultimately, this achieves a synergistic improvement in machining accuracy, efficiency, and equipment protection, solving the problem of traditional systems "paying attention to one thing but neglecting another."

[0015] 2. Dynamic error compensation to reduce machining errors: The newly added multi-axis collaborative compensation module can calculate the cumulative error based on the real-time data collected by the status monitoring module and integrate the compensation amount into the trajectory optimization process. This avoids the error lag problem caused by the traditional system's "plan first, then compensate" approach, and can effectively improve the error accumulation phenomenon in multi-axis motion. Especially in long-term continuous machining, it can maintain stable machining accuracy.

[0016] 3. Flexible adaptation to processing needs and reduced operating threshold: The trajectory planning module can adapt to different accuracy requirements through the interpolation accuracy adjustment unit. The trajectory optimization module can automatically select the algorithm with matching complexity, and the multi-objective optimization unit supports weight adjustment, which can adjust the optimization focus according to the needs of high precision or high efficiency. At the same time, the parameter storage module can classify, store and update the optimal parameters, reduce manual repetitive settings, reduce dependence on operator experience, and improve the system's adaptability to different workpieces and different process scenarios.

[0017] 4. Enhanced visualization and controllability ensure stable processing: The human-machine interface module can display basic parameters, target trajectory, and equipment status in real time, allowing users to intuitively grasp the processing progress; it also supports manual input of start / stop and parameter adjustment commands, enabling rapid intervention in cases of abnormal equipment vibration or speed deviation; the status monitoring module transmits real-time data at high frequency, and in conjunction with the synchronous calibration of the execution control module, it can effectively prevent the amplification of multi-axis motion anomalies, ensure the stability of the processing process, and reduce the scrap rate caused by equipment failure or parameter deviation. Attached Figure Description

[0018] Figure 1 This is a connection relationship block diagram of the CNC gantry milling machine multi-axis linkage trajectory optimization system provided in an embodiment of the present invention; Figure 2 A comparison chart showing the time consumption for parameter setting of CNC gantry milling machines using this system and traditional systems; Figure 3 A comparison chart showing the machining accuracy of CNC gantry milling machines using this system and traditional systems; Figure 4 A comparison chart of vibration of CNC gantry milling machine equipment using this system and traditional systems; Figure 5 This chart compares the processing efficiency of CNC gantry milling machines using this system and traditional systems. Detailed Implementation

[0019] The technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0020] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual images. They should not be construed as limiting the scope of this application. To better illustrate the embodiments of the present invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual dimensions of the product. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0021] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "inner," and "outer" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present application. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0022] In the description of this invention, unless otherwise explicitly specified and limited, the term "connection" or similar designation indicating a connection between components should be interpreted broadly. For example, it can refer to a fixed connection, a detachable connection, or an integral part; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can refer to the internal communication between two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0023] Example The CNC gantry milling machine multi-axis linkage trajectory optimization system provided in this embodiment, such as Figures 1-5 As shown, the system includes a data acquisition module, a trajectory planning module, a trajectory optimization module, an execution control module, a status monitoring module, and a parameter storage module. The output of the data acquisition module is connected to the input of the trajectory planning module to transmit the acquired basic motion parameters of the CNC gantry milling machine to the trajectory planning module. The output of the trajectory planning module is connected to the input of the trajectory optimization module to generate an initial linkage trajectory based on the basic motion parameters and transmit it to the trajectory optimization module. The output of the trajectory optimization module is connected to the input of the execution control module to optimize the initial linkage trajectory, generate a target linkage trajectory, and transmit it to the execution control module. The execution control module is connected to the multi-axis drive unit of the CNC gantry milling machine to control the movement of the multi-axis drive unit according to the target linkage trajectory. The output of the status monitoring module is connected to both the trajectory optimization module and the execution control module to collect real-time status data of the multi-axis motion and transmit it to both modules respectively. The output of the parameter storage module is connected to the data acquisition module, the trajectory planning module, and the trajectory optimization module to store the basic motion parameters of the multi-axis motion, the trajectory planning algorithm parameters, and the trajectory optimization evaluation parameters.

[0024] This solution establishes a complete modular architecture encompassing "data acquisition, trajectory planning, trajectory optimization, execution control, status monitoring, and parameter storage," and clearly defines the signal connections between each module, forming a closed-loop system for multi-axis linkage trajectory optimization. Its technical advantages include: enabling seamless coordination throughout the entire process from basic parameter input to trajectory execution, status feedback, and parameter storage, avoiding data gaps or coordination breakdowns between modules; simultaneously, each module performs its specific function while supporting each other, providing a structural foundation for the systematic optimization of multi-axis linkage trajectories, ensuring the orderly and reliable trajectory optimization process, and thus laying a framework guarantee for subsequent precise control of multi-axis motion.

[0025] Specifically, in this embodiment, the data acquisition module includes a workpiece model import unit, a machining process parameter input unit, and a multi-axis hardware parameter acquisition unit. The workpiece model import unit is used to import the three-dimensional model data of the workpiece, the machining process parameter input unit is used to input the cutting speed, feed rate, and depth of cut parameters, and the multi-axis hardware parameter acquisition unit is used to acquire the travel, maximum speed, and acceleration parameters of each axis. The output terminals of the workpiece model import unit, the machining process parameter input unit, and the multi-axis hardware parameter acquisition unit are all connected to the total output terminal of the data acquisition module.

[0026] This solution refines the data acquisition module into three units: workpiece model import, machining process parameter input, and multi-axis hardware parameter acquisition, respectively acquiring key basic data related to the workpiece, process, and hardware. Its technical advantages are: comprehensive coverage of the core basic data required for multi-axis linkage trajectory planning, avoiding initial trajectory planning deviations due to missing parameters; and by collecting data from different dimensions, ensuring the completeness and accuracy of parameters input to the trajectory planning module, reducing the correction costs of subsequent trajectory optimization, and providing data support for the rationality of the initial linkage trajectory.

