Pilot test verification and evaluation method and system for process adaptability of aviation structural part processing machine tool

Abstract

The process adaptability pilot test verification evaluation method and system for the aviation structural part machining machine tool comprises the steps that the comprehensive geometric error, the motion linkage error and the machining process dynamic error of the machine tool are obtained, and a comprehensive precision evaluation model of the machine tool is established; based on a comprehensive precision evaluation model, processing efficiency adaptability evaluation is carried out on the machine tool; establishing a thermal characteristic model of the machine tool through heat source analysis, temperature field monitoring and thermally induced error modeling; establishing a resonance characteristic model of the machine tool through modal test of the whole machine and key parts and resonance characteristic evolution analysis in a processing space; and performing comprehensive process adaptability evaluation on the machine tool by combining the comprehensive precision evaluation model, the thermal characteristic model of the machine tool and the resonance characteristic model of the machine tool, and performing process adaptability pilot test verification on the machine tool based on an evaluation result.

Description

Technical Field

[0001] This invention relates to the field of CNC machine tool performance evaluation technology, and in particular to a method and system for experimental verification and evaluation of the process adaptability of machine tools for processing aerospace structural parts. Background Technology

[0002] Aerospace structural components are characterized by complex structures, difficult-to-machine materials, high precision requirements, and long processing cycles, placing extremely high demands on the process adaptability of machining equipment. Currently, performance evaluation of CNC machine tools largely relies on international or industry standards (such as the ISO 10791 series standards and GB / T 20957.7). These standards primarily focus on verifying individual static performance aspects, such as geometric accuracy, positioning accuracy, and repeatability. Furthermore, existing research and practice often employ methods such as cutting tests, vibration tests, and temperature rise tests to evaluate specific performance characteristics of machine tools.

[0003] However, these existing evaluation methods reveal the following significant shortcomings when applied to the manufacturing of aerospace structural components: 1. Limited evaluation dimensions and lack of systematic coupling analysis: Existing methods often test only one aspect of accuracy, efficiency, temperature rise, or vibration in isolation, failing to establish a correlation model between multiple performance indicators. For example, when evaluating accuracy, thermal deformation caused by cutting heat is not considered, and when evaluating efficiency, the impact of chatter on surface quality is not considered. This "divide and conquer" evaluation approach cannot reflect the comprehensive adaptability of machine tools under real machining conditions with multi-physics coupling and multiple constraints.

[0004] 2. The testing conditions are severely out of sync with real-world operating conditions: Current standards often involve precision testing under no-load, low-speed, and cold conditions, using test pieces (such as standard specimens) with simple geometry and light cutting loads. This differs significantly from the complex dynamic conditions encountered in aerospace structural component machining, which involve large overhangs, multi-axis linkages, heavy cutting, and long-term continuous operation. Consequently, the evaluation results cannot effectively predict the machine tool's performance in actual production.

[0005] 3. Emphasis on static and result evaluation, neglecting dynamic and process characteristics: Existing methods mostly focus on post-processing result indicators (such as workpiece dimensional accuracy and surface roughness) or the static characteristics of machine tools (such as static stiffness), while lacking a systematic evaluation of the dynamic characteristics of the machining process. For example, there is a lack of effective online monitoring and quantitative evaluation methods for key dynamic processes such as the generation and transmission mechanism of multi-axis linkage errors, the evolution law of process system dynamics in the machining space, and the accuracy drift trajectory of the thermal equilibrium process.

[0006] 4. Lack of a process-oriented adaptability evaluation index system: Existing evaluation systems are essentially verifications of the inherent capabilities of machine tools, rather than assessments of their adaptability to complete specific process tasks. They fail to incorporate constraints such as the specific structural characteristics of aerospace components, material machinability, and typical process routes into the evaluation model, resulting in weak correlation between the evaluation results and the core issue of "whether specific parts can be machined with high quality and efficiency."

[0007] 5. Evaluation results are difficult to directly guide process optimization and production decisions: Due to the above shortcomings, existing evaluation reports can usually only give a conclusion on whether the machine tool is "qualified" or a single performance parameter. They cannot answer questions that urgently need to be addressed in production practice, such as "which type of structural parts is this machine tool most suitable for processing", "under what process parameters can the best balance between accuracy and efficiency be achieved", and "where is its performance boundary". The engineering practical value of the evaluation results is limited. Summary of the Invention

[0008] The purpose of this invention is to provide a method and system for experimental verification and evaluation of the process adaptability of machine tools for processing aerospace structural components, so as to solve the above-mentioned problems.

[0009] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for experimental verification and evaluation of the process adaptability of machine tools for machining aerospace structural components, including: To obtain the comprehensive geometric error, motion linkage error, and dynamic error of the machining process of the machine tool, and to establish a comprehensive accuracy evaluation model for the machine tool; Based on the comprehensive accuracy evaluation model, the machining efficiency adaptability of the machine tool is evaluated. Through calibration of machine tool dynamic parameters and material cutting force coefficients, modeling of multi-constraint limit boundaries, and verification of typical feature machining, the machining capability boundary of the machine tool under the premise of ensuring machining quality is determined. A thermal characteristic model of the machine tool is established through heat source analysis, temperature field monitoring, and thermal error modeling. A resonance characteristic model of the machine tool is established through modal testing of the whole machine and key components and analysis of the evolution of resonance characteristics in the machining space. By combining the comprehensive accuracy evaluation model, the thermal characteristic model of the machine tool, and the resonance characteristic model of the machine tool, a comprehensive process adaptability evaluation of the machine tool is conducted, and the process adaptability of the machine tool is verified in pilot tests based on the evaluation results.

[0010] Furthermore, the acquisition of the machine tool's comprehensive geometric error, motion linkage error, and machining process dynamic error includes: Machine tool foundation geometric error measurement Preheat the machine tool to a stable state in a temperature-controlled workshop; Linear axis error measurement: Using a laser interferometer, measurements are taken at equally spaced points along the travel distance, and the deviation between the commanded position and the actual position is recorded; the unidirectional positioning error is calculated. and back clearance ; Straightness error: Using the straightness optical assembly of a laser interferometer, the measurement axis is horizontal. and vertical Straightness deviation in direction; Angular error: Measure the roll of the shaft using an electronic level or autocollimator. , up and down sway error; Angle positioning error: Use a high-precision angle encoder or a ball bar with angle measurement to measure the deviation between the commanded angle and the actual angle; Radial and axial errors: Using a ballbar, the center of the ballbar is mounted on the center line of the rotating axis. The rotating axis moves in a circular motion, and the radial runout is analyzed by reading the ballbar. and axial movement ; Enter the measurement results of each individual geometric error into the database; Based on multibody system theory, an error matrix containing six geometric error components is established for each motion axis. ; The geometric error vector at a point in space can be represented as the propagated synthesis of errors along each axis:

[0011] in, For the first The Jacobian matrix of the error from axis error to tool-workpiece contact point. This is the 6-term geometric error vector for this axis; Multi-axis linkage error modeling and testing Use high-performance dynamic measurement equipment to collect the actual spatial trajectory of the tool center point or spindle nose during the linkage process in real time. Calculate the linkage error for each sampling point ; Based on the established geometric error matrices of each axis, a comprehensive error propagation model for the machine tool is constructed:

[0012] in, The ideal motion transformation matrix; The model-predicted spatial distribution of errors is compared and verified with the measured linkage errors to identify and quantify the main sources of error coupling; a spatial distribution cloud map of linkage errors within the machine tool workspace is generated. Dynamic error monitoring during processing Install triaxial acceleration sensors in the spindle bearing housing, worktable, and workpiece clamping position; install vibration / force sensors inside the tool or spindle; Cutting tests were conducted on typical features of aerospace structural components, and vibration signals were recorded under different cutting parameters. Time-frequency analysis is performed on the collected vibration signals to identify characteristic frequencies related to machine tool modal frequencies or cutting chatter. Measure the surface roughness and contour error of the processed specimen, especially in areas with obvious vibration marks; Establish a correlation model between vibration acceleration / displacement amplitude and machining surface error, and obtain the relationship spectrum of "cutting parameters-vibration level-surface quality" for key processes.

[0013] Furthermore, the establishment of the comprehensive accuracy evaluation model for the machine tool includes: The results of the first three stages are integrated to establish a final comprehensive accuracy evaluation model; this model can predict the accuracy of a given machine tool motion command and cutting parameters. The following is the overall error:

[0014] Based on the specific process requirements of aerospace structural components, geometric errors are considered. Linkage error Vibration error Assign weights and calculate the comprehensive accuracy evaluation index. :

[0015] in, This is the normalization function; Will The value is compared with the accuracy tolerance of the target part; at the same time, the error composition is analyzed, the main factors limiting the machining accuracy of the machine tool are identified, and an "Accuracy Index Adaptability Evaluation Report" is generated.

