A method and system for processing thin-walled parts

Abstract

The present invention belongs to the technical field of thin-walled part processing, and in particular, to a method and system for processing thin-walled parts, comprising: performing multiple cutting operations on a part blank using the same cutting parameters and cutting trajectory before finishing the thin-walled part to obtain a feed current curve for each cutting operation; judging whether the part blank has an abnormal area on the cutting trajectory based on the changing characteristics of multiple feed current curves in the same trajectory interval; generating a target feed curve for the thin-walled part based on at least one feed current curve when an abnormal area exists in the part blank; and cutting the remaining material of the thin-walled part based on the target feed curve. In the present invention, by obtaining a feed current curve through multiple cutting operations, utilizing curve fluctuation characteristics, similarity analysis, and fluctuation frequency / mean value judgment, abnormal areas such as hardness distribution differences and residual stress distribution differences in the part blank can be accurately located, thereby avoiding processing defects caused by material unevenness.

Description

Technical Field

[0001] The present invention relates to the technical field of thin-walled parts processing, and in particular to a thin-walled parts processing method and system. Background Art

[0002] Thin-walled parts are widely used in the aerospace, precision manufacturing, and automotive industries. Due to their thin walls and poor rigidity, they are easily deformed during machining due to cutting forces and heat, affecting the dimensional accuracy and surface quality of thin-walled parts. This is especially true for raw materials such as forgings, pipes, and bars, which often have internal structural inhomogeneities such as forging streamlines, residual stresses, carbide segregation, and cold work hardening. These inhomogeneities can lead to fluctuating cutting forces, abnormal tool wear, and thermal deformation of the workpiece, thus affecting the final machining quality of thin-walled parts.

[0003] Existing machining methods typically reduce deformation by lowering cutting parameters or increasing workpiece support, but this approach can reduce machining efficiency and cannot adapt to changes in material structure in real time. Some intelligent machining systems incorporate force sensing or temperature monitoring technology for adjustment, but lack accurate feedback on material property fluctuations, making it difficult to optimize machining in localized areas. Therefore, a machining method for thin-walled parts is proposed. Summary of the Invention

[0004] Based on the technical problems existing in the prior art, the present invention proposes a processing method and system for thin-walled parts.

[0005] The present invention provides a method for processing thin-walled parts, comprising the following steps:

[0006] Step 1: Before finishing the thin-walled part, the part blank is cut multiple times with the same cutting parameters and cutting trajectory to obtain a feed current curve for each cutting process, wherein the feed current curve is a curve of the feed current of the tool feed motor changing with the cutting trajectory;

[0007] Step 2: judging whether there is an abnormal area on the cutting trajectory of the part blank based on the change characteristics of multiple feed current curves in the same trajectory interval;

[0008] Step 3: When the abnormal area exists in the part blank, generating a target feed curve for the thin-walled part according to at least one feed current curve, wherein the target feed curve is a curve showing the feed rate of the tool feed motor changing with the cutting trajectory;

[0009] Step 4: cutting the remaining material of the thin-walled part according to the target feed curve until the processing task of the thin-walled part is completed.

[0010] Preferably, before obtaining the feed current curve of the tool feed motor during each cutting process, the method further includes:

[0011] Determining whether a no-load current exists in the feed current of the tool feed motor when continuous cutting processing is performed under current cutting parameters and a current cutting trajectory;

[0012] If so, clear the curve data recorded in the current cutting track, and continue to determine whether the feed current of the next cutting track has a no-load current;

[0013] If not, the feed current curve corresponding to the current cutting trajectory is marked as the initial recorded curve of the multiple cutting processes.

[0014] Preferably, before obtaining the feed current curve of the tool feed motor during each cutting process, the method further includes:

[0015] According to the cutting force change characterized by the abnormality of the material of the part blank, a trial cutting rate curve of the part blank is configured, wherein the trial cutting rate curve is a curve showing the feed rate of the tool feed motor changing along the trial cutting trajectory;

[0016] According to the heat impact threshold of the qualified section of the part blank during thin-wall machining and the heat impact results of different cutting parameters, the test cutting parameters of the qualified section are obtained, wherein the test cutting parameters include the test cutting speed and the test cutting depth;

[0017] Performing a test cutting task on the qualified section according to the test cutting rate curve and the test cutting parameters to obtain test cutting current data fed back by the tool feed motor;

[0018] The cutting parameters of the multiple cutting processes are obtained according to the trial cutting current data and the minimum fluctuating current characterized by the part blank when the material is abnormal.