[0027] Specifically, in this embodiment, the trajectory planning module uses the NURBS curve interpolation algorithm to generate the initial linkage trajectory; the trajectory planning module is equipped with an interpolation accuracy adjustment unit, which is used to adjust the interpolation node density of the NURBS curve according to the workpiece machining accuracy requirements, and the interpolation node density is positively correlated with the machining accuracy requirements.

[0028] This solution uses the NURBS curve interpolation algorithm to generate the initial trajectory and sets up an interpolation accuracy adjustment unit to adapt to the machining accuracy requirements. Its technical advantages are: the NURBS curve interpolation algorithm itself is suitable for trajectory description of complex surfaces, generating smooth and continuous initial linkage trajectories, reducing the impact of trajectory breakpoints on machining quality; at the same time, the interpolation accuracy can be adjusted according to the machining accuracy requirements, ensuring trajectory details in high-precision machining scenarios while avoiding trajectory redundancy caused by over-interpolation in conventional accuracy scenarios, thus improving the flexibility and adaptability of trajectory planning.

[0029] Specifically, in this embodiment, the trajectory optimization module includes a multi-objective optimization unit and an optimization algorithm selection unit. The multi-objective optimization unit constructs an objective function with trajectory motion accuracy, motion efficiency, and inter-axis impact as optimization objectives. The optimization algorithm selection unit incorporates a genetic algorithm, a particle swarm optimization algorithm, and a simulated annealing algorithm, and can automatically select a matching optimization algorithm based on the complexity of the initial linkage trajectory. The output of the optimization algorithm selection unit is connected to the input of the multi-objective optimization unit to transmit the selected optimization algorithm to the multi-objective optimization unit for trajectory optimization calculation.

[0030] This scheme divides the trajectory optimization module into a multi-objective optimization unit and an optimization algorithm selection unit. The former constructs a function with accuracy, efficiency, and inter-axis impact as objectives, while the latter automatically selects an algorithm based on trajectory complexity. The technical advantages are: multi-objective optimization avoids the machining imbalance caused by single-objective optimization (such as pursuing only accuracy while ignoring efficiency), balancing machining quality, machining speed, and equipment protection; automatic algorithm selection eliminates the need for manual judgment of suitable algorithms, matching the optimal calculation method based on trajectory complexity, reducing the problem of low optimization efficiency or poor optimization results caused by inappropriate algorithm selection, and improving the targeting and efficiency of trajectory optimization.

[0031] Specifically, in this embodiment, the execution control module includes a trajectory command conversion unit and an inter-axis synchronization control unit; the trajectory command conversion unit is used to convert the target linkage trajectory into pulse control commands that can be recognized by the multi-axis drive unit; the inter-axis synchronization control unit is used to calibrate the motion displacement difference of each axis in real time, so that the motion displacement difference of each axis is controlled within a preset synchronization error range; the output end of the trajectory command conversion unit is signal-connected to the input end of the inter-axis synchronization control unit, and the output end of the inter-axis synchronization control unit is signal-connected to the multi-axis drive unit.

[0032] This solution incorporates a trajectory command conversion and an inter-axis synchronization control unit within the execution control module, responsible for command conversion and displacement difference calibration, respectively. The technical benefits are as follows: trajectory command conversion ensures that the optimized target trajectory can be accurately converted into action commands recognizable by the multi-axis drive unit, avoiding motion deviations caused by command incompatibility; inter-axis synchronization control reduces machining errors caused by asynchronous motion of each axis through real-time calibration of displacement differences, ensuring the accuracy and stability of multi-axis linkage motion and improving final machining precision.

[0033] Specifically, in this embodiment, the status monitoring module includes a displacement sensor, a velocity sensor, and a vibration sensor; the displacement sensor is used to collect real-time displacement data of each axis, the velocity sensor is used to collect real-time velocity data of each axis, and the vibration sensor is used to collect equipment vibration data during multi-axis linkage; the output terminals of the displacement sensor, velocity sensor, and vibration sensor are all connected to the total output terminal of the status monitoring module, and the real-time status data transmission frequency is not less than 1kHz.

[0034] This solution collects real-time data using three types of sensors: displacement, velocity, and vibration, while ensuring high-frequency data transmission. Its technical advantages include: real-time capture of displacement states, velocity changes, and equipment vibration in multi-axis motion, comprehensively reflecting dynamic information during multi-axis linkage; and timely data transmission ensuring prompt feedback to the optimization and control modules, facilitating rapid response to motion anomalies (such as excessive vibration or velocity deviation), preventing the escalation of anomalies from affecting processing quality or equipment safety, and ensuring stable processing.

[0035] Specifically, in this embodiment, the parameter storage module includes a data classification storage unit and a data update unit; the data classification storage unit stores the multi-axis motion basic parameters, trajectory planning algorithm parameters and trajectory optimization evaluation parameters in separate directories; the data update unit is used to update the optimal parameters generated in this optimization process to the corresponding storage directory after each trajectory optimization is completed, and retain historical parameter versions for retrospective recall.

[0036] This scheme incorporates categorized storage and data update units within the parameter storage module, while also retaining historical parameter versions. The technical benefits are as follows: categorized storage makes the management of different parameter types (basic parameters, algorithm parameters, evaluation parameters) clearer, facilitating subsequent retrieval and access; the data update unit saves the optimal parameters from each optimization, enabling the reuse of high-quality parameters and reducing the cost of repetitive optimization; and historical parameter backtracking facilitates tracing the optimization process, analyzing the impact of parameter adjustments on trajectory performance, providing a reference for subsequent optimization strategy adjustments, and improving parameter utilization efficiency.

[0037] Specifically, in this embodiment, the multi-objective optimization unit has a built-in weight adjustment unit; the weight adjustment unit is used to adjust the optimization weights of motion accuracy, motion efficiency and inter-axis impact according to the processing requirements; when the processing requirement is high precision priority, the weight coefficient of motion accuracy is not less than 0.5; when the processing requirement is high efficiency priority, the weight coefficient of motion efficiency is not less than 0.5.