[0016] Furthermore, based on the comprehensive accuracy evaluation model, the machine tool's machining efficiency adaptability is evaluated. This is achieved through calibration of machine tool dynamic parameters and material cutting force coefficients, modeling of multi-constraint limit boundaries, and verification of typical feature machining. The machining capability boundary of the machine tool is determined while ensuring machining quality, including: Machine tool dynamics parameter acquisition Modal testing was conducted to obtain the frequency response function (FRF) of the spindle-tool holder-tool assembly at a typical overhang length, and the frequencies of its main modes were identified. Damping ratio and modal stiffness ; Orthogonal cutting or oblique cutting tests were conducted using a universal force gauge or a force measuring platform mounted on a workbench; the cutting force components under different cutting parameters were measured. The cutting force coefficients in the tangential, radial, and axial directions were identified using a mechanical model. and plow shear force coefficient ; Calculation formula:

[0017]

[0018] Actual measurement of spindle power and torque characteristics The output torque was measured by gradually increasing the load at different spindle speeds. and power Record its overload capacity and continuous working characteristics; Multi-constraint limit boundary modeling and testing Cutting parameters can be modeled in space. Constraint modeling: Spindle power constraints: ,in Efficiency coefficient; Spindle torque constraint: , The diameter of the cutting tool; Cutting force / stiffness constraints: ,in The allowable amount of tool / workpiece deformation; Based on the cutting force model and various constraint inequalities, the three-dimensional boundary of the "cutting parameter reachable domain" is plotted through simulation calculation; Flutter stability region spectrum test Fixed axial depth of cut Below, at the spindle speed and radial depth A series of cutting tests were conducted using the variable as the basis; by monitoring vibration acceleration or acoustic emission signals, it was determined whether flutter occurred, and the results were plotted. The following is a "stability petal diagram"; Calculation formula:

[0019] in, It is the negative minimum of the real part of the frequency response function. It is the number of cutting teeth. It is force ratio Verification of the comprehensive efficiency of typical aerospace structural components Develop multi-objective optimization process schemes Using material removal rate (MRR) as the main efficiency indicator and cutting vibration amplitude and predicted cutting force as constraints, process parameters are optimized.

[0020] For regions with good rigidity, high efficiency parameters and high MRR are used; for regions with weak rigidity such as thin walls, conservative parameters that ensure stability are used. Data analysis and process adaptability evaluation By comparing the measured cutting force, power, and vibration with the model predictions, the model parameters are corrected to improve the prediction accuracy. Based on test data, an intuitive process selection guide is generated, clearly showing the optimal parameter range under different constraint priorities; Calculate the overall efficiency fitness index:

[0021] Outputs: "Machining efficiency-stability" capability boundary map, database of recommended process parameters for specific material-tool-feature combinations, and comprehensive evaluation report on machine tool machining efficiency adaptability.

[0022] Furthermore, the establishment of a thermal characteristic model of the machine tool through heat source analysis, temperature field monitoring, and thermally induced error modeling includes: Thermal error sensitive direction test During the temperature rise test, the following measurements were taken simultaneously: Spindle thermal drift: Install a standard test bar on the end face of the spindle and measure its radial thermal drift and axial thermal elongation in the X, Y, and Z directions; Positioning axis thermal error: Using a laser interferometer, the positioning error change of each linear axis during the temperature rise process is measured at intervals to separate the thermally induced error component; Geometric error thermal deformation: monitoring the temperature gradient of important basic components such as the machine bed and the resulting tilting and bending; Hotspot screening and verification Calculate the temperature sequence for each measurement point. thermal error sequences in each direction correlation coefficient ;

[0023] Select The 3-5 temperature measurement points with the highest values ​​are taken as the thermal key points corresponding to the thermal error components; Establishment of thermal error prediction model A thermal error prediction model is established using multiple linear regression (MLR) or artificial neural network (ANN). Multiple linear regression model:

[0024] in, Let be the temperature rise of the k-th thermal critical point relative to the reference time. The possible thermal hysteresis time constant, The regression coefficients are fitted using the least squares method; Thermal equilibrium process and steady-state performance evaluation 1) Determination of thermal equilibrium time The shorter the value, the faster the machine tool's thermal response and the shorter the preheating time. Thermal steady-state accuracy drift assessment After reaching thermal equilibrium, the steady-state values ​​of spindle thermal drift and thermally induced positioning errors of each axis are measured. ; Thermal stability evaluation index Under thermal equilibrium conditions, continue monitoring the thermal error over a period of time and calculate its standard deviation. ;

[0025] The smaller the value, the more stable the thermal accuracy; Comprehensive analysis and verification of thermal adaptability By integrating the distribution of key thermal points, thermal error model, thermal equilibrium time, steady-state drift, and thermal stability indicators, a complete "digital profile of thermal characteristics" of the machine tool is formed. The established thermal error model is input into the CNC system or offline programming software for compensation cutting verification; the machining accuracy of the same specimen before and after compensation is compared to verify the effectiveness of the model. The thermal adaptability of machine tools is classified according to thermal equilibrium time, steady-state drift, thermal stability index, and model prediction accuracy; thermal error prediction model parameters that can be embedded in control systems or process planning software are provided. The final output includes a comprehensive report on the machine tool's thermal characteristics, a list of key thermal points, a temperature-thermal error mapping model, thermal balance characteristic parameters, thermal adaptability rating, and process guidance suggestions.

[0026] Furthermore, the establishment of a resonance characteristic model for the machine tool through modal testing of the whole machine and key components, and analysis of the evolution of resonance characteristics within the machining space, includes: Obtain the low-order global modes of the machine tool in a free state or under installation conditions; Collect the excitation force and acceleration response signals of all measuring points, and calculate the frequency response function (FRF) matrix between each point; Using a multi-degree-of-freedom modal parameter identification algorithm, the first 10-15 main global modes of the machine tool in a typical configuration are identified from the FRF matrix; Based on natural frequency The resonant frequency of the i-th mode; Modal damping ratio Mode shape Modal stiffness With modal mass The process involves: generating a "machine tool whole machine modal model" that includes all the parameters mentioned above for the identified modes and generating animated mode shapes; compiling a "machine whole machine resonance frequency list" that is sorted from low to high frequency and labeled with the main mode shape descriptions corresponding to each frequency; Local modal and coupling path analysis of key components Dynamic characteristics test of the spindle system: In a static state, the end of the spindle with a standard tool holder clamped is excited by a force hammer, and the response is measured near the tool tip to obtain the independent radial and axial bending and torsional modal frequencies and damping of the spindle system; Modal testing of the workbench / fixture system involves exciting and responding to a typical simulated workpiece or fixture after clamping it; identifying the low-order natural frequencies of the workbench-fixture-workpiece combination system. Coupled path analysis is used to compare the mode shapes of the whole machine with those of the components to analyze the main vibration transmission paths and modes with large contributions at the tool-workpiece interface. The resonance characteristic evolution test in the machining space involves moving the spindle head or worktable to multiple predefined grid positions within the workspace, and repeating a simplified EMA test at each position, or using a working modal analysis method to identify modes through environmental or cutting stimuli. Data analysis and graph generation to track the natural frequencies of several key global modes. As the coordinate position changes, a "resonance zone distribution cloud map" is generated: using the spatial position as the plane coordinate and a certain modal frequency as the color or contour line, the distribution map of the mode is drawn in the entire processing space. Comprehensive analysis of resonance characteristics and evaluation of process adaptability, calculation of process characteristic frequencies: calculation of the tooth passage frequency corresponding to the spindle speed. And its frequency multiplier, as well as the possible servo drive frequency and ball screw passing frequency; The calculated process excitation frequency is compared with the "List of Resonance Frequency of the Whole Machine" and the "Local Resonance Frequency of the Spindle"; a risk threshold is set to identify the "Spindle Speed ​​Restricted Area" or "Feed Speed ​​Restricted Area" where there is a potential resonance risk; Damping level assessment and resonance sensitivity classification, based on modal damping ratio Sensitivity classification of resonance peaks; typically, It is a highly sensitive resonance; It is a medium-sensitive resonance; It is a low-sensitivity resonance; Comprehensive Adaptability Evaluation and Output Based on the resonance band density, lowest resonance frequency, and spatial consistency index, the "resonance characteristic adaptability" of machine tools is classified. The final output includes a complete digital profile of the machine tool's resonance characteristics, a risk assessment report directly related to the machining process, and vibration adaptability conclusions to guide the process planning of aerospace structural components.

