Simulation system for machining deformation compensation of thin-walled parts integrating residual stress prediction

Abstract

This invention discloses a simulation system for compensating cutting deformation of thin-walled parts by integrating residual stress prediction, belonging to the field of numerical simulation technology. This simulation system includes a stress analysis module, a path analysis module, a stress prediction module, and a path reconstruction module. The stress analysis module generates an initial residual stress dataset based on residual stress data; the path analysis module generates a set of path anomalies based on the initial residual stress dataset; the stress prediction module generates a stress evolution prediction set based on tool displacement curve data and the set of path anomalies; and the path reconstruction module generates an iterative cutting path set based on the stress evolution prediction set and the set of path anomalies. This invention, through an analysis mechanism that dynamically links stress acquisition with path direction, can improve the machining stability and geometric accuracy of thin-walled parts under complex stress fields.

Description

Technical Field

[0001] This invention relates to the field of numerical simulation technology, and specifically to a simulation system for compensating for cutting deformation of thin-walled parts by integrating residual stress prediction. Background Technology

[0002] Numerical simulation technology encompasses the modeling, solving, and visualization of various physical, mechanical, and thermal phenomena in a computational environment, and is an indispensable and crucial component of modern engineering design and manufacturing processes. Its core content includes finite element analysis, computational fluid dynamics, thermodynamic simulation, and multiphysics coupling calculations. The aim is to simulate the response behavior of products under actual operating conditions through virtual experiments, thereby predicting their performance and optimizing structural design and manufacturing processes. Numerical simulation is widely used in high-end manufacturing fields such as aerospace, automotive manufacturing, electronic packaging, and energy equipment. Particularly in materials processing and manufacturing precision control, it can be used to evaluate stress evolution, deformation trends, and residual stress accumulation during processing, providing a basis for product performance evaluation and process decision-making.

[0003] Among them, the simulation system for compensating cutting deformation of thin-walled parts by integrating residual stress prediction refers to a technical system based on numerical modeling and simulation calculation. It addresses the deformation problem of thin-walled structural parts during machining by introducing and coupling analysis of the residual stress field to design compensation paths. It mainly involves obtaining the initial residual stress of the workpiece, simulating the evolution of the stress field under cutting load, and predicting cutting deformation. Based on this, the cutting path is corrected according to the principle of reverse compensation.

[0004] While existing technologies cover multiple stages, including stress acquisition, finite element simulation, and path adjustment, significant shortcomings remain in data processing and path response mechanisms. The stress acquisition process primarily relies on static residual stress fields, lacking dynamic relationship modeling with the toolpath. This results in the inability to identify and partition stress disturbance sources early on, leading to a lack of proactive deformation trend avoidance mechanisms during the cutting path design phase. Furthermore, path adjustment largely depends on post-processing error correction, failing to incorporate stress evolution trends for coordinated optimization in the early stages of path generation. This results in delayed compensation strategies and limited adjustment ranges, impacting post-machining shape accuracy and stress balance. Taking typical bending deformation in material processing as an example, a significant mismatch between the path penetration direction and the principal stress direction can easily trigger abrupt local deformation, creating deformation errors that cannot be resolved through end-effector compensation. Overall, existing technologies lack the capability for dynamic prediction of stress evolution and synergy in path planning, limiting their stability under high-precision, complex load conditions. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide a simulation system for compensating cutting deformation of thin-walled parts that integrates residual stress prediction, in order to solve the technical problem that the existing technology is insufficient in terms of the synergy between dynamic prediction of stress evolution and path planning.

[0006] To achieve at least one of the above objectives, the present invention provides the following technical solution:

[0007] One embodiment of the present invention provides a simulation system for compensating cutting deformation of thin-walled parts by incorporating residual stress prediction, comprising:

[0008] The stress analysis module is used to collect residual stress data of thin-walled parts before cutting, obtain a stress distribution map based on the residual stress data, and obtain an initial dataset of residual stress based on the stress distribution map.

[0009] The path analysis module is used to obtain the path direction vector of the tool cutting and the initial dataset of residual stress, calculate the angle change rate based on the initial dataset of residual stress and the path direction vector, and obtain the path abnormal disturbance set based on the angle change rate.

[0010] The stress prediction module is used to acquire tool displacement curve data and the path abnormal disturbance set, perform finite element analysis calculations based on the tool displacement curve data and the path abnormal disturbance set to obtain the residual stress change, and obtain the stress evolution prediction set based on the residual stress change.

[0011] The path reconstruction module is used to obtain the stress evolution prediction set and the path anomaly perturbation set, perform path planning calculations based on the stress evolution prediction set and the path anomaly perturbation set to obtain a corrected path sequence, and obtain an iterative cutting path set based on the corrected path sequence.

[0012] The simulation system for compensating cutting deformation of thin-walled parts by incorporating residual stress prediction as described above, wherein the stress analysis module includes:

[0013] The stress detection submodule is used to collect residual stress data of thin-walled parts before cutting, and to perform preliminary calibration based on the residual stress data to obtain preliminary residual stress data.

[0014] The distribution map construction submodule is used to obtain the preliminary residual stress data and perform spatial mapping based on the preliminary residual stress data to obtain the stress distribution map;

[0015] The stress set generation submodule is used to obtain the stress distribution map, divide the grid region based on the stress distribution map and label the stress in each grid region, and integrate the stress data of all the grid regions to obtain the initial dataset of residual stress.

[0016] The simulation system for compensating cutting deformation of thin-walled parts by incorporating residual stress prediction as described above includes a stress detection submodule comprising a stress meter, which is used to collect stress values ​​at multiple locations of the thin-walled part before cutting.

[0017] The simulation system for thin-walled part cutting deformation compensation that integrates residual stress prediction as described above, wherein the path analysis module includes:

[0018] The path acquisition submodule is used to acquire the path trajectory data of the tool during the cutting process, obtain the start and end spatial coordinates and cutting time of each path segment based on the path trajectory data, obtain the path direction vector based on the start and end spatial coordinates, and obtain the path direction vector sequence based on the start and end spatial coordinates, the path direction vector and the cutting time.

[0019] The sequence construction submodule is used to obtain the initial dataset of residual stress and the path direction vector sequence, calculate the residual stress direction vector based on the initial dataset of residual stress, and calculate the angle change rate based on the path direction vector in the path direction vector sequence and the residual stress direction vector to obtain the path angle change rate.