[0038] This scheme adds a weight adjustment unit to the multi-objective optimization unit, adjusting the weights of each objective according to processing requirements. Its technical advantages are: it can flexibly allocate optimization priorities based on actual processing priorities (such as high-precision processing or high-efficiency processing), avoiding a disconnect between optimization objectives and actual needs; for example, when prioritizing high precision, the focus is on ensuring trajectory accuracy, while when prioritizing high efficiency, the focus is on improving movement speed, making the optimized trajectory more suitable for the specific processing scenario and enhancing the practicality and relevance of trajectory optimization.

[0039] Specifically, in this embodiment, a multi-axis collaborative compensation module is also included; the input end of the multi-axis collaborative compensation module is connected to the output end of the state monitoring module, and the output end is connected to the input end of the trajectory optimization module; the multi-axis collaborative compensation module is used to calculate the cumulative error of each axis based on the real-time state data of multi-axis motion, and generate an error compensation amount which is transmitted to the trajectory optimization module, so that the trajectory optimization module incorporates the error compensation amount during the optimization process.

[0040] This solution adds a multi-axis collaborative compensation module, which calculates cumulative errors and generates compensation amounts based on real-time status data, integrating it into trajectory optimization. Its technical advantages are: it can proactively identify and correct cumulative errors generated during the movement of each axis, preventing error accumulation from affecting trajectory accuracy; by combining error compensation with trajectory optimization, the optimized target trajectory inherently possesses error correction effects, further reducing machining errors, improving the accuracy of multi-axis linkage motion, and ultimately improving product machining quality.

[0041] Specifically, in this embodiment, a human-computer interaction module is also included; the input end of the human-computer interaction module is connected to the data acquisition module, the trajectory optimization module and the status monitoring module respectively, and is used to receive and display the basic parameters of multi-axis motion, the target linkage trajectory and the real-time status data of multi-axis motion; the output end of the human-computer interaction module is connected to the execution control module, and is used to receive the motion start and stop commands and parameter adjustment commands input by the user and transmit them to the execution control module.

[0042] This solution adds a human-computer interaction module, enabling data display and command input. Its technical advantages are: users can intuitively view basic parameters, target trajectory, and real-time motion status, clearly understanding the system's operation and avoiding blind operation due to information asymmetry; simultaneously, users can directly input start / stop commands and parameter adjustment commands, allowing for timely intervention in the motion process based on actual processing conditions, enhancing the system's operability and flexibility, and improving the user's control over the processing.

[0043] Specifically, in this embodiment, the multi-objective optimization unit constructs an objective function based on the real-time dynamic characteristics of multi-axis motion during the online optimization process. The specific expression is as follows: ; in: θ is the trajectory parameter vector, used to define the planned trajectory q(θ,t) for multi-axis linkage. It is obtained through iterative adjustment by optimization algorithm. For example, in a five-axis linkage scenario, it is the coordinate vector of 8-15 control points of the NURBS curve. q(θ,t) is the multi-axis real-time planning position vector determined by parameter θ at time t. It is generated by θ and time t and takes values ​​in the range [X(t),Y(t),Z(t),A(t),C(t)]T, with units of mm, mm, mm, deg, and deg, respectively. q d (t) is the multi-axis expected position trajectory vector at time t, derived from the initial linkage trajectory output by the trajectory planning module, and has the same dimension as q(θ,t). For example, at t=600s, q d (600) = [250, 180, 80, 30, 45] T ; K is the error compensation gain matrix, which is pre-calibrated through system identification experiments combined with multi-axis hardware parameters. The gain coefficients for the diagonal matrix and linear axes are typically 0.6-0.9, while those for the rotation axes are 0.5-0.8. e c (t c ) represents the current monitoring time t c The multi-axis cumulative error vector is calculated and generated by the multi-axis collaborative compensation module. According to the machining accuracy requirements, the absolute value is usually ≤0.005mm (linear axis) and ≤0.001deg (rotary axis). μ is the impact weighting coefficient, which can be manually set in the human-computer interaction module according to processing requirements or adaptively adjusted by the system based on the initial trajectory complexity; the value range is 0.1-0.8, 0.2-0.4 for high-precision processing and 0.5-0.7 for high-smoothness processing; The vector of multi-axis acceleration change rate, determined by parameter θ at time t, reflects the degree of inter-axis impact. It is obtained by taking the second derivative of q(θ,t) and then taking the third derivative, with units of mm / s. 3 (Linear axis), deg / s 3 (Rotating axis), usually controlled within 80% of the maximum allowable value of the equipment; t c The starting time for current trajectory optimization is synchronized with the system clock and changes dynamically with the processing progress, typically triggering online optimization every 30-120 seconds; T represents the total duration of this multi-axis linkage machining process, which is preset according to the machining process parameters. For simple workpieces, it is 500-1000s, and for complex workpieces, it is 1500-3000s. The derivation of the equation is as follows: The derivation of the objective function is based on the core logic of "dynamic error compensation - multi-objective collaborative optimization" and is completed in three steps: 1. Error Compensation Term Construction: Traditional trajectory optimization only considers the deviation between the planned trajectory and the desired trajectory as the optimization objective, ignoring the impact of real-time accumulated error. This equation introduces a multi-axis collaborative compensation module to calculate e. c (t c ), and convert it into a compensation quantity K·e through a pre-calibrated gain matrix K. c (t c This makes the compensated trajectory deviation become q(θ,t)-q d (t)+K·e c (t c Take the square of the 2-norm of this deviation vector. The trajectory tracking accuracy after compensation can be quantified, and minimizing this term can effectively suppress error accumulation.

[0044] 2. Impact Constraint Construction: Inter-shaft impact is determined by the rate of change of acceleration. The larger the value, the more severe the equipment vibration and hardware wear. (Introduction) 2-norm square As a quantitative indicator of impact, the optimization priority of accuracy and impact is balanced by the weighting coefficient μ, so as to avoid equipment damage caused by solely pursuing accuracy.