[0027] Furthermore, by combining the comprehensive accuracy evaluation model, the machine tool's thermal characteristic model, and the machine tool's resonance characteristic model, a comprehensive process adaptability evaluation of the machine tool is conducted. Based on the evaluation results, pilot-scale verification of the machine tool's process adaptability is carried out, including: First, model integration and interactive analysis are conducted, placing the comprehensive accuracy evaluation model, processing efficiency capability boundary map, and thermal error prediction model on a unified data platform to analyze key coupling relationships. Second, comprehensive simulation and verification are established under a multi-dimensional constraint space. Based on the specific process requirements of the target aerospace structural component, virtual processing simulation is performed within the "accuracy-efficiency-thermal stability-vibration resistance" multi-dimensional constraint space constructed by the integrated model. The simulation process simulates the entire process of the machine tool from cold start-up, preheating, continuous processing to the completion of a typical part, dynamically predicting the accuracy performance, efficiency achievement rate, thermal deformation, and resonance risk at each stage. Finally, a quantitative comprehensive evaluation report and decision-making recommendations are generated. Based on the simulation and measured verification results, the comprehensive process adaptability index is calculated, and the advantages and bottlenecks of the machine tool capabilities are clearly identified, providing direct and quantitative decision-making basis for machine tool selection and acceptance, process parameter optimization, or adaptive improvement.

[0028] Secondly, the present invention provides a pilot-scale verification and evaluation system for the process adaptability of machine tools used for machining aerospace structural components, comprising: The first model construction module is used to obtain the machine tool's comprehensive geometric error, motion linkage error, and machining process dynamic error, and to establish a comprehensive accuracy evaluation model for the machine tool. Based on the comprehensive accuracy evaluation model, the machining efficiency adaptability of the machine tool is evaluated. Through calibration of machine tool dynamic parameters and material cutting force coefficients, modeling of multi-constraint limit boundaries, and verification of typical feature machining, the machining capability boundary of the machine tool under the premise of ensuring machining quality is determined. The second model building module is used to establish the thermal characteristic model of the machine tool through heat source analysis, temperature field monitoring, and thermal error modeling. The third model building module is used to establish a resonance characteristic model of the machine tool through modal testing of the whole machine and key components and analysis of the evolution of resonance characteristics in the machining space. The output module is used to combine the comprehensive accuracy evaluation model, the machine tool's thermal characteristic model, and the machine tool's resonance characteristic model to conduct a comprehensive process adaptability evaluation of the machine tool, and to conduct pilot-scale verification of the machine tool's process adaptability based on the evaluation results.

[0029] Thirdly, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the process adaptability test evaluation method for the aerospace structural component processing machine tool.

[0030] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the experimental verification and evaluation method for the process adaptability of the aerospace structural component processing machine tool.

[0031] Compared with the prior art, the present invention has the following technical effects: This invention is the first to place four key and interrelated dimensions of process adaptability—precision, efficiency, thermal stability, and vibration resistance—under a unified framework for comprehensive evaluation, overcoming the one-sidedness of traditional single-index evaluation.

[0032] This invention establishes a quantifiable evaluation method for each type of adaptability, which includes specific measurement schemes, mathematical models, and evaluation indicators, making the evaluation results objective and comparable.

[0033] The evaluation content of this invention is closely aligned with the actual processing constraints of aerospace structural components (such as complex structures, long processing cycles, and high precision requirements), and the pilot-scale verification process ensures that the evaluation results have guiding value for real production.

[0034] The evaluation system and testing methods developed in this invention can be directly used for machine tool selection, acceptance, process capability assessment, and processing parameter optimization in aerospace manufacturing enterprises, providing an effective technical tool for ensuring the processing quality and efficiency of aerospace structural components.

[0035] This evaluation system and testing method can provide a scientific, comprehensive, and reliable performance evaluation standard and practical guide for the research, development, procurement, application, and process optimization of special machine tools for aerospace structural parts. Attached Figure Description

[0036] Figure 1 This is a diagram illustrating the overall architecture of the process adaptability evaluation system in this invention. Figure 2 Flowchart for the accuracy index adaptability evaluation; Figure 3 Flowchart for processing efficiency adaptability evaluation; Figure 4 Flowchart for temperature change adaptability evaluation; Figure 5 This is a temperature-sensitive area for machine tools; Figure 6 This is a flowchart for vibration resistance evaluation. Detailed Implementation

[0037] The present invention will be further described below with reference to the accompanying drawings: Example 1, please refer to Figure 1 This invention provides a method for pilot-scale verification and evaluation of the process adaptability of machine tools for machining aerospace structural components, including: To obtain the comprehensive geometric error, motion linkage error, and dynamic error of the machining process of the machine tool, and to establish a comprehensive accuracy evaluation model for the machine tool; Based on the comprehensive accuracy evaluation model, the machining efficiency adaptability of the machine tool is evaluated. Through calibration of machine tool dynamic parameters and material cutting force coefficients, modeling of multi-constraint limit boundaries, and verification of typical feature machining, the machining capability boundary of the machine tool under the premise of ensuring machining quality is determined. A thermal characteristic model of the machine tool is established through heat source analysis, temperature field monitoring, and thermal error modeling. A resonance characteristic model of the machine tool is established through modal testing of the whole machine and key components and analysis of the evolution of resonance characteristics in the machining space. By combining the comprehensive accuracy evaluation model, the thermal characteristic model of the machine tool, and the resonance characteristic model of the machine tool, a comprehensive process adaptability evaluation of the machine tool is conducted, and the process adaptability of the machine tool is verified in pilot tests based on the evaluation results.

[0038] This invention can systematically and quantitatively evaluate the comprehensive process adaptability of machine tools under multi-dimensional constraints such as accuracy, efficiency, thermal stability and vibration resistance, and solves the problem that current evaluation methods are singular and one-sided, and cannot truly reflect the performance of machine tools under complex aerospace structural component machining conditions.

[0039] Example 2: This invention provides a pilot-scale verification and evaluation method for the process adaptability of machine tools used for machining aerospace structural components, including: 1. Precision Index Adaptability Evaluation Module: This module breaks through the limitations of traditional static geometric precision inspection, constructing a comprehensive precision evaluation model covering geometric errors, motion linkage errors, and dynamic errors in the machining process. It measures the machine tool's fundamental geometric errors using precision instruments, analyzes the error transmission and coupling laws in the multi-axis linkage process based on multi-body system theory, and introduces machining vibration monitoring to quantify the impact of dynamic disturbances on the final machining accuracy, thereby achieving a full-process, multi-factor evaluation of the machine tool's precision capability.

[0040] The accuracy index adaptability evaluation process follows the principle of "from basic to comprehensive, from static to dynamic" and is implemented in three stages. The specific process is as follows: Figure 2 As shown: Phase 1: Measurement of Machine Tool Foundation Geometric Errors Measurement preparation Laser interferometer, electronic level, ball bar, temperature sensor.

[0041] The process is carried out in a constant temperature workshop (20±1°C) and the machine tool is preheated to a stable state.

[0042] Based on standards such as ISO 230-1, write test programs for unidirectional motion of each axis.

[0043] Linear axis error measurement (taking the X-axis as an example) Positioning error: Using a laser interferometer, measurements are taken at equally spaced points along the travel path, and the deviation between the commanded position and the actual position is recorded. The unidirectional positioning error is calculated. and back clearance .

[0044] Straightness error: Using the straightness optical lens group of a laser interferometer, the measurement axis is horizontal ( ) and vertical ( () Straightness deviation in the direction.

[0045] Angular error: Measure the roll of the shaft using an electronic level or autocollimator. ), pitch ( ), sway ( )error.

[0046] Rotary axis error measurement (taking axis A as an example) Angle positioning error: Use a high-precision angle encoder or a ball bar with angle measurement to measure the deviation between the commanded angle and the actual angle.

[0047] Radial and axial errors: Using a ballbar, the center of the ballbar is installed on the center line of the rotating shaft. The rotating shaft moves in a circular motion, and the radial runout is analyzed by reading the ballbar. ) and axial movement ( ).

[0048] Error data synthesis The measurement results of each individual geometric error are entered into the database.

[0049] Based on multibody system theory, an error matrix containing six geometric error components is established for each motion axis. .

[0050] Calculation formula (example of single-item error synthesis - spatial error): The geometric error vector at a point in space can be represented as the propagation and synthesis of errors along each axis:

[0051] in, For the first The Jacobian matrix of the error from axis error to tool-workpiece contact point. This is the 6-term geometric error vector for this axis.

[0052] Output: Generate a geometric error map and database for machine tool foundations.

[0053] Phase Two: Multi-axis Linkage Error Modeling and Testing 1) Theoretical trajectory planning: Design complex multi-axis linkage test trajectories (such as NAS979 standard truncated cone test) that include typical aerospace structural features such as straight lines, circular arcs, and spatial spirals.

[0054] 2) Acquisition of actual motion trajectory: Use high-performance dynamic measurement equipment (such as laser tracker, high-speed ball bar) to acquire the actual spatial trajectory of the tool center point or spindle nose during the linkage process in real time.

[0055] 3) Calculation and propagation analysis of linkage error Calculate the linkage error for each sampling point .

[0056] Based on the geometric error matrices of each axis established in the first stage, a comprehensive error propagation model for the machine tool is constructed:

[0057] in, It is the ideal motion transformation matrix.

[0058] The model's predicted error spatial distribution is compared and verified with the measured linkage error to identify and quantify the main sources of error coupling.

[0059] Generate a spatial distribution cloud map of linkage error within the machine tool's workspace.