[0020] The disturbance identification submodule is used to obtain the path angle change rate, filter out path segments whose change rate exceeds the angle change threshold based on the path angle change rate, and obtain a path abnormal disturbance set based on the filtered path segments.

[0021] In the thin-walled part cutting deformation compensation simulation system that integrates residual stress prediction as described above, the included angle change threshold is set based on the mean and standard deviation of the included angle change rate of all path segments.

[0022] The simulation system for thin-walled part cutting deformation compensation that integrates residual stress prediction as described above, wherein the stress prediction module includes:

[0023] The time matching submodule is used to acquire tool displacement curve data and the path abnormal disturbance set, and to obtain the disturbance time position sequence by comparing the tool displacement curve data and the path abnormal disturbance set.

[0024] The stress relief submodule is used to obtain the disturbance time location sequence, obtain the first node based on the disturbance time location sequence, and perform finite element analysis calculation based on the coordinates of the first node to obtain the residual stress change.

[0025] The trend calculation submodule is used to obtain the residual stress change, calculate the rate of change of stress release value between two adjacent path segments based on the residual stress change, and obtain the stress evolution prediction set based on the rate of change of stress release value.

[0026] The simulation system for thin-walled part cutting deformation compensation based on residual stress prediction, as described above, includes the following path reconstruction module:

[0027] The path fitting submodule is used to obtain the stress evolution prediction set and the path anomaly perturbation set, obtain the time series and spatial coordinates of the perturbation path segment based on the stress evolution prediction set and the path anomaly perturbation set, and calculate the time coordinate alignment based on the time series and the spatial coordinates to obtain the fitted path coordinate sequence.

[0028] The path correction submodule is used to obtain the fitted path coordinate sequence and the path anomaly perturbation set, calculate the spatial continuity deviation based on the fitted path coordinate sequence, perform path correction operation based on the path anomaly perturbation set and the spatial continuity deviation, and obtain the corrected path sequence based on the path correction operation.

[0029] The path update submodule is used to obtain the corrected path sequence, iteratively update the path coordinates based on the corrected path sequence, and adjust the direction of the cutting path of the tool to obtain an iterative cutting path set.

[0030] The simulation system for compensating cutting deformation of thin-walled parts based on residual stress prediction, as described above, further includes:

[0031] The compensation verification module is used to acquire tool trajectory data, the iterative cutting path set, and the stress evolution prediction set. Based on the tool trajectory data, the iterative cutting path set, and the stress evolution prediction set, a corrected cutting trajectory is obtained. The corrected cutting trajectory is input into the simulation space to complete the simulation-driven deformation compensation closed loop for thin-walled parts.

[0032] The simulation system for compensating cutting deformation of thin-walled parts based on residual stress prediction, as described above, includes a compensation verification module comprising:

[0033] The displacement trend superposition submodule is used to acquire tool trajectory data and the iterative cutting path set, obtain a displacement increment sequence based on the tool trajectory data and the iterative cutting path set, and perform cumulative trend superposition based on the displacement increment sequence to obtain the displacement trend superposition amount.

[0034] The path offset calculation submodule is used to obtain the displacement trend superposition amount and the iterative cutting path set, calculate the offset vector based on the displacement trend superposition amount and the iterative cutting path set, construct the offset projection relationship based on the offset vector, and obtain the cutting path offset value based on the offset vector projection.

[0035] The trajectory iteration submodule is used to obtain the cutting path offset value and the stress evolution prediction set, obtain the corrected cutting trajectory based on the cutting path offset value, the stress evolution prediction set and the preset scaling factor, input the corrected cutting trajectory into the simulation space for deformation response simulation and trajectory error cyclic comparison, and complete the simulation-driven thin-walled part deformation compensation closed loop.

[0036] The above-described simulation system for compensating cutting deformation of thin-walled parts by incorporating residual stress prediction, wherein the tool path is formed from data collected by displacement sensors of a CNC machine tool.

[0037] Compared with the prior art, the beneficial effects that the at least one technical solution adopted by the present invention can achieve include at least the following:

[0038] The system of this invention, through stress data acquisition and stress distribution map construction, further calculates the consistency of stress direction, enabling detailed understanding of the initial state of thin-walled parts under complex working conditions. After being transferred to the path analysis module, the penetration sequence of the cutting path is extracted through a mesh structure, and the rate of change of the angle between the stress vector and the path vector is analyzed. This allows for the identification of path segments sensitive to stress release trends. This path perturbation correction method based on stress path synergy significantly improves the accuracy of identifying deformation sources. Furthermore, by combining displacement curves for finite element prediction and establishing stress evolution trends, the stress release behavior during the cutting process can be predicted in advance, enabling subsequent path reconstruction to have feedforward adjustments to deformation trends. Capabilities: By fitting the three-dimensional path planning, the spatial continuity and dynamic adaptability of the path are enhanced. Further, by combining trajectory data superposition and displacement trend analysis, a full-process verification mechanism for the cutting trajectory is formed. The above process, through the analysis mechanism of stress acquisition and dynamic linkage of path direction, as well as the iterative optimization and verification closed loop of the cutting path, can significantly improve the processing stability and geometric accuracy of thin-walled parts under complex stress fields, reduce the unexpected deformation caused by insufficient identification of stress disturbance in traditional path design, enhance the response speed of path control and the lead of deformation prediction, improve the accuracy and controllability of cutting compensation, and comprehensively enhance performance in multiple dimensions such as processing quality, simulation efficiency, and heat transfer structure consistency. Attached Figure Description

[0039] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a schematic diagram of the structure of the thin-walled part cutting deformation compensation simulation system that integrates residual stress prediction according to the present invention;

[0041] Figure 2 This is another structural schematic diagram of the simulation system for compensating cutting deformation of thin-walled parts that integrates residual stress prediction according to the present invention;

[0042] Figure 3 This is a schematic diagram of the stress analysis module in the system of the present invention;

[0043] Figure 4 This is a schematic diagram of the path analysis module in the system of the present invention;

[0044] Figure 5 This is a schematic diagram of the stress prediction module in the system of the present invention;

[0045] Figure 6 This is a schematic diagram of the path reconstruction module in the system of the present invention;

[0046] Figure 7 This is a schematic diagram of the compensation verification module in the system of the present invention. Detailed Implementation

[0047] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0048] Unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains; the terminology used in this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention; the terms “comprising” and “having”, and any variations thereof, in the specification and the foregoing description of the invention are intended to cover non-exclusive inclusion.

[0049] The term "embodiment" as used in this invention means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this invention can be combined with other embodiments.