[0045] 3. Integration of Time Integral and Objective Function: Multi-axis linkage machining is a continuous time process, requiring the integration of the "compensated accuracy term" and the "impact constraint term" within the remaining machining time interval [t]. c Integrating within [T] ensures that the entire machining process meets the requirements for accuracy and smoothness, ultimately forming a complete objective function F(θ), achieving the dual optimization goal of "real-time error correction + smooth motion throughout the process".

[0046] Example: Taking "complex cavity machining of automotive mold steel (H13)" as the application scenario, a CNC gantry milling machine (XK2730 type) equipped with this system performs five-axis linkage machining. The specific application process of the equation is as follows: 1. Parameter initialization: Before processing, the compensation gain matrix K (a diagonal matrix, with diagonal elements corresponding to the compensation coefficients of the five axes X / Y / Z / A / C) of historical H13 steel processing is called through the parameter storage module. The impact weight coefficient μ=0.3 is set in the human-computer interaction module (prioritizing accuracy while taking into account smoothness). The total processing time T=1800s is preset according to the process parameters.

[0047] 2. Real-time data acquisition and error calculation: Processing continues until t c At 600s, the displacement sensor (sampling frequency 1kHz) of the state monitoring module collects real-time position data for five axes. The multi-axis collaborative compensation module compares the "theoretical position - actual position" and calculates the cumulative error vector e. c (600) = [0.003, -0.002, 0.001, 0.0008, -0.0005] T mm.

[0048] 3. Online Optimization Calculation: The trajectory optimization module calls a genetic algorithm (the optimization algorithm selection unit determines that the current cavity trajectory complexity is medium to high and matches the genetic algorithm). With F(θ) as the objective function, it iteratively optimizes the trajectory parameters θ (coordinates of the 12 control points of the NURBS curve) for the remaining time period [600, 1800] s. The number of iterations is set to 50, and finally the optimal parameters that minimize F(θ) are obtained. .

[0049] 4. Optimize trajectory output and execution: The trajectory optimization module, based on... The updated target trajectory is generated and transmitted to the execution control module. The trajectory command conversion unit converts it into pulse commands that the five-axis drive unit can recognize. The inter-axis synchronization control unit combines the new trajectory to calibrate the inter-axis displacement difference in real time, ensuring that the optimized trajectory is executed accurately.

[0050] Technical effects: 1. Improved dynamic accuracy: Compared to traditional fixed trajectory optimization, this equation incorporates e in real time. c (t c Dynamic error compensation was achieved. In the H13 steel mold processing experiment, the multi-axis position error was reduced from 0.008-0.012mm in the traditional system to 0.002-0.005mm, meeting the requirements of high-precision processing.

[0051] 2. Enhanced equipment protection: Introduced After the constraint terms are applied, the vibration amplitude of the spindle box during the five-axis linkage process is reduced from 0.15-0.2mm in the traditional system to 0.06-0.09mm, which reduces the wear of the guide rail and lead screw caused by the inter-axis impact and extends the equipment maintenance cycle by more than 30%.

[0052] 3. Adaptive capability optimization: The compensation gain matrix K and weight coefficient μ can be flexibly adjusted according to the processing material (such as aluminum alloy, mold steel) and workpiece accuracy requirements, without the need to redevelop the algorithm, and the efficiency is improved by 40% to adapt to different processing scenarios.

[0053] 4. Closed-loop collaborative enhancement: The equations rely on real-time data from the state monitoring module and error calculation results from the multi-axis collaborative compensation module, and are deeply coupled with the existing modules of the system to form a complete closed loop of "data acquisition - error calculation - optimization execution - state feedback", avoiding data isolation between modules.

[0054] The working principle and process are as follows: 1. Parameter preset and initialization: Before processing, the historical optimized parameters (historical optimal values ​​of K and μ) are called through the parameter storage module, and combined with the current processing technology parameter preset T, the basic parameter configuration of the objective function is completed.

[0055] 2. Real-time data acquisition: During the processing, the status monitoring module acquires multi-axis displacement and velocity data at a frequency of 1kHz and transmits it to the multi-axis collaborative compensation module and trajectory optimization module in real time.

[0056] 3. Cumulative Error Calculation: Comparison of Multi-Axis Collaborative Compensation Module with "q" d (t) - actual location data", calculate e c (t), and at the set optimization trigger time t c (e.g., every 60 seconds) e c (t c The data is transmitted to the trajectory optimization module.

[0057] 4. Objective Function Construction and Optimization: The trajectory optimization module receives e c (t c After that, substituting the objective function F(θ), and combining iterative optimization algorithms (such as genetic algorithms or particle swarm optimization) to select unit matching algorithms, θ is optimized to obtain the optimal trajectory parameters. .

[0058] 5. Optimize trajectory execution and feedback: The trajectory optimization module, based on... The target trajectory is generated and transmitted to the execution control module for execution; simultaneously, the status monitoring module continuously collects execution data of the new trajectory to prepare for the next execution. c Optimization at any given moment provides data support, forming a cycle.

[0059] In summary, the CNC gantry milling machine multi-axis linkage trajectory optimization system provided in this embodiment achieves multi-dimensional technical improvements through a closed-loop architecture of "data acquisition - trajectory planning - trajectory optimization - execution control - status monitoring - parameter storage" combined with multi-module collaborative design. The specific effects are as follows: 1. End-to-end collaborative optimization to improve overall machining performance: The system's modules form a data and control closed loop. The data acquisition module comprehensively collects workpiece, process, and hardware parameters, providing a precise foundation for trajectory planning. The trajectory optimization module optimizes multiple objectives, including accuracy, efficiency, and inter-axis impact, to avoid machining imbalances caused by a single objective. The execution control and status monitoring modules work in real time, calibrating inter-axis synchronization errors and capturing equipment anomalies. Ultimately, this achieves a synergistic improvement in machining accuracy, efficiency, and equipment protection, solving the problem of traditional systems "paying attention to one thing but neglecting another."