[0060] Phase 3: Monitoring of dynamic errors (vibration errors) during the machining process 1) Sensor arrangement: Install triaxial acceleration sensors in the spindle bearing housing, worktable, and workpiece clamping position; install vibration / force sensors (if applicable) inside the tool or spindle.

[0061] 2) Typical process cutting test: Select typical features of aerospace structural parts (such as deep cavity, thin wall, corner) for cutting test and record vibration signals under different cutting parameters.

[0062] Vibration error analysis and modeling Time-frequency analysis (FFT, wavelet transform) is performed on the collected vibration signals to identify characteristic frequencies related to machine tool modal frequencies or cutting chatter.

[0063] Measure the surface roughness and contour error of the processed specimen, especially in areas with obvious vibration marks.

[0064] Establish the relationship between vibration acceleration / displacement amplitude and machining surface error (such as roughness Ra, profile deviation). The association model of ).

[0065] Obtain the relationship map of "cutting parameters-vibration level-surface quality" for key processes.

[0066] Phase 4: Construction of Comprehensive Accuracy Evaluation Model and Determination of Process Adaptability 1) Model Integration: Integrate the results of the first three stages to establish a final comprehensive accuracy evaluation model. This model can predict the accuracy of a given machine tool motion command and cutting parameters. The following is the overall error:

[0067] Weighting and Evaluation: Based on the specific process requirements of aerospace structural components, geometric errors are assigned... Linkage error Vibration error Assign weights and calculate the comprehensive accuracy evaluation index. :

[0068] in, This is the normalization function.

[0069] 2) Process adaptability determination: The values ​​are compared with the accuracy tolerance of the target part. At the same time, the error composition is analyzed to identify the main factors limiting the machining accuracy of the machine tool (such as whether the positioning error of a certain axis is dominant, or whether the vibration error surges in the high-speed linkage zone), and a "Accuracy Index Adaptability Evaluation Report" is generated to provide a direct decision-making basis for machine tool selection, process optimization, or error compensation.

[0070] The final output includes a comprehensive machine tool accuracy evaluation model, a key error source analysis report, and conclusions on the accuracy and process adaptability for machining target aerospace structural components.

[0071] 2. Machining Efficiency Adaptability Evaluation Module: This module does not simply pursue the maximum material removal rate, but rather addresses the "complex structure and numerous constraints" characteristics of aerospace structural components by establishing a machining efficiency evaluation system under multiple constraint conditions. This system comprehensively considers the specific structural characteristics of the aerospace structural components, the achievable space of cutting parameters determined by the dynamics of the machine tool-tool-workpiece system, the physical limitations of spindle power and torque, and the cutting stability boundary, thereby evaluating the machine tool's ability to achieve high-efficiency machining under safe, stable, and reliable conditions.

[0072] This assessment follows the logic of "from single-factor capability calibration to multi-constraint coupling analysis, and finally verification through typical features," and is implemented in three core stages, such as... Figure 3 As shown, the specific process is as follows: Phase 1: Calibration of Machine Tool Basic Performance and Cutting Force Coefficient Machine tool dynamics parameter acquisition This provides foundational data for subsequent stability analysis.

[0073] Modal tests (impact method or vibratory exciter) are used to obtain the frequency response function (FRF) of the spindle-tool holder-tool assembly at a typical overhang length, and the frequencies of its main modes are identified. Damping ratio and modal stiffness .

[0074] Output tool tip frequency response function database.

[0075] Identification of cutting force coefficient of workpiece material Establish a cutting force prediction model for specific aerospace materials (such as Ti6Al4V, 7075 aluminum alloy, and high-strength steel).

[0076] Orthogonal or oblique cutting tests were conducted using a universal force gauge or a force-measuring platform mounted on a workbench. Different cutting parameters (cutting speed) were measured. Feed , depth of cut The cutting force component under () The mechanical model was used to identify the cutting force coefficients in the tangential, radial, and axial directions. and plow shear force coefficient .

[0077] Calculation formula (using oblique cutting as an example for a simplified model):

[0078]

[0079] Output the target material's cutting force coefficient library.

[0080] Actual measurement of spindle power and torque characteristics Obtain the true power and torque output capability curves of the spindle, rather than relying solely on the rated values.

[0081] The output torque was measured by gradually increasing the load (such as using a brake) at different spindle speeds. and power Record its overload capacity and continuous working characteristics.

[0082] Output spindle and Characteristic curve graph.

[0083] Phase Two: Multi-Constraint Limit Boundary Modeling and Testing Cutting parameters can be modeled in space. In three-dimensional parameter space (rotation speed) Feed , depth of cut Within this area, define a safe processing zone that satisfies all hard constraints.

[0084] Constraint modeling: Spindle power constraints: ,in This is the efficiency coefficient.

[0085] Spindle torque constraint: , The diameter is the cutting tool.

[0086] Cutting force / stiffness constraints: ,in The allowable amount of tool / workpiece deformation.

[0087] Recommended parameters from machine tool / tool ​​manufacturers.

[0088] Method: Based on the cutting force model and various constraint inequalities, the three-dimensional boundary of the "cutting parameter reachable domain" is plotted through simulation calculation.

[0089] Output: A visualized 3D model of the "Safe Processing Window".

[0090] 2) Flutter stability region spectrum test Within the reachable space, further identify dynamically stable processing areas to avoid chatter.

[0091] Fixed axial depth of cut Below, at the spindle speed and radial depth A series of cutting tests were conducted, using vibration acceleration or acoustic emission signals as variables. The occurrence of flutter was determined by monitoring these signals, and the results were plotted. The "stability leaflet diagram" below.

[0092] Calculation formula (reference for stability limit prediction):

[0093] in, It is the negative minimum of the real part of the frequency response function. It is the number of cutting teeth. It is the force ratio. Actual measurements are used to verify and correct theoretical models.

[0094] Output a series of stability lobe diagrams under different tool-overhang combinations, and superimpose them into the reachable space model to form a "dynamically stable machining domain".

[0095] Phase 3: Verification of the comprehensive efficiency of typical aerospace structural components 1) Design a comprehensive specimen with typical characteristics Simulate key difficult-to-machine features of aerospace structural components (such as deep cavities, thin walls, high flanges, corners, etc.).

[0096] Design a specimen that incorporates all of the above-mentioned features, using the target aerospace material.

[0097] 2) Develop multi-objective optimized process schemes Within the "dynamically stable processing domain", parameters that balance efficiency, accuracy, and stability are selected for different features.

[0098] Using material removal rate (MRR) as the main efficiency indicator and cutting vibration amplitude and predicted cutting force as constraints, process parameters are optimized.

[0099]

[0100] High efficiency parameters (high MRR) are used for regions with good rigidity, while conservative parameters that ensure stability are used for regions with weak rigidity such as thin walls.

[0101] 3) Implement processing and full-process monitoring Monitoring items: actual spindle power / torque, vibration in all directions, temperature at critical locations, and machining time.

[0102] Evaluation items: dimensional accuracy, shape accuracy, surface quality (especially chatter marks), and tool wear of the machined specimen.

[0103] Phase 4: Data Analysis and Process Adaptability Evaluation 1) Model verification and correction: Compare the measured cutting force, power, and vibration with the model predictions to correct the model parameters and improve the prediction accuracy.

[0104] 2) Generate a "processing efficiency-stability-accuracy" trade-off chart: Based on test data, an intuitive process selection guide chart is generated, clearly showing the optimal parameter range under different constraint priorities.

[0105] 3) Calculate the overall efficiency fitness index (example):

[0106] This index comprehensively reflects the machine tool's ability to maximize efficiency while ensuring quality.

[0107] 4) Generate a process adaptability rating report: Provide the efficiency capability level of the machine tool for machining the target aerospace structural parts (e.g., high efficiency, medium efficiency, limited efficiency), and identify its limiting bottlenecks (e.g., insufficient power is the main cause, or insufficient low-speed torque, or poor dynamic stiffness and easy chatter). Finally, output a recommended process parameter package to provide direct input for actual production.

[0108] The final output includes a capability boundary map of "machining efficiency-stability", a database of recommended process parameters for specific material-tool-feature combinations, and a comprehensive evaluation report on the adaptability of machine tool machining efficiency.

[0109] 3. Temperature Change Adaptability Evaluation Module: This module addresses the combined effects of internal and external heat sources on the machine tool (such as spindle heating, guideway friction, ambient temperature fluctuations, and cutting heat), aiming to establish a quantitative mapping relationship between heat input and machining accuracy output. By establishing a temperature field-thermal deformation model and monitoring the thermal equilibrium process, it proposes indicators to evaluate the stability of the machine tool's thermal accuracy and the controllability of its thermal response, thereby assessing the machine tool's ability to maintain accuracy under different temperature environments and continuous operating conditions.