[0050] The specific term "exemplary" used in this invention means "serving as an example, embodiment, or illustration." Any embodiment illustrated as "exemplary" is not necessarily to be construed as superior or better than other embodiments. Although various aspects of embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless specifically indicated otherwise.

[0051] In the description of this invention, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly indicating the number, specific order, or primary and secondary relationship of the indicated technical features.

[0052] In the description of this invention, "a plurality of" means two or more (including two), unless otherwise explicitly specified.

[0053] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0054] Figure 1 This is a schematic diagram of the structure of the thin-walled part cutting deformation compensation simulation system that integrates residual stress prediction according to the present invention.

[0055] like Figure 1 As shown, one embodiment of the present invention provides a simulation system 100 for thin-walled part cutting deformation compensation that integrates residual stress prediction, which includes a stress analysis module 110, a path analysis module 120, a stress prediction module 130, and a path reconstruction module 140. Specifically:

[0056] The stress analysis module 110 is used to collect residual stress data of thin-walled parts before cutting. In a specific example, the thin-walled part is an aircraft fuselage frame. The stress distribution map is obtained based on the residual stress data, and the initial dataset of residual stress is obtained based on the stress distribution map. The initial dataset of residual stress includes the stress distribution map, spatial mesh structure and node coupling relationship.

[0057] The path analysis module 120 is used to acquire the path direction vector of the tool cutting and the initial dataset of residual stress. That is, the path analysis module collects the path of the tool cutting and calculates the path direction vector based on the path. At the same time, the path analysis module receives the initial dataset of residual stress generated by the stress analysis module, calculates the angle change rate based on the initial dataset of residual stress and the path direction vector, and obtains the path abnormal disturbance set based on the angle change rate. The path abnormal disturbance set includes the path segment index, the angle change rate label and the disturbance displacement vector.

[0058] The stress prediction module 130 is used to acquire tool displacement curve data and path abnormal disturbance set. That is, the stress prediction module collects tool displacement curve data, and at the same time, the stress prediction module receives the path abnormal disturbance set generated by the path analysis module. Based on the tool displacement curve data and the path abnormal disturbance set, it performs finite element analysis calculation to obtain the residual stress change. Based on the residual stress change, it obtains the stress evolution prediction set, which includes stress release trend sequence, time cutting mapping table and residual stress change parameters.

[0059] The path reconstruction module 140 is used to obtain the stress evolution prediction set and the path anomaly disturbance set. That is, the path reconstruction module receives the path anomaly disturbance set generated by the path analysis module and the stress evolution prediction set generated by the stress prediction module, performs path planning calculation based on the stress evolution prediction set and the path anomaly disturbance set, obtains the corrected path sequence, and obtains the iterative cutting path set based on the corrected path sequence. The iterative cutting path set includes the fitted path sequence, the spatial continuity structure and the multi-round iterative path version.

[0060] The system of this invention, through an analysis mechanism that dynamically links stress acquisition and path direction, can improve the processing stability and geometric accuracy of thin-walled parts under complex stress fields, and reduce the unexpected deformation caused by insufficient identification of stress disturbances in traditional path design.

[0061] Figure 2 This is another structural schematic diagram of the simulation system for compensating cutting deformation of thin-walled parts that integrates residual stress prediction according to the present invention.

[0062] like Figure 2 As shown, another embodiment of the present invention provides a simulation system for compensating cutting deformation of thin-walled parts by incorporating residual stress prediction. This compensation simulation system is largely the same as the compensation simulation system described above, except that the simulation compensation in this embodiment also includes a compensation verification module 150. Specifically:

[0063] The compensation verification module 150 is used to acquire tool trajectory data, iterative cutting path set, and stress evolution prediction set. That is, the compensation verification module collects tool trajectory data and simultaneously receives the iterative cutting path set generated by the path reconstruction module and the stress evolution prediction set generated by the stress prediction module. Based on the tool trajectory data, iterative cutting path set, and stress evolution prediction set, a corrected cutting trajectory is obtained. The corrected cutting trajectory is input into the simulation space to complete the simulation-driven deformation compensation closed loop for thin-walled parts. The deformation compensation closed loop for thin-walled parts includes a path offset control sequence, simulation verification feedback information, and the corrected cutting trajectory.

[0064] The system of this invention, through the analysis mechanism of dynamic linkage between stress acquisition and path direction, as well as the iterative optimization and verification closed loop of cutting path, can significantly improve the machining stability and geometric accuracy of thin-walled parts under complex stress fields, reduce the unexpected deformation caused by insufficient identification of stress disturbances in traditional path design, enhance the response speed of path control and the lead time of deformation prediction, improve the accuracy and controllability of cutting compensation, and comprehensively enhance performance in multiple dimensions such as machining quality, simulation efficiency, and structural consistency.

[0065] The initial dataset of residual stress includes stress distribution map, spatial grid structure and node coupling relationship; the set of path anomaly disturbances includes path segment index, angle change rate label and disturbance displacement vector; the stress evolution prediction set specifically includes stress release trend sequence, time cutting mapping table and residual stress change parameters; the iterative cutting path set includes fitted path sequence, spatial continuity structure and multi-round iterative path version; and the closed loop of thin-walled part deformation compensation includes path offset control sequence, simulation verification feedback information and corrected cutting trajectory.

[0066] Figure 3 This is a schematic diagram of the stress analysis module in the compensation simulation system; Figure 4 This is a schematic diagram of the path analysis module in the compensation simulation system; Figure 5 This is a schematic diagram of the stress prediction module in the compensation simulation system; Figure 6 This is a schematic diagram of the path reconstruction module in the compensation simulation system; Figure 7 This is a schematic diagram of the compensation verification module in the compensation simulation system.

[0067] like Figure 3 As shown, the stress analysis module 110 includes a stress detection submodule 111, a distribution map construction submodule 112, and a stress set generation submodule 113, wherein:

[0068] The stress detection submodule 111 is used to collect residual stress data of thin-walled parts before cutting. Further, the stress detection submodule includes a stress meter, which is used to collect stress values ​​at multiple locations of the thin-walled parts before cutting and record the stress values ​​at multiple locations through sensors. Based on the residual stress data, preliminary calibration is performed to obtain preliminary residual stress data.