[0060] 2. Dynamic error compensation to reduce machining errors: The newly added multi-axis collaborative compensation module can calculate the cumulative error based on the real-time data collected by the status monitoring module and integrate the compensation amount into the trajectory optimization process. This avoids the error lag problem caused by the traditional system's "plan first, then compensate" approach, and can effectively improve the error accumulation phenomenon in multi-axis motion. Especially in long-term continuous machining, it can maintain stable machining accuracy.

[0061] 3. Flexible adaptation to processing needs and reduced operating threshold: The trajectory planning module can adapt to different accuracy requirements through the interpolation accuracy adjustment unit. The trajectory optimization module can automatically select the algorithm with matching complexity, and the multi-objective optimization unit supports weight adjustment, which can adjust the optimization focus according to the needs of high precision or high efficiency. At the same time, the parameter storage module can classify, store and update the optimal parameters, reduce manual repetitive settings, reduce dependence on operator experience, and improve the system's adaptability to different workpieces and different process scenarios.

[0062] 4. Enhanced visualization and controllability ensure stable processing: The human-machine interface module can display basic parameters, target trajectory, and equipment status in real time, allowing users to intuitively grasp the processing progress; it also supports manual input of start / stop and parameter adjustment commands, enabling rapid intervention in cases of abnormal equipment vibration or speed deviation; the status monitoring module transmits real-time data at high frequency, and in conjunction with the synchronous calibration of the execution control module, it can effectively prevent the amplification of multi-axis motion anomalies, ensure the stability of the processing process, and reduce the scrap rate caused by equipment failure or parameter deviation.

[0063] Working principle: The system operates on a core logic of "data-driven, trajectory processing, execution feedback, and parameter accumulation," with each module working collaboratively according to the following process: 1. Data Input and Preprocessing: The workpiece model import unit, machining process parameter input unit, and multi-axis hardware parameter acquisition unit of the data acquisition module respectively collect parameters such as the workpiece 3D model, cutting speed / feed rate / depth of cut, and travel / maximum speed / acceleration of each axis. After integrating these parameters, they are transmitted to the trajectory planning module. At the same time, the parameter storage module will synchronously transmit the historically stored trajectory planning algorithm parameters and optimization evaluation parameters to the trajectory planning and trajectory optimization modules to provide reference for subsequent processing.

[0064] 2. Initial trajectory generation: The trajectory planning module uses the NURBS curve interpolation algorithm, combined with the input basic parameters and historical algorithm parameters, to generate an initial linkage trajectory that adapts to the workpiece processing path; if there is a need for accuracy adjustment, the interpolation accuracy adjustment unit will adjust the interpolation node density according to the processing accuracy requirements to ensure the smoothness and accuracy adaptability of the initial trajectory.

[0065] 3. Multi-objective trajectory optimization: After receiving the initial linkage trajectory, the trajectory optimization module will automatically match the genetic algorithm, particle swarm optimization, or simulated annealing algorithm according to the trajectory complexity (such as the number of path inflection points and surface curvature changes); the multi-objective optimization unit constructs functions with motion accuracy, motion efficiency, and inter-axis impact as objectives. If it is necessary to adapt to the processing priority, the weight adjustment unit will adjust the weights of each objective and finally generate the target linkage trajectory.

[0066] 4. Execution Control and Real-time Feedback: The trajectory command conversion unit of the execution control module converts the target linkage trajectory into pulse commands recognizable by the multi-axis drive unit. The inter-axis synchronization control unit calibrates the displacement difference of each axis in real time to ensure synchronous movement of multiple axes. At the same time, the status monitoring module collects real-time data through displacement, velocity, and vibration sensors. On the one hand, it transmits the data to the trajectory optimization module to provide dynamic basis for the optimization process. On the other hand, it transmits the data to the multi-axis collaborative compensation module to calculate the cumulative error and generate compensation amount, which is fed back to the trajectory optimization module to correct the trajectory. If the data is abnormal, the status monitoring module will trigger the reminder function of the human-machine interaction module.

[0067] 5. Parameter storage and update: After each trajectory optimization and processing is completed, the data update unit of the parameter storage module will update the optimal parameters (such as algorithm parameters and weight coefficients) of this optimization to the corresponding directory. The data classification storage unit saves them in directories according to type, and at the same time retains historical parameter versions for subsequent processing backtracking or parameter reuse.

[0068] How to use: 1. System Preparation and Parameter Input: The operator starts the system through the human-machine interface module and completes three operations in the data acquisition module: First, import the 3D model data of the workpiece to be processed through the workpiece model import unit; second, set process parameters such as cutting speed, feed rate, and depth of cut through the machining process parameter input unit; third, trigger the equipment self-check through the multi-axis hardware parameter acquisition unit to automatically acquire hardware parameters such as the stroke, maximum speed, and acceleration of each axis. During the parameter input process, the human-machine interface module will display the input data in real time for the operator to verify.

[0069] 2. Trajectory planning parameter settings: According to the workpiece machining accuracy requirements, the operator can adjust the interpolation accuracy adjustment unit of the trajectory planning module through the human-machine interaction module to set the appropriate interpolation accuracy (such as increasing the interpolation node density in high-precision machining scenarios); at the same time, the parameter storage module will automatically call the trajectory planning algorithm parameters of similar workpieces in the past, and the operator can choose to reuse or fine-tune them according to actual needs, reducing parameter setting time.

[0070] 3. Trajectory Optimization Target Configuration: In the human-computer interaction module, select the processing priority (high precision priority or high efficiency priority). The system will automatically adjust the optimization weights of motion accuracy, motion efficiency, and inter-axis impact through the weight adjustment unit of the trajectory optimization module. If custom weights are required, the operator can manually input the weight coefficients of each target. After the settings are completed, the optimization algorithm selection unit of the trajectory optimization module will automatically match the optimization algorithm according to the initial trajectory complexity without manual intervention.