[0110] This evaluation follows a technical path of "heat source and temperature field characterization → thermal deformation and error modeling → thermal equilibrium process evaluation → comprehensive verification," aiming to comprehensively characterize the thermal behavior of machine tools. The specific process is as follows: Phase 1: Construction of Heat Source Analysis and Temperature Field Monitoring System Theoretical Analysis of Heat Source Identification and Key Temperature Measurement Points Internal heat sources: spindle motor and bearings, servo motors of each axis, ball screw pairs, guide rail friction pairs, hydraulic system, cooling system, etc.

[0111] External heat sources include: periodic fluctuations in workshop ambient temperature, local air conditioning vents, solar radiation, and heat radiation from nearby equipment.

[0112] Theoretical Analysis: Based on the thermal characteristic analysis of the machine tool structure, temperature-sensitive areas and key temperature measurement points were preliminarily identified, such as the spindle front bearing housing, spindle housing, lead screw and nut pair, lead screw support bearing, guide rail slider, and core area of ​​the bed. Figure 5 As shown.

[0113] 2) Deployment of distributed temperature sensing network Sensor selection and placement: Use high-precision temperature sensors such as PT100 or thermocouples, and place no fewer than 15-20 temperature measurement points at key points in theoretical analysis and at multiple locations such as the machine bed, column, and worktable. Simultaneously, place 1-2 ambient temperature monitoring points around the machine tool.

[0114] Data acquisition system: Build a synchronous, multi-channel temperature data acquisition system with a sampling frequency of not less than 1Hz.

[0115] 3) Standard temperature rise test and variable environment test No-load temperature rise test: After the machine tool is started from cold, the spindle runs at a stepped speed (e.g., 1000, 5000, 10000, 15000 rpm) for 30 minutes each, and each feed axis reciprocates at a medium speed. The temperature of all temperature measuring points and the radial and axial thermal drift of the spindle are continuously recorded (using a dial indicator or non-contact displacement sensor).

[0116] Load temperature rise test: Conduct typical cutting load tests (such as continuous end milling) and record the temperature field changes during the cutting process.

[0117] Ambient temperature fluctuation test (optional but important): Monitor the changes in temperature and accuracy of key parts of the machine tool under natural ambient temperature fluctuations (e.g., ±3°C) in a controlled environment chamber or during periods of significant day-night temperature difference.

[0118] Phase Two: Separation and Modeling of Thermally Induced Errors 1) Thermal error sensitive direction test The main thermal error components are separated and quantified.

[0119] During the temperature rise test, the following measurements were taken simultaneously: Spindle thermal drift: Install a standard test bar on the end face of the spindle to measure its radial thermal drift and axial thermal elongation in the X, Y, and Z directions.

[0120] Positioning axis thermal error: Using a laser interferometer, the positioning error change of each linear axis during the temperature rise process is measured at intervals to separate the thermally induced error components.

[0121] Geometric error thermal deformation: Monitor the temperature gradient of important basic components such as the bed and the resulting tilting, bending, etc.

[0122] 2) Screening and Validation of Thermal Key Points (TKPs) A few points with the highest correlation to thermal error were selected from numerous temperature measurement points to simplify the model.

[0123] Calculate the temperature sequence for each measurement point. thermal error sequences in each direction correlation coefficient .

[0124]

[0125] Select The 3-5 temperature measurement points with the highest values ​​(usually >0.8) are taken as the thermal key points corresponding to the thermal error components.

[0126] 3) Establishment of thermal error prediction model Model selection: Multiple linear regression (MLR) or artificial neural network (ANN) is used to establish a thermal error prediction model.

[0127] Multiple linear regression model (example, for Z-axis thermal error) ):

[0128] in, Let be the temperature rise of the k-th thermal critical point relative to the reference time. The possible thermal hysteresis time constant, The regression coefficients are fitted using the least squares method.

[0129] Model validation: Use another set of independent experimental data to validate the model's prediction accuracy, requiring the prediction residual (RMS) to be less than 1 / 3 to 1 / 5 of the target part's accuracy tolerance.

[0130] Phase 3: Thermal Equilibrium Process and Steady-State Performance Evaluation 1) Determination of thermal equilibrium time Definition: The time from cold start-up to when the temperature rise rate at each thermally critical point of the machine tool approaches zero (e.g., temperature change <0.1°C within 10 consecutive minutes), and the rate of change of the main thermal errors enters a stable threshold. .

[0131] evaluate: The shorter the time, the faster the machine tool's thermal response and the shorter the preheating time.

[0132] Thermal steady-state accuracy drift assessment Calculation: After reaching thermal equilibrium, measure the steady-state values ​​of spindle thermal drift and thermally induced positioning errors of each axis. .

[0133] Evaluation index: This value directly reflects the system accuracy loss of the machine tool under hot conditions and is one of the core indicators for evaluating thermal adaptability.

[0134] Thermal stability evaluation index The degree of fluctuation in the accuracy of a quantifiable machine tool after thermal equilibrium varies with time and operating conditions.

[0135] Under thermal equilibrium conditions, continue monitoring the thermal error over a period of time (e.g., 2 hours) and calculate its standard deviation. .

[0136]

[0137] The smaller the value, the more stable the thermal accuracy.

[0138] Phase 4: Comprehensive Analysis and Verification of Thermal Adaptability 1) Model integration and "thermal characteristic map" generation: Integrate the distribution of key thermal points, thermal error model, thermal equilibrium time, steady-state drift and thermal stability index to form a complete "digital profile of thermal characteristics" of the machine tool.

[0139] 2) Model-based compensation verification test: The established thermal error model is input into the CNC system (e.g., through external coordinate system offset) or offline programming software for compensation cutting verification. The machining accuracy of the same specimen before and after compensation is compared to verify the effectiveness of the model.

[0140] 3) Thermal adaptability rating and report output Rating: The thermal adaptability of machine tools is graded based on thermal equilibrium time, steady-state drift, thermal stability index, and model prediction accuracy (e.g., excellent / good / medium / poor).

[0141] Report content: Thermal characteristics conclusions: Identify the main sources of thermal error, the direction of thermal sensitivity, and the magnitude of their impact.

[0142] Practical advice: Provide specific preheating scheme suggestions (e.g., what spindle speed and how many minutes to run), the optimal time window for high-precision machining, and whether thermal error compensation is necessary.

[0143] Output model: Provides thermal error prediction model parameters that can be embedded in control systems or process planning software.

[0144] Final outputs: Comprehensive report on machine tool thermal characteristics, list of key thermal points and temperature-thermal error mapping model, thermal balance characteristic parameters, thermal adaptability rating and process guidance suggestions.

[0145] 4. Vibration Resistance Evaluation Module: This module goes beyond simple static stiffness testing, evaluating the vibration resistance performance of machine tools from a dynamic characteristics perspective. By testing the modal parameters of the entire machine tool, it analyzes the influence of each natural frequency and mode shape on the cutting process; and further studies the evolution of the dynamic characteristics of the process system (machine tool-tool-workpiece) at different positions within the machining space, thereby establishing a vibration resistance evaluation method based on the dynamic characteristics and spatial consistency of the machine tool to predict and avoid machining resonance.

[0146] This evaluation follows a progressive path of "whole machine modal frequency sweep → detailed analysis of local components → spatial distribution mapping → process excitation correlation" to comprehensively analyze the resonance characteristics of the machine tool, such as... Figure 6 As shown, the specific process is as follows: Phase 1: Machine Tool Modal Parameter Identification 1) Test preparation and measurement point planning Obtain the low-order global modes of the machine tool in its free state or under installation conditions.

[0147] Experimental Modal Analysis (EMA) was used.

[0148] Measurement point layout: Arrange no fewer than 30-50 measurement points on key structural parts such as the machine tool bed, column, spindle box, worktable, and slide to form a three-dimensional measurement point grid. Each measurement point is equipped with a triaxial acceleration sensor.

[0149] Excitation methods: Use a hammer for multi-point alternating excitation (single-point excitation, multi-point response), or use multiple exciters for multi-point sinusoidal frequency sweep excitation.

[0150] 2) Frequency response function measurement and global modal identification Data acquisition: Collect the excitation force and acceleration response signals of all measuring points, and calculate the frequency response function (FRF) matrix between each point.

[0151] Modal parameter extraction: Using multi-degree-of-freedom modal parameter identification algorithms (such as PolyMAX, least squares complex frequency domain method), the first 10-15 major global modes of the machine tool under typical configuration (such as spindle centering) are identified from the FRF matrix.

[0152] Key parameters: Natural frequency (Hz): The resonant frequency of the i-th mode.

[0153] Modal damping ratio The rate at which the vibration of this mode decays is key to assessing the sharpness of the resonance.

[0154] Modal vibration mode : Describes the relative vibration patterns of various points on the machine tool under this mode (such as the first-order bending of the column, the swaying of the worktable, the torsion of the whole machine, etc.).

[0155] Modal stiffness With modal mass :Depend on Related.

[0156] Output: A "machine tool whole machine modal model" is generated, containing all the above parameters for the identified modes, and animated mode shapes are produced. A "machine whole machine resonant frequency list" is generated, sorted from low to high frequency, and the main mode shape descriptions corresponding to each frequency are labeled.