[0069] Specifically, operate the X-ray stress meter, vertically aligning the probe with the test point on the surface of the thin-walled part (aircraft fuselage frame), maintaining a distance of 10mm. Taking the center point of the aircraft fuselage frame web as an example, set the measurement point coordinates (200, 300, 0), start the stress meter, and continuously collect three stress values, recording them as -125.3MPa, -123.8MPa, and -124.7MPa. Simultaneously record the ambient temperature at 26.5℃, and calculate the arithmetic mean of the three measurements. The temperature compensation coefficient was set to 0.55 MPa / ℃, which was obtained experimentally. At a standard temperature of 20℃, the stress values ​​of the same part were measured at 25℃, 30℃, and 35℃. The stress change for every 1℃ increase in temperature was calculated, and the average of five experiments (0.55) was used to calculate the compensation amount. Compensation is performed on the original stress value: Rounded to -128.2 MPa, the stress was measured three times at points (150, 50, 0) on the upper surface of the frame edge. The measured values ​​were -85.1 MPa, -86.3 MPa, and -84.7 MPa. The average value was calculated to be -85.37 MPa. The temperature was 26.3℃. The compensation was calculated as follows: After calibration, the pressure is -88.835 MPa. Measurements at the edge of the frame web (300, 400, 0) are recorded as 45.6 MPa, 46.2 MPa, and 44.9 MPa, with an average of 45.57 MPa. The temperature is 26.6℃. Calculate the compensation amount. After calibration, the pressure is 41.94 MPa, as shown in Table 1. Table 1 lists the data of all measurement points, and the preliminary data of residual stress are obtained.

[0070] Table 1: Stress Calibration Table for Measurement Points on Aircraft Fuselage Frame

[0071]

[0072] As shown in Table 1, the residual stress values ​​at multiple points were obtained through temperature compensation calibration.

[0073] The distribution map construction submodule 112 is used to obtain preliminary residual stress data. Based on the preliminary residual stress data, a matching graphical method is used to perform spatial mapping to obtain a stress distribution map. The stress distribution map can display the stress value distribution in multiple regions through color.

[0074] Specifically, based on the preliminary residual stress data in Table 1, a two-dimensional plane coordinate system was established with the lower left corner of the thin-walled part as the origin. The horizontal axis ranged from 0 to 500 mm, and the vertical axis ranged from 0 to 600 mm. The stress values ​​of -128.2 MPa at the measurement point (200, 300), -88.8 MPa at (150, 50), and 41.9 MPa at (300, 400) were plotted on the coordinate system. The grid spacing was set to 50 mm. A 10×12 grid array was created. Taking the grid point (100, 100) as an example, four surrounding measurement points were selected: (150, 50), (-88.8MPa), (200, 300), (-128.2MPa), (300, 400), and (41.9MPa). Bilinear interpolation was calculated, first along the x-direction. On the edge where y=50, the weight ratio of x=100 between x=150 and x=200 was calculated as follows: Interpolation result: On the edge where y=400, x=100 lies between x=150 and x=300, with weights... (Taking boundary values ​​when out of range), directly take the value of the nearest point (150, 50) - 88.8, then interpolate along the y-direction. y=100 lies between y=50 and y=400, weighted... Interpolation result: Rounded to -91.6 MPa, the stress values ​​of all grid points are calculated. A color mapping rule is established: compressive stress values ​​≤ -50 MPa are displayed in dark blue, -50 MPa to 0 MPa are displayed in light blue, and tensile stress values ​​≥ 0 MPa are displayed in red. The -91.6 MPa value of grid point (100, 100) is mapped to dark blue, and the grid point (250, 350) is mapped to red by interpolation to 15.3 MPa, thus generating a stress distribution map.

[0075] The stress set generation submodule 113 is used to obtain a stress distribution map, divide the grid region based on the stress distribution map and label the stress in each grid region, integrate the stress data of all grid regions, and obtain the initial dataset of residual stress.

[0076] Specifically, based on the stress distribution map, a pre-divided 50mm spacing grid is used, and each grid region is assigned a unique identifier. The lower left corner coordinates are taken as the region center point. The grid region (50, 50) corresponds to the center point (75, 75). The stress value is taken from the interpolation result of the grid point (100, 100) in the distribution map, which is -91.6MPa. The calibrated stress value is -91.6MPa. The center point (225, 375) of the grid region (200, 350) has a stress value of 15.3MPa, taken from the interpolation result of the grid point (250, 350). 15.3 MPa. Integrate all mesh data, sort them in ascending order by x-coordinate first and then y-coordinate. The first row of data: stress value of -102.1 MPa at the center point (25, 25) of region (0, 0); the second row: stress value of -97.8 MPa at the center point (75, 25) of region (50, 0); the third row: stress value of -93.5 MPa at the center point (125, 25) of region (100, 0); and so on, up to the stress value of 28.7 MPa at the center point (475, 575) of region (450, 550), for a total of 120 sets of data, to generate the initial dataset of residual stress.

[0077] like Figure 4 As shown, the path analysis module 120 includes a path acquisition submodule 121, a sequence construction submodule 122, and a disturbance identification submodule 123, specifically:

[0078] The path acquisition submodule 121 is used to acquire the path trajectory data of the tool at each moment during the cutting process. Based on the path trajectory data, the start and end spatial coordinates and cutting time of each path segment are obtained. Based on the start and end spatial coordinates, the path direction vector is obtained. Based on the start and end spatial coordinates, the path direction vector and the cutting time, a time index mapping is established according to the number to obtain the path direction vector sequence.

[0079] Specifically, the displacement sensor of the CNC machine tool collects the tool trajectory at a sampling frequency of 50Hz. Taking the cutting of the fuselage frame web plate of an aircraft as an example, path segment 1 is defined as: start time. End time Starting coordinates Termination coordinates Calculate the direction vector components: , , , to obtain vector Path segment 2: , Starting coordinates Termination coordinates ,calculate , , ,vector Path segment 3: , Starting coordinates Termination coordinates ,vector Assign a number (1, 2, 3) to each path segment and establish a time index mapping: number 1 maps to a time interval. Mapping number 2 Mapping number 3 This generates a sequence of path direction vectors.

[0080] Table 2: Toolpath Segment Data Table

[0081]

[0082] As shown in Table 2, record the path segment coordinates, time, and direction vector to generate a path direction vector sequence.

[0083] The sequence construction submodule 122 is used to obtain the initial dataset of residual stress and the path direction vector sequence. The residual stress direction vector is calculated based on the initial dataset of residual stress. The node number penetrated by each path is extracted based on the path direction vector sequence. The path direction vector is paired with the corresponding grid node. The angle change rate is calculated based on the path direction vector and the residual stress direction vector to obtain the path angle change rate.