[0019] Preferably, judging whether there is an abnormal area in the part blank of the thin-walled part according to the change characteristics of the plurality of feed current curves in the same trajectory interval specifically includes the following steps:

[0020] Dividing the plurality of feed current curves into a plurality of trajectory intervals according to fluctuation characteristics presented by the plurality of feed current curves;

[0021] Obtaining similarities between multiple curve segments within the same trajectory interval based on curve slopes of the multiple feed current curves having the same monotonic characteristics within the same trajectory interval;

[0022] When the similarity between the multiple curve segments in the same trajectory interval is greater than a preset value, it is determined that the area where the part blank is located in the corresponding trajectory interval is an abnormal area.

[0023] Preferably, when the abnormal area exists in the part blank, generating a target feed curve for the thin-walled part according to at least one feed current curve specifically comprises the following steps:

[0024] Determining the abnormality type of the abnormal area according to the change characteristics of the abnormal area represented by the multiple feed current curves, wherein the abnormality type includes hardness distribution difference and residual stress distribution difference;

[0025] A corresponding number of feed current curves are selected according to the abnormality type to generate a target feed curve for the thin-walled part.

[0026] Preferably, determining the abnormal type of the abnormal area according to the change characteristics of the abnormal area represented by the multiple feed current curves specifically includes the following steps:

[0027] Obtaining the fluctuation frequency and maximum fluctuation mean of each curve segment according to the curve segment change characteristics corresponding to the abnormal area of ​​the plurality of feed current curves, wherein the maximum fluctuation mean is the average value of all maximum peak currents on the curve segment;

[0028] When the fluctuation frequency is less than a first threshold and the maximum fluctuation mean is greater than a second threshold, determining that the abnormality type of the abnormal area is a hardness distribution difference;

[0029] When the fluctuation frequency is greater than or equal to a first threshold and the maximum fluctuation mean is less than or equal to a second threshold, it is determined that the abnormal type of the abnormal area is residual stress distribution difference.

[0030] Preferably, selecting a corresponding number of feed current curves according to the abnormality type to generate the target feed curve of the thin-walled part specifically includes the following steps:

[0031] When the abnormality type is a hardness distribution difference, generating the target feed curve according to the hardness variation of the abnormal area represented by the feed current curves that are less than a first number;

[0032] When the abnormality type is residual stress distribution difference, determining the cutting fluctuation amplitude and cutting fluctuation frequency of the abnormal area based on a feed current curve greater than a second number;

[0033] The target feed curve is generated according to the cutting fluctuation amplitude and the cutting fluctuation frequency, so that the cutting force fluctuation of the remaining material during cutting is less than a preset value.

[0034] Preferably, the remaining material of the thin-walled part is cut according to the target feed curve, specifically as follows:

[0035] When the tool enters the abnormal area, dynamic compensation is performed based on the deviation value ΔI between the real-time collected feed current data and the target feed curve.

[0036] Preferably, when cutting the remaining material of the thin-walled part according to the target feed curve, the method further includes:

[0037] A transition processing zone is established at the boundary of the abnormal area, and its width L is determined by the residual stress gradient ▽σ and the material elastic modulus E: ;

[0038] In the transition zone, progressive cutting parameter adjustment is adopted, and the feed rate changes follow: ;

[0039] Where x is the distance from the boundary of the abnormal area, k is the attenuation coefficient and k=3 / L, is the feed rate in the normal area, Optimized feed rate for abnormal areas;

[0040] At the same time, axial compensation is introduced , where μ is the compensation coefficient, is the maximum current deviation in the current cutting cycle, t is the cutting time, and the compensation direction is opposite to the cutting force direction.

[0041] The present invention also provides a thin-walled parts processing system, which is used to implement any of the above-mentioned thin-walled parts processing methods, and the processing system includes:

[0042] An acquisition module is used to perform multiple cutting operations on the part blank with the same cutting parameters and cutting trajectory before finishing the thin-walled part, so as to obtain a feed current curve for each cutting operation, wherein the feed current curve is a curve showing the feed current of the tool feed motor changing with the cutting trajectory;

[0043] A judgment module, configured to judge whether there is an abnormal area of ​​the part blank on the cutting trajectory based on the change characteristics of multiple feed current curves in the same trajectory interval;

[0044] a generating module, configured to generate a target feed curve for the thin-walled part according to at least one feed current curve when the abnormal area exists in the part blank, wherein the target feed curve is a curve showing a feed rate of the tool feed motor varying with a cutting trajectory;

[0045] A processing module is used to cut the remaining material of the thin-walled part according to the target feed curve until the processing task of the thin-walled part is completed.

[0046] Furthermore, the acquisition module is configured as a processing terminal of the tool feed motor current sensor (sampling rate ≥ 10 kHz).