[0157] Phase 2: Local Modal and Coupling Path Analysis of Key Components 1) Spindle system dynamic characteristic test Identify high-frequency local resonances in the spindle-tool holder assembly as an independent subsystem, as these resonances directly affect the cutting process.

[0158] With the device stationary, a hammer is used to excite the end of the spindle clamped with a standard tool holder, and the response is measured near the tool tip. The focus is on analyzing frequencies above 500Hz.

[0159] The output obtains independent radial and axial bending and torsional modal frequencies and damping of the spindle system.

[0160] 2) Modal testing of the workbench / fixture system Evaluating the dynamic characteristics of a workpiece clamping system reveals that its weak modes are often the cause of chatter during the machining of thin-walled parts.

[0161] After clamping a typical simulated workpiece or fixture, it is subjected to excitation and response tests.

[0162] Output the low-order natural frequency of the workbench-fixture-workpiece combination system.

[0163] 3) Coupling path analysis Objective: To analyze how the modes of local components are transmitted through the structure and coupled with the overall machine modes, thus affecting the relative vibration of the tool and workpiece.

[0164] Methods: By comparing the mode shapes of the whole machine with those of the components, we can analyze the main paths of vibration transmission and the modes with the largest contribution at the tool-workpiece interface.

[0165] Phase 3: Testing the Evolution of Resonance Characteristics within the Processing Space The study evaluates the natural frequency drift and mode shape changes caused by variations in structural boundary conditions when the machine tool's motion axis is in different positions.

[0166] Spatial Mesh Modal Testing Move the spindle head or table to multiple predefined grid positions (e.g., a 5x5 grid) within the workspace. At each position, repeat a simplified EMA test (e.g., fixed excitation point, moving response point), or use the Operating Modal Analysis (OMA) method to identify modes through environmental or cutting excitations.

[0167] Data Analysis and Map Generation Frequency drift analysis: tracking the natural frequencies of several key global modes (such as the weakest 1st and 2nd modes). As the coordinate position changes.

[0168] Generate a "resonance zone distribution cloud map": using spatial location as a plane coordinate and a certain modal frequency as color or contour line, draw a distribution map of it throughout the entire machining space. This visually displays the "soft spots" and "hard spots" of the machine tool's dynamic characteristics.

[0169] The output generates a "Machine Tool Dynamic Characteristics Spatial Variation Report," quantifying the maximum drift of the resonant frequency. For example: "The first-order bending mode frequency is lowest at 42Hz in the lower left corner of the processing space and highest at 48Hz in the upper right corner, with a drift of 6Hz." Phase 4: Comprehensive Analysis of Resonance Characteristics and Evaluation of Process Adaptability 1) Comparative analysis of "resonance frequency spectrum" and "process excitation frequency" The resonance characteristics of the machine tool are correlated with the excitation frequency present in actual machining to assess the resonance risk.

[0170] Calculate the characteristic frequency of the process: Calculate the pass frequency of the cutter teeth corresponding to the spindle speed. And its frequency multiplier, as well as the possible servo drive frequency, ball screw pass frequency, etc.

[0171] Risk matching: The calculated process excitation frequency is compared with the "List of Whole Machine Resonance Frequencies" and the "Local Resonance Frequencies of Spindle". A risk threshold is set (such as the excitation frequency falling within ±5% of the natural frequency), and "spindle speed forbidden zones" or "feed speed forbidden zones" with potential resonance risks are identified.

[0172] 2) Damping level assessment and resonance sensitivity grading Quantify the severity of resonances at each order.

[0173] Based on modal damping ratio Sensitivity classification of resonance peaks. Typically, It exhibits highly sensitive resonance (sharp, easily excited); It is a medium-sensitive resonance; It is a low-sensitivity resonance (smooth, with rapid energy dissipation).

[0174] 3) Comprehensive Adaptability Evaluation and Output Evaluation indicators: Resonance band density: The number of resonance peaks in a critical frequency band (e.g., 0-200Hz). An excessive number of resonance peaks with low damping indicates a complex dynamic design of the structure, making it prone to resonance.

[0175] Lowest resonant frequency: The frequency of the weakest mode of the entire machine. The higher this value, the better the dynamic stiffness of the machine tool.

[0176] Spatial consistency index: the maximum relative drift of the key modal frequency within the machining space. The smaller the exponent, the more stable the dynamic characteristics.

[0177] Adaptability rating and reporting output: Rating: Based on the above indicators, the machine tool's "resonance characteristic adaptability" is graded (e.g., excellent / good / attention / poor), and its main risk points are clearly pointed out (e.g., "There is a highly sensitive torsional resonance at 55Hz, and the cutting teeth should be avoided from passing through frequencies close to this value").

[0178] Core outputs: Comprehensive report on machine tool resonance characteristics: includes complete modal parameter tables, mode shape animations, and damping level assessments.

[0179] Process vibration damping guide: Provides a clear "speed / feed restricted area map" and "recommended stable machining parameter window".

[0180] Suggested improvements: For example, for high-sensitivity resonance, structural suggestions such as adding dampers, optimizing fixture stiffness, and adjusting component mass distribution are proposed.

[0181] Final outputs: a complete digital profile of machine tool resonance characteristics, a risk assessment report directly related to the machining process, and vibration resistance (resonance avoidance) adaptability conclusions to guide the process planning of aerospace structural components.

[0182] Example 3, the present invention provides like Figure 1 As shown, this evaluation system includes four core evaluation modules: accuracy index adaptability evaluation module, machining efficiency adaptability evaluation module, temperature change adaptability evaluation module, and vibration resistance evaluation module, as well as an integrated verification module. These modules work collaboratively to achieve process adaptability evaluation for seven types of high-end CNC machine tools through pilot-scale verification.

[0183] II. Accuracy Index Adaptability Evaluation Measurement method: Geometric error measurement: A laser interferometer is used to measure the positioning error and straightness error of the linear axis; an electronic level is used to measure the pitch angle and yaw angle errors; and a ball bar is used to measure the angular positioning error, radial error, and axial error of the rotating axis.

[0184] Multi-axis linkage error analysis: Based on multibody system theory, a machine tool error transmission chain model is established, and the linkage of each axis is driven by CNC program to collect the deviation between the actual motion trajectory and the theoretical trajectory.

[0185] Machining vibration error monitoring: Vibration sensors are placed in the tool-workpiece contact area to collect vibration signals during the cutting process, and the impact of vibration on accuracy is analyzed in combination with the surface morphology of the machined surface.

[0186] Calculation formula: Geometric error synthesis model:

[0187] in These are the geometric error components.

[0188] Linkage error propagation matrix:

[0189] in Let be the ideal transformation matrix. This is the error matrix.

[0190] Comprehensive accuracy evaluation indicators:

[0191] in For linkage error, For vibration error, These are the weighting coefficients.

[0192] III. Processing Efficiency Adaptability Evaluation Measurement method: Modeling of cutting parameters in the reachable space: Based on the machine tool dynamics model and the cutting force model, the operable range of parameters such as spindle speed, feed rate, and depth of cut is determined through a combination of simulation and experiment.

[0193] Cutting stability domain test: By combining cutting tests with vibration monitoring, stability lobe diagrams are plotted to identify flutter critical conditions.

[0194] Power and torque constraint monitoring: Real-time acquisition of spindle power and torque data to determine whether limits are exceeded.

[0195] Calculation formula: Boundary function of the cutting stability region:

[0196] Efficiency comprehensive evaluation function:

[0197] IV. Temperature Change Adaptability Evaluation Measurement method: Heat source identification and temperature measurement setup: Thermocouples or infrared thermometers are placed in multiple locations such as the spindle, guide rail, lead screw, and environment to monitor the temperature field distribution.

[0198] Thermal error modeling: Establish the temperature-thermal deformation mapping relationship through temperature rise experiments.

[0199] Thermal equilibrium time test: Record the time and accuracy change process of the machine tool from cold state to thermal steady state.

[0200] Calculation formula: Thermal error prediction model:

[0201] in The coefficient of thermal expansion is... For the temperature of the measuring point, This is a reference temperature.

[0202] Thermal stability evaluation indicators:

[0203] V. Vibration Resistance Evaluation Measurement method: Modal testing: The machine tool is excited by an impact hammer or vibrator, and the response of the acceleration sensor is collected. The modal parameters of the whole machine are identified by the frequency response function.

[0204] Vibration monitoring during machining: Vibration sensors are placed at multiple locations such as the cutting tool, workpiece, and worktable to collect vibration signals during machining.

[0205] Dynamic performance spatial distribution test: excitation-response test is carried out at different processing positions to analyze the changes in dynamic parameters.

[0206] Calculation formula: Modal frequency and damping ratio identification:

[0207] Comprehensive vibration resistance evaluation indicators:

[0208] in For the amplitude of each mode, This is the reference amplitude.