[0084] Specifically, the path direction vector sequence is called (data in Table 2), based on 50mm spacing grid nodes (such as nodes). , , Extract the penetration node of path segment 1: interpolate with a step size of 10mm. Location Corresponding node , Location Corresponding node , Location Corresponding node Path segment 2: node , Location Calculate the distance to the nearest grid node: , The minimum distance of 25mm is less than the threshold of 30mm (the threshold is set at 60% of the grid spacing of 50mm, and the average effective distance has been verified through 5 experiments), and the node is identified. , node Pair the path direction vector with the node: path segment 1 vector Node configuration Same vector matching nodes and Path segment 2 vector Node configuration , and Retrieve the initial dataset of residual stress, including 120 sets of stress values ​​for mesh regions, such as the stress in region (0, 0). Calculate the residual stress direction vector: node ,stress (Compressive stress), direction vector (Experimental calibration of vertical direction), node stress ,direction ; Calculate the included angle: node place, , module length , included angle ,node place, , included angle Time difference ( to ), rate of change Calculate the rate of change of all paired points to obtain the sequence of the rate of change of the path angle.

[0085] The disturbance identification submodule 123 is used to obtain the path angle change rate, filter out path segments whose change rate exceeds the angle change threshold based on the path angle change rate, number the selected path segments, and generate a set of path disturbance segments according to the number time series.

[0086] The angle change threshold is set based on the mean and standard deviation of the angle change rate of all path segments. Specifically, the angle change threshold is set by calculating the mean and standard deviation of the angle change rate of all path segments by statistically analyzing the overall distribution range of the angle change rate of the path segments, and then setting the threshold according to the degree of fluctuation in the change range.

[0087] Specifically, based on the path angle change rate sequence (e.g.) Set the angle change threshold: collect data from 10 normal cutting experiments and calculate the average rate of change. Standard deviation threshold (Rounding), Judgment rule: Rate of change This is within the normal range. For abnormal intervals, filter path segment numbers: Path segment 1 node rate of change Normal, path segment 2 nodes rate of change An anomaly was identified, and path segment 2 was assigned a number. The anomaly segments were grouped into a set and sorted by time series: path segment 2 time interval. Generate a set of path disturbance segments and obtain a set of path abnormal disturbances.

[0088] like Figure 5 As shown, the stress prediction module 130 includes a time matching submodule 131, a stress release submodule 132, and a trend calculation submodule 133, wherein:

[0089] The time matching submodule 131 is used to acquire tool displacement curve data and path abnormal disturbance set. Based on the tool displacement curve data and path abnormal disturbance set, the time node and position coordinate of each disturbance path are compared, analyzed and mapped to obtain the disturbance time position sequence.

[0090] Specifically, based on the set of abnormal path disturbances (including the marked abnormal path segment numbers, such as path segment 2), the tool displacement curve data recorded by the CNC machine tool displacement sensor (sampling frequency 50Hz) is called to extract the time node corresponding to path segment 2: start time. End time Data points within that time period were extracted from the displacement curve data, and position coordinate sequences were obtained at 0.02-second intervals, including... Time coordinates , Time coordinates until Time coordinates By matching the path segment number 2 with the time interval [2.5, 5.0] on the displacement time axis, a disturbance time position sequence is generated. The sequence elements are (time, coordinate) pairs, including (2.5, (100, 100, 0)), (2.52, (100.8, 99.6, 0)) ~ (5.0, (200, 50, 0)), a total of 126 data points (time span 2.5s, sampling interval 0.02s, number of data points = 2.5 / 0.02+1 = 126), generating the disturbance time position sequence.

[0091] Table 3: Example Table of Displacement Data for Path Segment 2

[0092]

[0093] As shown in Table 3, the displacement data sequence of the abnormal path segment is recorded to generate the disturbance time and location sequence.

[0094] The stress relief submodule 132 is used to obtain the disturbance time location sequence, obtain the first node based on the disturbance time location sequence, construct displacement boundary conditions based on the displacement coordinate data under the corresponding time node, apply boundary input conditions in the mesh for analysis, and perform finite element analysis calculation based on the coordinates of the first node to obtain the residual stress change.

[0095] Specifically, the perturbation time location sequence is called (as shown in Table 3), and the key (first) node is selected (one point is taken every 0.1s, for a total of 26 points). The first point is used as the basis for the selection. coordinate For example, the calculation is performed using the following formula:

[0096] Substitute into the formula

[0097] in, This represents the initial residual stress value, which is obtained directly from the initial residual stress dataset (e.g., the value corresponding to the mesh node coordinates), and the unit is MPa.

[0098] This represents the equivalent stress value, obtained through iterative calculation of the finite element equilibrium equations (based on displacement boundary conditions), and its unit is MPa.

[0099] This represents the number of degrees of freedom; for two-dimensional planar problems, it is 2 (in the x and y directions), and for three-dimensional problems, it is 3.

[0100] Representing the The increment of displacement change is calculated by the coordinate difference between adjacent time points of the displacement sensor, and the unit is mm;

[0101] This represents a reference displacement value, set to 1 mm according to the material testing standard ASTM E8.

[0102] This represents a dimensionless correction coefficient, calibrated through material tensile testing (to eliminate small displacement measurement errors).

[0103] Subscript Index of degrees of freedom representing the association of summation symbols ( Corresponding to the x-direction, (corresponding to the y-direction)

[0104] In this example, : Read from the initial dataset of residual stress (implementation data: at node (100,100)) );

[0105] By inputting displacement boundary conditions ( ), and The displacement boundary conditions represent the x and y coordinates. The equilibrium equations are solved iteratively until convergence (5 iterations), and the equivalent stress values ​​are output. ;

[0106] For two-dimensional plane problems, the value is fixed at 2;

[0107] Displacement sensor data calculation ( coordinate , coordinate ):

[0108] (x direction)

[0109] (y direction),

[0110] The standard is set at 1.0 mm, based on ASTM E8.

[0111] Material tensile test calibration procedure: Apply a displacement of 0.1-0.5 mm to 5 groups of aluminum alloy specimens, measure the stress response deviation, and fit the deviation curve to obtain... (Experimental values: 0.12, 0.09, 0.11, 0.10, 0.08, average 0.1)

[0112] Substituting the above values ​​into the above formula yields:

[0113] ,

[0114] The results showed that The stress release was 8.643 MPa. By correlating the displacement boundary conditions with the stress state, the local stress relaxation effect was quantified, and the residual stress change was obtained as [8.6, 12.3] MPa.