[0071] 4. Machining Execution and Status Monitoring: The operator sends a machining start command to the execution control module through the human-machine interface module. The system generates the target linkage trajectory according to the working principle and drives the multi-axis motion. During machining, the human-machine interface module displays the real-time status of the multi-axis motion (such as displacement, speed, and equipment vibration of each axis). If the status monitoring module detects abnormal data (such as excessive vibration), the human-machine interface module will pop up a reminder. The operator can choose to pause machining, adjust the parameters through the human-machine interface module (such as reducing the feed rate), and then restart.

[0072] 5. Post-processing data management: After processing is completed, the parameter storage module automatically updates the optimal parameters (algorithm parameters, weight coefficients, error compensation amount) of this optimization to the corresponding storage directory and retains historical parameters. Operators can view the trajectory data (comparison between initial trajectory and target trajectory) and status data (vibration curve, displacement error curve) of this processing through the human-computer interaction module. If similar workpieces are processed in the future, the historical optimal parameters in the parameter storage module can be directly called without repeating the settings.

[0073] This embodiment also provides an example of a multi-axis linkage trajectory optimization system for a CNC gantry milling machine, as detailed below: I. Basic Information of the Example This example uses "machining of aerospace aluminum alloy integral frame workpieces" as the application scenario, and adopts the XK2420 CNC gantry milling machine as the basic machining equipment. It is equipped with the "CNC gantry milling machine multi-axis linkage trajectory optimization system" of this invention to perform multi-axis linkage machining on complex curved surfaces (curvature radius variation range 0.8m-5m), deep cavities (depth 80mm), and high-precision hole systems (hole diameter tolerance ±0.005mm) on the workpiece.

[0074] The system comprises the following modules: a data acquisition module (including a workpiece model import unit, a machining process parameter input unit, and a multi-axis hardware parameter acquisition unit), a trajectory planning module (including a NURBS curve interpolation algorithm and an interpolation accuracy adjustment unit), a trajectory optimization module (including a multi-objective optimization unit, an optimization algorithm selection unit, and a weight adjustment unit), an execution control module (including a trajectory command conversion unit and an inter-axis synchronization control unit), a status monitoring module (including displacement sensors, velocity sensors, and vibration sensors), a parameter storage module (including a data classification storage unit and a data update unit), a multi-axis collaborative compensation module, and a human-machine interaction module. Each module achieves data interaction according to the signal connection relationships defined in the embodiment.

[0075] II. Detailed Implementation Process 1. System startup and parameter input The operator starts the system through the human-computer interaction module and first imports the SolidWorks 3D model data (in STEP format) of the aluminum alloy integral frame through the workpiece model import unit of the data acquisition module. The process parameters are set through the machining process parameter input unit: the cutting speed is set to the medium speed range according to the aluminum alloy material, the feed rate is set according to the differences between the hole system and the curved surface, and the cutting depth is set according to the deep cavity layering machining requirements. The device self-test is triggered by the multi-axis hardware parameter acquisition unit, which automatically acquires the travel of the X-axis / Y-axis / Z-axis / W-axis (four-axis linkage), the maximum speed and acceleration parameters of each axis of the XK2420 milling machine; The parameter storage module's data classification storage unit automatically retrieves trajectory planning algorithm parameters (such as NURBS interpolation initial node density) and trajectory optimization evaluation parameters (such as inter-axis impact threshold) for similar aluminum alloy workpieces from the past, and displays them on the human-machine interaction module. Once the operator confirms, there is no need to modify them repeatedly.

[0076] 2. Initial linkage trajectory generation After receiving the complete parameters transmitted by the data acquisition module, the trajectory planning module starts the NURBS curve interpolation algorithm to fit the machining path of the complex curved surface of the workpiece and generate a continuous four-axis linkage initial trajectory. Because the workpiece hole system requires high precision (tolerance ±0.005mm), the operator sends instructions to the interpolation accuracy adjustment unit of the trajectory planning module through the human-machine interaction module to increase the interpolation node density of the hole system machining path, making the initial trajectory more detailed in the hole system area; while the curved surface area retains the initial node density according to the conventional precision requirements to avoid excessive interpolation leading to trajectory redundancy.

[0077] 3. Trajectory Multi-Objective Optimization After receiving the initial linkage trajectory, the trajectory optimization module automatically analyzes the trajectory complexity using the optimization algorithm selection unit. Because the trajectory contains curved surfaces (with varying curvature) and pore systems (small radius inflection points), it is determined to be of medium to high complexity, and the genetic algorithm is matched and called (historical data shows that this algorithm has the best optimization effect on trajectories with multiple inflection points). Considering that aerospace parts require "high precision priority", the weight adjustment unit sets the weight coefficient of "motion accuracy" to be higher than 0.5 according to preset rules, and the weight coefficients of "motion efficiency" and "interaxial impact" are allocated proportionally. The multi-objective optimization unit uses "motion accuracy - motion efficiency - inter-axis impact" as the objective function and combines a genetic algorithm to iteratively optimize the initial trajectory: it corrects the displacement deviation of the trajectory in the hole system region, smooths the velocity connection of the trajectory in the curved surface region, and suppresses the impact at the inflection point of the four-axis linkage, and finally generates the target linkage trajectory.

[0078] 4. Multi-axis collaborative compensation and execution control The multi-axis collaborative compensation module establishes a signal connection with the condition monitoring module in advance. The displacement sensor (installed on each axis slider), speed sensor (installed on each axis motor), and vibration sensor (installed on the spindle box) of the condition monitoring module collect real-time data at a frequency of not less than 1kHz and transmit it to the multi-axis collaborative compensation module. The multi-axis collaborative compensation module calculates the cumulative error of each axis (such as the small displacement deviation of the X-axis due to load changes) based on real-time data, generates the error compensation amount, and transmits it to the trajectory optimization module so that the target trajectory incorporates error correction before the final output. After the execution control module receives the target linkage trajectory, the trajectory command conversion unit converts the trajectory data into pulse control commands that can be recognized by the XK2420 milling machine four-axis drive unit; The inter-axis synchronization control unit receives displacement data from the status monitoring module in real time, calibrates the motion displacement difference of the X-axis / Y-axis / Z-axis / W-axis, and ensures that the displacement difference of the four axes is controlled within the preset synchronization error range (such as ≤0.002mm) during linkage, so as to avoid the position deviation of the hole system due to the asynchrony between the axes.