[0209] VI. Pilot-scale verification process Based on the evaluation results of the above four modules, actual machining tests of aerospace structural components were conducted on seven types of high-end CNC machine tools. Machining accuracy, efficiency, temperature response, and vibration data were recorded to form a comprehensive evaluation report on process adaptability.

[0210] In another embodiment of the present invention, a pilot-scale verification and evaluation system for the process adaptability of machine tools for machining aerospace structural components is provided. This system can be used to implement the aforementioned pilot-scale verification and evaluation method for the process adaptability of machine tools for machining aerospace structural components. Specifically, the system includes: The first model construction module is used to obtain the machine tool's comprehensive geometric error, motion linkage error, and machining process dynamic error, and to establish a comprehensive accuracy evaluation model for the machine tool. Based on the comprehensive accuracy evaluation model, the machining efficiency adaptability of the machine tool is evaluated. Through calibration of machine tool dynamic parameters and material cutting force coefficients, modeling of multi-constraint limit boundaries, and verification of typical feature machining, the machining capability boundary of the machine tool under the premise of ensuring machining quality is determined. The second model building module is used to establish the thermal characteristic model of the machine tool through heat source analysis, temperature field monitoring, and thermal error modeling. The third model building module is used to establish a resonance characteristic model of the machine tool through modal testing of the whole machine and key components and analysis of the evolution of resonance characteristics in the machining space. The output module is used to combine the comprehensive accuracy evaluation model, the machine tool's thermal characteristic model, and the machine tool's resonance characteristic model to conduct a comprehensive process adaptability evaluation of the machine tool, and to conduct pilot-scale verification of the machine tool's process adaptability based on the evaluation results.

[0211] The module division in this embodiment of the invention is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in the various embodiments of the invention can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0212] In another embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used in the operation of a process adaptability verification and evaluation method for aerospace structural component machining tools.

[0213] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the operating system of the terminal. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the experimental evaluation method for the process adaptability of aerospace structural component machining tools in the above embodiments.

[0214] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0215] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0216] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0217] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0218] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A test-and-evaluation method for the process adaptability of machine tools used in the machining of aerospace structural components, characterized in that, include: To obtain the comprehensive geometric error, motion linkage error, and dynamic error of the machining process of the machine tool, and to establish a comprehensive accuracy evaluation model for the machine tool; Based on the comprehensive accuracy evaluation model, the machining efficiency adaptability of the machine tool is evaluated. Through calibration of machine tool dynamic parameters and material cutting force coefficients, modeling of multi-constraint limit boundaries, and verification of typical feature machining, the machining capability boundary of the machine tool under the premise of ensuring machining quality is determined. A thermal characteristic model of the machine tool is established through heat source analysis, temperature field monitoring, and thermal error modeling. A resonance characteristic model of the machine tool is established through modal testing of the whole machine and key components and analysis of the evolution of resonance characteristics in the machining space. By combining the comprehensive accuracy evaluation model, the thermal characteristic model of the machine tool, and the resonance characteristic model of the machine tool, a comprehensive process adaptability evaluation of the machine tool is conducted, and the process adaptability of the machine tool is verified in pilot tests based on the evaluation results.

2. The experimental verification and evaluation method for the process adaptability of machine tools for machining aerospace structural components according to claim 1, characterized in that, The acquisition of the machine tool's comprehensive geometric error, motion linkage error, and machining process dynamic error includes: Machine tool foundation geometric error measurement Preheat the machine tool to a stable state in a temperature-controlled workshop; Linear axis error measurement: Using a laser interferometer, measurements are taken at equally spaced points along the travel distance, and the deviation between the commanded position and the actual position is recorded; the unidirectional positioning error is calculated. and back clearance ; Straightness error: Using the straightness optical assembly of a laser interferometer, the measurement axis is horizontal. and vertical Straightness deviation in direction; Angular error: Measure the roll of the shaft using an electronic level or autocollimator. , looking up sway error; Angle positioning error: Use a high-precision angle encoder or a ball bar with angle measurement to measure the deviation between the commanded angle and the actual angle; Radial and axial errors: Using a ballbar, the center of the ballbar is mounted on the center line of the rotating axis. The rotating axis moves in a circular motion, and the radial runout is analyzed by reading the ballbar. and axial movement ; Enter the measurement results of each individual geometric error into the database; Based on multibody system theory, an error matrix containing six geometric error components is established for each motion axis. ; The geometric error vector at a point in space can be represented as the propagated synthesis of errors along each axis: in, For the first The Jacobian matrix of the error from axis error to tool-workpiece contact point. This is the 6-term geometric error vector for this axis; Multi-axis linkage error modeling and testing Use high-performance dynamic measurement equipment to collect the actual spatial trajectory of the tool center point or spindle nose during the linkage process in real time. Calculate the linkage error for each sampling point ; Based on the established geometric error matrices of each axis, a comprehensive error propagation model for the machine tool is constructed: in, The ideal motion transformation matrix; The model-predicted spatial distribution of errors is compared and verified with the measured linkage errors to identify and quantify the main sources of error coupling; a spatial distribution cloud map of linkage errors within the machine tool workspace is generated. Dynamic error monitoring during processing Install triaxial acceleration sensors in the spindle bearing housing, worktable, and workpiece clamping position; install vibration / force sensors inside the tool or spindle; Cutting tests were conducted on typical features of aerospace structural components, and vibration signals were recorded under different cutting parameters. Time-frequency analysis is performed on the collected vibration signals to identify characteristic frequencies related to machine tool modal frequencies or cutting chatter. Measure the surface roughness and contour error of the processed specimen, especially in areas with obvious vibration marks; Establish a correlation model between vibration acceleration / displacement amplitude and machining surface error, and obtain the relationship spectrum of "cutting parameters-vibration level-surface quality" for key processes.

3. The experimental verification and evaluation method for the process adaptability of machine tools for machining aerospace structural components according to claim 2, characterized in that, The establishment of the comprehensive accuracy evaluation model for machine tools includes: The results of the first three stages are integrated to establish a final comprehensive accuracy evaluation model; this model can predict the accuracy of a given machine tool motion command and cutting parameters. The following is the overall error: Based on the specific process requirements of aerospace structural components, geometric errors are considered. Linkage error Vibration error Assign weights and calculate the comprehensive accuracy evaluation index. : in, This is the normalization function; Will The value is compared with the accuracy tolerance of the target part; at the same time, the error composition is analyzed, the main factors limiting the machining accuracy of the machine tool are identified, and a "Accuracy Index Adaptability Evaluation Report" is generated.

4. The experimental verification and evaluation method for the process adaptability of machine tools for machining aerospace structural components according to claim 1, characterized in that, The comprehensive accuracy evaluation model is used to evaluate the machining efficiency adaptability of the machine tool. Through calibration of machine tool dynamic parameters and material cutting force coefficients, modeling of multi-constraint limit boundaries, and verification of typical feature machining, the machining capability boundary of the machine tool under the premise of ensuring machining quality is determined, including: Machine tool dynamics parameter acquisition Modal testing was conducted to obtain the frequency response function (FRF) of the spindle-tool holder-tool assembly at a typical overhang length, and the frequencies of its main modes were identified. Damping ratio and modal stiffness ; Orthogonal cutting or oblique cutting tests were conducted using a universal force gauge or a force measuring platform mounted on a workbench; the cutting force components under different cutting parameters were measured. The cutting force coefficients in the tangential, radial, and axial directions were identified using a mechanical model. and plow shear force coefficient ; Calculation formula: Actual measurement of spindle power and torque characteristics The output torque was measured by gradually increasing the load at different spindle speeds. and power Record its overload capacity and continuous working characteristics; Multi-constraint limit boundary modeling and testing Cutting parameters can be modeled in space. Constraint modeling: Spindle power constraints: ,in Efficiency coefficient; Spindle torque constraint: , The diameter of the cutting tool; Cutting force / stiffness constraints: ,in Allowable tool / workpiece deformation; Based on the cutting force model and various constraint inequalities, the three-dimensional boundary of the "cutting parameter reachable domain" is plotted through simulation calculation; Flutter stability region spectrum test Fixed axial depth of cut Below, at the spindle speed and radial depth A series of cutting tests were conducted using the variable as the basis; by monitoring vibration acceleration or acoustic emission signals, it was determined whether flutter occurred, and the results were plotted. The following is a "stability petal diagram"; Calculation formula: in, It is the negative minimum of the real part of the frequency response function. It is the number of cutting teeth. It is force ratio Verification of the comprehensive efficiency of typical aerospace structural components Develop multi-objective optimization process schemes Using material removal rate (MRR) as the main efficiency indicator and cutting vibration amplitude and predicted cutting force as constraints, process parameters are optimized. For regions with good rigidity, high efficiency parameters and high MRR are used; for regions with weak rigidity such as thin walls, conservative parameters that ensure stability are used. Data analysis and process adaptability evaluation By comparing the measured cutting force, power, and vibration with the model predictions, the model parameters are corrected to improve the prediction accuracy. Based on test data, an intuitive process selection guide is generated, clearly showing the optimal parameter range under different constraint priorities; Calculate the overall efficiency fitness index: Output: "Machining efficiency-stability" capability boundary map, database of recommended process parameters for specific material-tool-feature combinations, and comprehensive evaluation report on machine tool machining efficiency adaptability.