[0115] The trend calculation submodule 133 is used to obtain the residual stress change, calculate the rate of change of stress release value between two adjacent path segments based on the residual stress change, and obtain the stress evolution prediction set based on the rate of change of stress release value.

[0116] Specifically, based on the residual stress variation (e.g., the release range of path segment 2 [8.6, 12.3] MPa), the maximum release amount of each path segment is extracted according to the path number sequence (path segment 1 normal cutting release amount 0 MPa, path segment 2 maximum release amount 12.3 MPa, path segment 3 release amount 5.0 MPa), and the change rate between adjacent path segments is calculated: the change amount from path segment 1 to 2. Time interval (From the end of path segment 1 to the end of path segment 2), rate of change The change in path segment 2 to 3 Time interval rate of change Construct a sequence according to the path order: , The change rate trend distribution sequence is generated to obtain the stress evolution prediction set.

[0117] like Figure 6 As shown, the path reconstruction module 140 includes a path fitting submodule 141, a path correction submodule 142, and a path update submodule 143, wherein:

[0118] The path fitting submodule 141 is used to obtain the stress evolution prediction set and the path anomaly disturbance set. Based on the stress evolution prediction set and the path anomaly disturbance set, the time series and spatial coordinates of the disturbance path segment are obtained. Based on the time series and spatial coordinates, the time coordinate alignment is calculated by a three-dimensional path planning algorithm to obtain the fitted path coordinate sequence.

[0119] Specifically, based on the stress evolution prediction set (including the stress change rate sequence of path segments, such as the change rate of path segment 2) ) and the path anomaly disturbance set (labeled with anomaly segment numbers and weights, such as the weight coefficient sequence of path segment 2), extract the time series of path segment 2 (start time) End time (Sampling points are spaced 0.1s apart, for a total of 26 points) and spatial coordinates (e.g., coordinates of point 1). Coordinates of point 2 Coordinates of point 3 The time coordinate alignment is calculated using the following formula, based on a 3D path planning algorithm (based on B-spline curve fitting):

[0120]

[0121] in, : Total number of valid sampling points, obtained by counting time series data points (e.g., 26 points for path segment 2), unit: none;

[0122] Sampling point index ( to ), indicating the sequential position of the data points;

[0123] Dynamic weighting coefficient, calculated based on stress change rate, unit: none;

[0124] Original path time coordinates, measured values ​​from displacement sensors, unit: seconds (s);

[0125] : Fitted path time coordinates, output value of the 3D path planning algorithm, unit: seconds (s);

[0126] Reference time resolution, average sampling interval during normal period, unit: seconds (s);

[0127] In this specific example, Path segment 2 time series ( to (Step size 0.1s) Calculate the number of points. ;

[0128] Based on stress change rate (MPa / s) calculation: where Let k be the rate of change of stress at point k, and point 1 be the rate of change of stress at point k. , point 2 , point 3 maximum value , , , ;

[0129] : Measured value of displacement sensor (point 1) , point 2 , point 3 );

[0130] B-spline algorithm output value (point 1) , point 2 , point 3 );

[0131] Calculation of the average sampling interval of 5 normal segments: ;

[0132] in, Threshold 0.5: Based on data from 10 cutting experiments, the high-weight segment ( (60%), median value taken; The sample size conforms to the machine tool sampling standard (0.01-0.5s), and the measured value of 0.1s is within a reasonable range. With n=3 points, substituting into the formula: ,molecular denominator , ,result (Preset benchmark:) (High alignment) indicates that the time deviation of the fitted path is within the allowable range, and the fitted path coordinate sequence can be directly generated for subsequent correction.

[0133] The path correction submodule 142 is used to obtain the fitted path coordinate sequence and the set of path anomalies, calculate the spatial continuity deviation based on the fitted path coordinate sequence, perform path correction operations based on the set of path anomalies and the spatial continuity deviation, and obtain the corrected path sequence based on the path correction operations. The path correction operations include adjusting the gaps and misalignments between path segments.

[0134] Specifically, the fitted path coordinate sequence (point 1(100, 100, 0), point 2(102, 99, 0), point 3(104, 98, 0)) is called, and compared with the initial path coordinates (point 1(100, 100, 0), point 2(101, 99.5, 0), point 3(103, 98.5, 0)), and the spatial continuity deviation is calculated: the difference in coordinates of point 1. , The difference in coordinates between point 2 , The difference in coordinates of point 3 , Based on the path anomaly perturbation set (marking path segment 2 as an anomaly, weight coefficient sequence δ-k), a correction operation is performed: First, identify gaps (distance deviation between point 2 and point 3, initial distance). Fitting distance (No gaps), identify misalignment (point 2 y coordinate deviation 0.5mm, threshold 0.3mm based on machine tool accuracy standard); then, adjust the misalignment: apply linear interpolation, new y coordinate = initial y + (fitted y - initial y) * δ - k, point 2 δ - k = 0.986, new y = 99.5 + (99 - 99.5) * 0.986 = 99.5 - 0.493 = 99.007, similarly point 3 δ - k = 0.996, new y = 98.5 + (98 - 98.5) * 0.996 = 98.5 - 0.498 = 98.002, generate the corrected path sequence (point 1 (100, 100, 0), point 2 (102, 99.007, 0), point 3 (104, 98.002, 0)).

[0135] The path update submodule 143 is used to obtain the corrected path sequence, iteratively update the path coordinates based on the corrected path sequence and synchronously adjust the direction of the cutting path of the tool to optimize the continuity of the path and the cutting stability, and obtain an iterative cutting path set.

[0136] Specifically, based on the corrected path sequence (point 1 (100, 100, 0), point 2 (102, 99.007, 0), point 3 (104, 98.002, 0)), the coordinates are iteratively updated: In the first iteration, the slope of the path segment (slope from point 1 to point 2) is calculated. Initial slope -0.5), adjust tool path (new slope = initial slope + (corrected slope - initial slope) * 0.5, set relaxation factor 0.5, the relaxation factor 0.5 is based on machine tool dynamic response characteristic experimental verification (5 sets of workpiece tests), calculated new slope = -0.5 + (-0.4965 - (-0.5)) * 0.5 = -0.5 + (0.0035) 0.5 = -0.5 + 0.00175 = -0.49825), update point 2 y coordinate = 100 + (-0.49825)(102 - 100) = 100 - 0.9965 = 99.0035, second iteration, according to the updated coordinates, repeat the above calculation process, optimize the continuity point 1 to point 2 distance. The distance from point 2 to point 3 is consistent, generating an iterative cutting path set: point 1 (100, 100, 0), point 2 (102, 99.0035, 0), and point 3 (104, 98.002, 0).