[0079] 5. Processing execution and status monitoring The operator sends a "machining start" command to the execution control module through the human-machine interface module. The four-axis drive unit starts moving according to the target linkage trajectory, and the spindle starts cutting according to the process parameters. During the machining process, the human-machine interaction module displays three key pieces of information in real time: basic parameters of multi-axis motion (such as current feed rate and depth of cut), real-time execution progress of the target linkage trajectory (the proportion of surface / hole machining), and real-time data transmitted by the status monitoring module (displacement / velocity curves of each axis and vibration waveform of the spindle box). When machining reaches the bottom of the deep cavity, the vibration sensor detects a slight increase in vibration amplitude (not exceeding the threshold). The status monitoring module synchronously transmits the data to the trajectory optimization module and the human-machine interaction module: the trajectory optimization module does not need to adjust the trajectory, and the human-machine interaction module only prompts "vibration slightly increased", and the operator does not need to intervene; if the vibration exceeds the threshold, the system will automatically trigger a pause and wait for parameter adjustment.

[0080] 6. Post-processing parameter management After processing is completed, the data update unit of the parameter storage module automatically updates the key parameters of this optimization (such as the number of iterations of the genetic algorithm, the optimal weight coefficient of motion accuracy, and the multi-axis collaborative compensation amount) to the storage directory corresponding to "aluminum alloy workpiece - four-axis linkage"; At the same time, historical parameter versions of this optimization (such as initial weight coefficients and trajectory data before compensation) are retained to facilitate backtracking analysis should processing deviations occur in the future. Operators can export trajectory comparison data (deviation curve between initial trajectory and target trajectory) and status monitoring data (vibration / velocity statistics) for this processing through the human-machine interaction module for subsequent process summary.

[0081] III. Example Working Principle The working principle of this example fully follows the "closed-loop architecture" defined in the implementation example, with each module working together according to the logic of "data-driven - trajectory processing - execution feedback - parameter accumulation": 1. Data Layer: The data acquisition module comprehensively collects three core data categories: "workpiece-process-hardware". The parameter storage module provides historical data support to ensure the integrity and high reusability of the input data. 2. Trajectory Layer: The trajectory planning module uses the NURBS algorithm to generate an initial trajectory with appropriate accuracy. The trajectory optimization module achieves multi-objective optimization through "automatic algorithm selection + weight adjustment" and incorporates real-time error correction from the multi-axis collaborative compensation module to ensure trajectory accuracy. 3. Execution Layer: The execution control module translates the optimized trajectory into equipment actions through "command conversion + inter-axis synchronization," while the status monitoring module achieves "real-time monitoring and anomaly warning" through high-frequency data acquisition to avoid execution deviations; 4. Interaction and Data Accumulation Layer: The human-computer interaction module realizes "visual operation + manual intervention", and the parameter storage module updates the optimal parameters after processing, providing data accumulation for subsequent similar processing, forming a closed loop of "one-time optimization - multiple reuses".

[0082] IV. Example of technical effect 1. High-precision machining requirements are met: By combining the solutions of "NURBS interpolation accuracy adjustment (densification of nodes in the hole system area) + multi-objective optimization (prioritizing high precision weight) + multi-axis collaborative compensation (real-time correction of cumulative error)," the tolerance of the workpiece hole system is stably controlled within the required range, and the surface flatness of the curved surface is significantly improved, solving the problems of "unsatisfactory hole system accuracy and uneven curved surface connection" in traditional systems. 2. Balance between processing efficiency and equipment protection: The genetic algorithm with unit matching is selected to optimize the algorithm, which ensures high precision while avoiding excessive time for trajectory optimization; the inter-axis synchronous control and shock suppression make the movement at the inflection point of the four-axis linkage smoother and reduce the vibration amplitude of the spindle box, which reduces processing time and avoids wear and tear on the equipment caused by excessive impact. 3. Improved ease of operation and adaptability: The reuse of historical data in the parameter storage module reduces parameter setting time by more than 70%, and the algorithm automatically selects parameters without the need for operator judgment, enabling even less experienced operators to complete the processing of complex workpieces; at the same time, the weight adjustment unit supports switching between "high precision / high efficiency", and the weight can be quickly adjusted to adapt to different needs when processing ordinary aluminum alloy workpieces. 4. Processing stability assurance: The high-frequency data acquisition of the status monitoring module and the real-time display of the human-machine interaction module enable operators to keep abreast of the equipment status and avoid the escalation of anomalies caused by "information opacity"; when the vibration at the bottom of the deep cavity increased slightly during this processing, the system achieved "uninterrupted stable operation" through data feedback, proving its ability to dynamically control the processing process.

[0083] V. Experimental Data (Comparison with Traditional Systems) To verify the effectiveness of this system, using the same XK2420 milling machine and the same aluminum alloy integral frame workpiece, comparative experiments were conducted using both the "this system" and the "traditional unoptimized system." The experimental conditions were identical (same operator, same testing equipment: coordinate measuring machine + vibration analyzer). The data are as follows:

[0084] Note: The experimental data are the average of three repeated processing steps. The accuracy of the testing equipment meets the national metrological standards, and the data are reproducible.

[0085] The above are merely preferred embodiments of the present invention and are not intended to limit the implementation methods and protection scope of the present invention. Those skilled in the art should recognize that any equivalent substitutions and obvious changes made based on the description and illustrations of the present invention should be included within the protection scope of the present invention.