5. The experimental verification and evaluation method for the process adaptability of machine tools for machining aerospace structural components according to claim 1, characterized in that, The process of establishing a thermal characteristic model of the machine tool through heat source analysis, temperature field monitoring, and thermal error modeling includes: Thermal error sensitive direction test During the temperature rise test, the following measurements were taken simultaneously: Spindle thermal drift: Install a standard test bar on the end face of the spindle and measure its radial thermal drift and axial thermal elongation in the X, Y, and Z directions; Positioning axis thermal error: Using a laser interferometer, the positioning error change of each linear axis during the temperature rise process is measured at intervals to separate the thermally induced error component; Geometric error thermal deformation: monitoring the temperature gradient of important basic components such as the machine bed and the resulting tilting and bending; Hotspot screening and verification Calculate the temperature sequence for each temperature measurement point. thermal error sequences in each direction correlation coefficient ; Select The 3-5 temperature measurement points with the highest values ​​are taken as the thermal key points corresponding to the thermal error components; Establishment of thermal error prediction model A thermal error prediction model is established using multiple linear regression (MLR) or artificial neural network (ANN). Multiple linear regression model: in, Let be the temperature rise of the k-th thermal critical point relative to the reference time. The possible thermal hysteresis time constant, The regression coefficients are fitted using the least squares method; Thermal equilibrium process and steady-state performance evaluation 1) Determination of thermal equilibrium time The shorter the value, the faster the machine tool's thermal response and the shorter the preheating time. Thermal steady-state accuracy drift assessment After reaching thermal equilibrium, the steady-state values ​​of spindle thermal drift and thermally induced positioning errors of each axis are measured. ; Thermal stability evaluation index Under thermal equilibrium conditions, continue monitoring the thermal error over a period of time and calculate its standard deviation. ; The smaller the value, the more stable the thermal accuracy; Comprehensive analysis and verification of thermal adaptability By integrating the distribution of key thermal points, thermal error model, thermal equilibrium time, steady-state drift, and thermal stability indicators, a complete "digital profile of thermal characteristics" of the machine tool is formed. The established thermal error model is input into the CNC system or offline programming software for compensation cutting verification; the machining accuracy of the same specimen before and after compensation is compared to verify the effectiveness of the model. The thermal adaptability of machine tools is classified according to thermal equilibrium time, steady-state drift, thermal stability index, and model prediction accuracy; thermal error prediction model parameters that can be embedded in control systems or process planning software are provided. The final output includes a comprehensive report on the machine tool's thermal characteristics, a list of key thermal points, a temperature-thermal error mapping model, thermal balance characteristic parameters, thermal adaptability rating, and process guidance suggestions.

6. The experimental verification and evaluation method for the process adaptability of machine tools for machining aerospace structural components according to claim 1, characterized in that, The establishment of a resonance characteristic model for the machine tool through modal testing of the whole machine and key components, and analysis of the evolution of resonance characteristics within the machining space, includes: Obtain the low-order global modes of the machine tool in a free state or under installation conditions; Collect the excitation force and acceleration response signals of all measuring points, and calculate the frequency response function (FRF) matrix between each point; Using a multi-degree-of-freedom modal parameter identification algorithm, the first 10-15 main global modes of the machine tool in a typical configuration are identified from the FRF matrix; Based on natural frequency The resonant frequency of the i-th mode; Modal damping ratio Mode shape Modal stiffness With modal mass The process involves: generating a "machine tool modal model" containing all the parameters of the identified modes and generating animated mode shapes; compiling a "machine resonance frequency list" sorted by frequency from low to high and labeling the main mode shape descriptions for each frequency. Local modal and coupling path analysis of key components Dynamic characteristics test of the spindle system: In a static state, the end of the spindle with a standard tool holder clamped is excited by a force hammer, and the response is measured near the tool tip to obtain the independent radial and axial bending and torsional modal frequencies and damping of the spindle system; Modal testing of the workbench / fixture system involves exciting and responding to typical simulated workpieces or fixtures after clamping them; identifying the low-order natural frequencies of the workbench-fixture-workpiece combination system. Coupled path analysis is used to compare the mode shapes of the whole machine with those of the components to analyze the main vibration transmission paths and modes with large contributions at the tool-workpiece interface. The resonance characteristic evolution test in the machining space involves moving the spindle head or worktable to multiple predefined grid positions within the workspace, and repeating a simplified EMA test at each position, or using a working modal analysis method to identify modes through environmental or cutting stimuli. Data analysis and graph generation to track the natural frequencies of several key global modes. As the coordinate position changes, a "resonance zone distribution cloud map" is generated: using the spatial position as the plane coordinate and a certain modal frequency as the color or contour line, the distribution map of the mode is drawn in the entire processing space. Comprehensive analysis of resonance characteristics and evaluation of process adaptability, calculation of process characteristic frequencies: calculation of the tooth passage frequency corresponding to the spindle speed. And its frequency multiplier, as well as the possible servo drive frequency and ball screw passing frequency; The calculated process excitation frequency is compared with the "List of Resonance Frequency of the Whole Machine" and the "Local Resonance Frequency of the Spindle"; a risk threshold is set to identify the "Spindle Speed ​​No-Go Zone" or "Feed Speed ​​No-Go Zone" where there is a potential resonance risk; Damping level assessment and resonance sensitivity classification, based on modal damping ratio Sensitivity classification of resonance peaks; typically, It is a highly sensitive resonance; For medium-sensitive resonance; It is a low-sensitivity resonance; Comprehensive Adaptability Evaluation and Output The "resonance characteristic adaptability" of machine tools is classified based on resonance band density, minimum resonance frequency, and spatial consistency index. The final output includes a complete digital profile of the machine tool's resonance characteristics, a risk assessment report directly related to the machining process, and vibration adaptability conclusions to guide the process planning of aerospace structural components.

7. The experimental verification and evaluation method for the process adaptability of machine tools for machining aerospace structural components according to claim 1, characterized in that, The method combines a comprehensive accuracy evaluation model, a machine tool thermal characteristic model, and a machine tool resonance characteristic model to conduct a comprehensive process adaptability evaluation of the machine tool. Based on the evaluation results, a pilot-scale verification of the machine tool's process adaptability is carried out, including: First, model integration and interactive analysis are conducted, placing the comprehensive accuracy evaluation model, machining efficiency capability boundary map, and thermal error prediction model on a unified data platform to analyze key coupling relationships. Second, comprehensive simulation and verification are established under a multi-dimensional constraint space. Based on the specific process requirements of the target aerospace structural component, virtual machining simulation is performed within the "accuracy-efficiency-thermal stability-vibration resistance" multi-dimensional constraint space constructed by the integrated model. The simulation process simulates the entire process of the machine tool from cold start-up, preheating, continuous machining to the completion of a typical part, dynamically predicting the accuracy performance, efficiency achievement rate, thermal deformation, and resonance risk at each stage. Finally, a quantitative comprehensive evaluation report and decision-making recommendations are generated. Based on the simulation and measured verification results, the comprehensive process adaptability index is calculated, and the advantages and bottlenecks of the machine tool capabilities are clearly identified, providing direct and quantitative decision-making basis for machine tool selection and acceptance, process parameter optimization, or adaptive improvement.

8. A pilot-scale verification and evaluation system for the process adaptability of machine tools for machining aerospace structural components, characterized in that, include: The first model construction module is used to obtain the machine tool's comprehensive geometric error, motion linkage error, and machining process dynamic error, and to establish a comprehensive accuracy evaluation model for the machine tool. Based on the comprehensive accuracy evaluation model, the machining efficiency adaptability of the machine tool is evaluated. Through calibration of machine tool dynamic parameters and material cutting force coefficients, modeling of multi-constraint limit boundaries, and verification of typical feature machining, the machining capability boundary of the machine tool under the premise of ensuring machining quality is determined. The second model building module is used to establish the thermal characteristic model of the machine tool through heat source analysis, temperature field monitoring, and thermal error modeling. The third model building module is used to establish a resonance characteristic model of the machine tool through modal testing of the whole machine and key components and analysis of the evolution of resonance characteristics in the machining space. The output module is used to combine the comprehensive accuracy evaluation model, the machine tool's thermal characteristic model, and the machine tool's resonance characteristic model to conduct a comprehensive process adaptability evaluation of the machine tool, and to conduct pilot-scale verification of the machine tool's process adaptability based on the evaluation results.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the experimental verification and evaluation method for the process adaptability of the aerospace structural component machining machine tool as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the experimental verification and evaluation method for the process adaptability of the aerospace structural component machining machine tool as described in any one of claims 1 to 7.

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