[0137] like Figure 7 As shown, the compensation verification module 150 includes a displacement trend superposition submodule 151, a path offset calculation submodule 152, and a trajectory iteration submodule 153, wherein:

[0138] The displacement trend superposition submodule 151 is used to acquire tool trajectory data and iterative cutting path set. The tool trajectory is formed by data collected by the displacement sensor of the CNC machine tool. The displacement increment sequence is obtained based on the tool trajectory data and iterative cutting path set. Specifically, the coordinate sequence and time sequence corresponding to multiple cutting steps are acquired based on the tool trajectory data. The path segment displacement vector is acquired based on the iterative cutting path set. The displacement increment sequence is obtained based on the coordinate sequence and time sequence corresponding to multiple cutting steps and the path segment displacement vector. The displacement trend superposition is performed by accumulating all the normalized displacement increment sequences to obtain the displacement trend superposition amount.

[0139] Specifically, based on the iterative cutting path set, including the path point sequence: point 1 (100, 100, 0), point 2 (102, 99.0035, 0), and point 3 (104, 98.002, 0), tool trajectory data from a CNC machine tool with a sampling frequency of 50Hz is collected, and the coordinate sequence of three cutting steps is extracted (cutting step 1: Coordinate sequence (0, 0, 0), (50, 50, 0), (100, 100, 0), cutting step 2: Coordinate sequence (100, 100, 0), (150, 75, 0), (200, 50, 0), cutting step 3: The coordinate sequence is (200, 50, 0), (250, 100, 0), (300, 150, 0); the displacement increment sequence is calculated as: the increment from point 1 to point 2 in cutting step 1. Increment from point 2 to point 3 The increment from point 1 to point 2 in cutting step 2 Normalization: Calculate the vector magnitude. Normalized value Calculate the same Length Normalized value Cumulative trend overlay: Cumulative value of cutting step 1 Cumulative value of cutting step 2 The displacement trend superposition sequence is generated, cutting step 1: (1.414, 1.414, 0), cutting step 2: (2.308, 0.967, 0).

[0140] Table 4: Normalized Displacement Increment Table

[0141]

[0142] As shown in Table 4, the displacement increments and normalization results are recorded.

[0143] The path offset calculation submodule 152 is used to obtain the displacement trend superposition amount and the iterative cutting path set, calculate the offset vector based on the displacement trend superposition amount and the iterative cutting path set, construct the offset projection relationship based on the offset vector, and obtain the cutting path offset value by performing segment-by-segment cumulative analysis on the offset vector projection and forming an offset distribution sequence.

[0144] Specifically, call the displacement trend superposition amount (cutting step 1 superposition amount). Cutting step 2 superposition amount ) and the set of iterative cutting paths (path segment 1 direction vector) Path segment 2 direction vector Offset vectors are calculated based on path segment numbers: Offset vector for path segment 1 (Assume initial) ) Path segment 2 offset vector Construct projection relationships: Offset projection of path segment 1 dot product , modulus square Projection vector Similarly, calculate the projection of path segment 2 (process omitted), and perform cumulative analysis segment by segment: cumulative projection value of path segment 1. Path segment 2 cumulative projection value This forms an offset distribution sequence (2.0, 3.0).

[0145] The trajectory iteration submodule 153 is used to obtain the cutting path offset value and stress evolution prediction set. Based on the cutting path offset value, stress evolution prediction set and preset scaling factor, the corrected cutting trajectory is obtained. The corrected cutting trajectory is input into the simulation space for deformation response simulation and trajectory error cyclic comparison to complete the simulation-driven thin-walled part deformation compensation closed loop.

[0146] Specifically, the cutting path offset values ​​(sequence values ​​2.0, 3.0) and the stress evolution prediction set (path segment 1 change rate) are called. Path segment 2 rate of change Set the scaling factor (Correlation of absolute value of rate of change) Represents the rate of change, the correction amount for path segment 1. Path segment 2 correction amount Update cutting trajectory: The original coordinates of the endpoint of path segment 2 are (200, 50, 0), and the corrected vector direction is taken from the path direction. Unit vector Corrected displacement New coordinates (200+0.0132, 50-0.0066, 0)≈(200.013, 49.993, 0), input simulation space (ABAQUS model), set boundary conditions (fixed constraints), material parameters (aluminum alloy: elastic modulus 70GPa, Poisson's ratio 0.33), cutting force load (500N), obtain deformation response: displacement after deformation of point (200.013, 49.993, 0) (0.012, -0.005, 0); error comparison: set threshold 0.01mm (machine tool accuracy standard), calculate error modulus. The requirements are met.

[0147] The system of this invention, through stress data acquisition and stress distribution map construction, further calculates the consistency of stress direction, enabling detailed understanding of the initial state of thin-walled parts under complex working conditions. After being transferred to the path analysis module, the penetration sequence of the cutting path is extracted through a mesh structure, and the rate of change of the angle between the stress vector and the path vector is analyzed. This allows for the identification of path segments sensitive to stress release trends. This path perturbation correction method based on stress path synergy significantly improves the accuracy of identifying deformation sources. Furthermore, by combining displacement curves for finite element prediction and establishing stress evolution trends, the stress release behavior during the cutting process can be predicted in advance, enabling subsequent path reconstruction to have feedforward adjustments to deformation trends. Capabilities: By fitting the three-dimensional path planning, the spatial continuity and dynamic adaptability of the path are enhanced. Further, by combining trajectory data superposition and displacement trend analysis, a full-process verification mechanism for the cutting trajectory is formed. The above process, through the analysis mechanism of stress acquisition and dynamic linkage of path direction, as well as the iterative optimization and verification closed loop of the cutting path, can significantly improve the processing stability and geometric accuracy of thin-walled parts under complex stress fields, reduce the unexpected deformation caused by insufficient identification of stress disturbance in traditional path design, enhance the response speed of path control and the lead of deformation prediction, improve the accuracy and controllability of cutting compensation, and comprehensively enhance performance in multiple dimensions such as processing quality, simulation efficiency, and heat transfer structure consistency.