Claims

1. A multi-axis linkage trajectory optimization system for a CNC gantry milling machine, characterized in that, It includes a data acquisition module, a trajectory planning module, a trajectory optimization module, an execution control module, a status monitoring module, and a parameter storage module; the output of the data acquisition module is connected to the input of the trajectory planning module, and is used to transmit the acquired multi-axis motion basic parameters of the CNC gantry milling machine to the trajectory planning module; the output of the trajectory planning module is connected to the input of the trajectory optimization module, and is used to generate an initial linkage trajectory based on the multi-axis motion basic parameters and transmit it to the trajectory optimization module. The output of the trajectory optimization module is signal-connected to the input of the execution control module, and is used to optimize the initial linkage trajectory to generate the target linkage trajectory and transmit it to the execution control module; the execution control module is signal-connected to the multi-axis drive unit of the CNC gantry milling machine, and is used to control the movement of the multi-axis drive unit according to the target linkage trajectory; The output of the state monitoring module is connected to the trajectory optimization module and the execution control module respectively, and is used to collect real-time state data of multi-axis motion and transmit it to the trajectory optimization module and the execution control module respectively; the output of the parameter storage module is connected to the data acquisition module, the trajectory planning module and the trajectory optimization module respectively, and is used to store the basic parameters of multi-axis motion, the trajectory planning algorithm parameters and the trajectory optimization evaluation parameters.

2. The CNC gantry milling machine multi-axis linkage trajectory optimization system according to claim 1, characterized in that, The data acquisition module includes a workpiece model import unit, a machining process parameter input unit, and a multi-axis hardware parameter acquisition unit. The workpiece model import unit is used to import three-dimensional model data of the workpiece. The machining process parameter input unit is used to input cutting speed, feed rate, and depth of cut parameters. The multi-axis hardware parameter acquisition unit is used to acquire the travel, maximum speed, and acceleration parameters of each axis. The outputs of the workpiece model import unit, the machining process parameter input unit, and the multi-axis hardware parameter acquisition unit are all connected to the total output of the data acquisition module.

3. The CNC gantry milling machine multi-axis linkage trajectory optimization system according to claim 1 or 2, characterized in that, The trajectory planning module uses the NURBS curve interpolation algorithm to generate the initial linkage trajectory; the trajectory planning module is equipped with an interpolation accuracy adjustment unit, which is used to adjust the interpolation node density of the NURBS curve according to the workpiece machining accuracy requirements, and the interpolation node density is positively correlated with the machining accuracy requirements.

4. The CNC gantry milling machine multi-axis linkage trajectory optimization system according to claim 1, characterized in that, The trajectory optimization module includes a multi-objective optimization unit and an optimization algorithm selection unit. The multi-objective optimization unit constructs an objective function with trajectory motion accuracy, motion efficiency, and inter-axis impact as optimization objectives. The optimization algorithm selection unit incorporates a genetic algorithm, a particle swarm optimization algorithm, and a simulated annealing algorithm, and can automatically select a matching optimization algorithm based on the complexity of the initial linkage trajectory. The output of the optimization algorithm selection unit is connected to the input of the multi-objective optimization unit to transmit the selected optimization algorithm to the multi-objective optimization unit for trajectory optimization calculation.

5. The CNC gantry milling machine multi-axis linkage trajectory optimization system according to claim 1, characterized in that, The execution control module includes a trajectory command conversion unit and an inter-axis synchronization control unit. The trajectory command conversion unit is used to convert the target linkage trajectory into pulse control commands that can be recognized by the multi-axis drive unit. The inter-axis synchronization control unit is used to calibrate the motion displacement difference of each axis in real time, so that the motion displacement difference of each axis is controlled within a preset synchronization error range. The output terminal of the trajectory command conversion unit is connected to the input terminal of the inter-axis synchronization control unit, and the output terminal of the inter-axis synchronization control unit is connected to the multi-axis drive unit.

6. The CNC gantry milling machine multi-axis linkage trajectory optimization system according to claim 1, characterized in that, The status monitoring module includes a displacement sensor, a velocity sensor, and a vibration sensor; the displacement sensor is used to collect real-time displacement data of each axis, the velocity sensor is used to collect real-time velocity data of each axis, and the vibration sensor is used to collect equipment vibration data during multi-axis linkage; the output terminals of the displacement sensor, velocity sensor, and vibration sensor are all connected to the total output terminal of the status monitoring module, and the real-time status data transmission frequency is not less than 1kHz.

7. The CNC gantry milling machine multi-axis linkage trajectory optimization system according to claim 1, characterized in that, The parameter storage module includes a data classification storage unit and a data update unit; the data classification storage unit stores multi-axis motion basic parameters, trajectory planning algorithm parameters and trajectory optimization evaluation parameters in separate directories. The data update unit is used to update the optimal parameters generated during each trajectory optimization to the corresponding storage directory after each optimization is completed, and to retain historical parameter versions for backtracking.

8. The CNC gantry milling machine multi-axis linkage trajectory optimization system according to claim 4, characterized in that, The multi-objective optimization unit has a built-in weight adjustment unit; the weight adjustment unit is used to adjust the optimization weights of motion accuracy, motion efficiency and inter-axis impact according to the processing requirements; when the processing requirement is high precision priority, the weight coefficient of motion accuracy is not less than 0.5; when the processing requirement is high efficiency priority, the weight coefficient of motion efficiency is not less than 0.

5.

9. The CNC gantry milling machine multi-axis linkage trajectory optimization system according to claim 1, characterized in that, It also includes a multi-axis collaborative compensation module; the input end of the multi-axis collaborative compensation module is connected to the output end of the state monitoring module, and the output end is connected to the input end of the trajectory optimization module; the multi-axis collaborative compensation module is used to calculate the cumulative error of each axis based on the real-time state data of multi-axis motion, and generate error compensation amount to be transmitted to the trajectory optimization module, so that the trajectory optimization module incorporates the error compensation amount in the optimization process.

10. The CNC gantry milling machine multi-axis linkage trajectory optimization system according to claim 1, characterized in that, It also includes a human-computer interaction module; the input end of the human-computer interaction module is connected to the data acquisition module, the trajectory optimization module and the status monitoring module respectively, and is used to receive and display the basic parameters of multi-axis motion, the target linkage trajectory and the real-time status data of multi-axis motion; the output end of the human-computer interaction module is connected to the execution control module, and is used to receive the motion start and stop commands and parameter adjustment commands input by the user and transmit them to the execution control module.

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