[0148] The above description is merely a specific embodiment of the present invention and should not be construed as limiting the scope of the invention. Therefore, substitutions of equivalent components, or equivalent changes and modifications made within the scope of protection of this application, should still fall within the scope of this application. Furthermore, the technical features, technical features and technical solutions, and technical solutions in this invention can be freely combined and used.

Claims

1. A simulation system for compensating cutting deformation of thin-walled parts by integrating residual stress prediction, characterized in that, The simulation system includes: The stress analysis module is used to collect residual stress data of thin-walled parts before cutting, obtain a stress distribution map based on the residual stress data, and obtain an initial dataset of residual stress based on the stress distribution map. The path analysis module is used to obtain the path direction vector of the tool cutting and the initial dataset of residual stress, calculate the angle change rate based on the initial dataset of residual stress and the path direction vector, and obtain the path abnormal disturbance set based on the angle change rate. The stress prediction module is used to acquire tool displacement curve data and the path abnormal disturbance set, perform finite element analysis calculations based on the tool displacement curve data and the path abnormal disturbance set to obtain the residual stress change, and obtain the stress evolution prediction set based on the residual stress change. The path reconstruction module is used to obtain the stress evolution prediction set and the path anomaly perturbation set, perform path planning calculations based on the stress evolution prediction set and the path anomaly perturbation set to obtain a corrected path sequence, and obtain an iterative cutting path set based on the corrected path sequence. The compensation verification module is used to acquire tool trajectory data, the iterative cutting path set, and the stress evolution prediction set. Based on the tool trajectory data, the iterative cutting path set, and the stress evolution prediction set, a corrected cutting trajectory is obtained. The corrected cutting trajectory is input into the simulation space to complete the simulation-driven deformation compensation closed loop for thin-walled parts. The path analysis module includes: a path acquisition submodule, used to acquire path trajectory data of the tool during the cutting process, obtain the start and end spatial coordinates and cutting time of each path segment based on the path trajectory data, obtain the path direction vector based on the start and end spatial coordinates, and obtain a path direction vector sequence based on the start and end spatial coordinates, the path direction vector, and the cutting time; a sequence construction submodule, used to acquire the initial dataset of residual stress and the path direction vector sequence, calculate the residual stress direction vector based on the initial dataset of residual stress, calculate the angle change rate based on the path direction vector in the path direction vector sequence and the residual stress direction vector, and obtain the path angle change rate; and a disturbance identification submodule, used to acquire the path angle change rate, filter out path segments with a change rate exceeding the angle change threshold based on the path angle change rate, and obtain a path abnormal disturbance set based on the filtered path segments. The path reconstruction module includes: a path fitting submodule, used to acquire the stress evolution prediction set and the path anomaly perturbation set, obtain the time series and spatial coordinates of the perturbation path segment based on the stress evolution prediction set and the path anomaly perturbation set, and calculate the time coordinate alignment based on the time series and the spatial coordinates to obtain a fitted path coordinate sequence; a path correction submodule, used to acquire the fitted path coordinate sequence and the path anomaly perturbation set, calculate the spatial continuity deviation based on the fitted path coordinate sequence, perform a path correction operation based on the path anomaly perturbation set and the spatial continuity deviation, and obtain a corrected path sequence based on the path correction operation; and a path update submodule, used to acquire the corrected path sequence, iteratively update the path coordinates based on the corrected path sequence, and adjust the cutting path direction of the tool to obtain an iterative cutting path set.

2. The simulation system for compensating cutting deformation of thin-walled parts by incorporating residual stress prediction as described in claim 1, characterized in that, The stress analysis module includes: The stress detection submodule is used to collect residual stress data of thin-walled parts before cutting, and to perform preliminary calibration based on the residual stress data to obtain preliminary residual stress data. The distribution map construction submodule is used to obtain the preliminary residual stress data and perform spatial mapping based on the preliminary residual stress data to obtain the stress distribution map; The stress set generation submodule is used to obtain the stress distribution map, divide the grid region based on the stress distribution map and label the stress in each grid region, and integrate the stress data of all the grid regions to obtain the initial dataset of residual stress.

3. The simulation system for compensating cutting deformation of thin-walled parts by integrating residual stress prediction according to claim 2, characterized in that, The stress detection submodule includes a stress meter, which is used to collect stress values ​​at multiple locations of the thin-walled part before cutting.

4. The simulation system for compensating cutting deformation of thin-walled parts by incorporating residual stress prediction as described in claim 1, characterized in that, The included angle change threshold is set based on the mean and standard deviation of the included angle change rate of all path segments.

5. The simulation system for compensating cutting deformation of thin-walled parts by incorporating residual stress prediction as described in claim 1, characterized in that, The stress prediction module includes: The time matching submodule is used to acquire tool displacement curve data and the path abnormal disturbance set, and to obtain the disturbance time position sequence by comparing the tool displacement curve data and the path abnormal disturbance set. The stress relief submodule is used to obtain the disturbance time location sequence, obtain the first node based on the disturbance time location sequence, and perform finite element analysis calculation based on the coordinates of the first node to obtain the residual stress change. The trend calculation submodule is used to obtain the residual stress change, calculate the rate of change of stress release value between two adjacent path segments based on the residual stress change, and obtain the stress evolution prediction set based on the rate of change of stress release value.

6. The simulation system for compensating cutting deformation of thin-walled parts by incorporating residual stress prediction as described in claim 1, characterized in that, The compensation verification module includes: The displacement trend superposition submodule is used to acquire tool trajectory data and the iterative cutting path set, obtain a displacement increment sequence based on the tool trajectory data and the iterative cutting path set, and perform cumulative trend superposition based on the displacement increment sequence to obtain the displacement trend superposition amount. The path offset calculation submodule is used to obtain the displacement trend superposition amount and the iterative cutting path set, calculate the offset vector based on the displacement trend superposition amount and the iterative cutting path set, construct the offset projection relationship based on the offset vector, and obtain the cutting path offset value based on the offset vector projection. The trajectory iteration submodule is used to obtain the cutting path offset value and the stress evolution prediction set, obtain the corrected cutting trajectory based on the cutting path offset value, the stress evolution prediction set and the preset scaling factor, input the corrected cutting trajectory into the simulation space for deformation response simulation and trajectory error cyclic comparison, and complete the simulation-driven thin-walled part deformation compensation closed loop.

7. The simulation system for compensating cutting deformation of thin-walled parts by incorporating residual stress prediction as described in claim 6, characterized in that, The tool path is formed from data collected by the displacement sensor of the CNC machine tool.

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