[0047] Furthermore, the processing system also includes a curve analysis module, a compensation control module and an execution module;

[0048] The curve analysis module is configured to perform the following operations:

[0049] a) Curve similarity calculation: The feed current curves obtained from multiple cutting operations are compared pairwise, and the similarity value S between each two curves is calculated using the dynamic time warping algorithm, where: , represents the dynamic time warping distance between the two curves;

[0050] b) Abnormal region determination: When the similarity value S of any two curves in the same trajectory interval is greater than 0.85, the trajectory interval is marked as a candidate abnormal region;

[0051] c) Anomaly type identification: Perform the following operations on candidate anomaly areas:

[0052] (c1) Extract the dominant fluctuation frequency of the current curve using fast Fourier transform; (c2) Calculate the average value of all maximum peak currents on the curve segment as the maximum fluctuation mean; (c3) If the dominant fluctuation frequency is less than 50 Hz and the maximum fluctuation mean is greater than 4.2 A, determine that the hardness distribution difference is abnormal; (c4) If the dominant fluctuation frequency is within the range of 50-200 Hz and the maximum fluctuation mean is less than or equal to 3.8 A, determine that the residual stress distribution difference is abnormal;

[0053] Compensation control module: including:

[0054] a) PID compensation unit: calculates the axial compensation value Δv in real time;

[0055] b) Transition zone control unit: used to Generate gradient feed instructions;

[0056] The execution module is used to control the servo motor driver and receive the axial compensation amount and gradient feed instructions to adjust the feed rate of the tool feed motor.

[0057] Compared with the prior art, the present invention provides a method and system for processing thin-walled parts, which has the following beneficial effects:

[0058] 1. Accurate identification of abnormal areas: By obtaining the feed current curve through multiple cutting operations and using the curve fluctuation characteristics, similarity analysis, and fluctuation frequency / mean value judgment, abnormal areas such as hardness distribution differences and residual stress distribution differences in the part blank can be accurately located, avoiding processing defects (such as deformation and chipping) caused by material unevenness, and improving processing accuracy by more than 30%;

[0059] Dynamic compensation mechanism: When the tool enters an abnormal area, dynamic compensation is performed based on the deviation value ΔI between the real-time feed current and the target curve through the PID algorithm (proportional, integral, and differential coefficients combined with material removal rate Q and cutting stiffness) to ensure that the cutting force fluctuation is less than the preset value and the surface roughness Ra of the machined surface can be controlled within 1.6μm.

[0060] 2. Accurate configuration of test cutting parameters: According to the cutting force changes when the material is abnormal, the heat impact threshold and the heat impact results of different parameters, the test cutting rate curve and test cutting parameters (speed, depth) are determined in advance to avoid tool loss caused by blind test cutting and extend tool life by about 2 times.

[0061] Progressive cutting adjustment: A transition processing zone is established at the boundary of the abnormal area. The width L is calculated by the residual stress gradient ▽σ and the material elastic modulus E. Combined with progressive feed rate adjustment, it reduces cutting impact and improves processing efficiency by 15%-20%.

[0062] 3. Abnormal type classification and processing: Distinguish hardness differences and residual stress differences based on fluctuation frequency and maximum fluctuation mean, and select the feed current curve to generate the target feed curve (for example, when the hardness difference is based on a small number of curves, the hardness change is adjusted; when the residual stress difference is based on multiple curves to analyze the fluctuation amplitude / frequency), adapting to different material defect scenarios.

[0063] Multi-dimensional compensation strategy: In addition to dynamic adjustment of the feed rate, the introduction of axial compensation and the combination of transition zone technology effectively suppress vibration and deformation during the processing of thin-walled parts, and the qualified rate of finished products is increased to over 98%.

[0064] 4. Initial data filtering mechanism: By judging whether there is no-load current in the feed current, the abnormal curve data is cleared and the initial recorded curve is marked to avoid invalid data interference, reduce the scrap rate caused by incorrect process parameters, and reduce production costs by 10%-15%.

[0065] Quantitative constraints and optimization: During the generation and compensation of the target feed curve, the constraints are strictly followed and quantitative calculations of material characteristic coefficients (α, β, γ) are combined to avoid parameter deviations caused by empiricism and improve process repeatability. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 This is a flow chart of a method for processing thin-walled parts proposed by the present invention;

[0067] Figure 2 This is a comparison diagram of the feed current curves of a thin-walled parts processing method proposed in the present invention. DETAILED DESCRIPTION

[0068] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0069] In the description of the present invention, it should be understood that the terms "upper", "lower", "front", "back", "left", "right", "top", "bottom", "inside", "outside", etc., indicating directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore should not be understood as limiting the present invention.

[0070] Reference Figure 1 , a method for processing thin-walled parts, comprising the following steps:

[0071] Step 1: Before finishing the thin-walled part, the part blank is cut multiple times with the same cutting parameters and cutting trajectory to obtain a feed current curve for each cutting process, wherein the feed current curve is a curve showing the feed current of the tool feed motor changing with the cutting trajectory;

[0072] In addition, before obtaining the feed current curve of the tool feed motor during each cutting process, it is determined whether the feed current of the tool feed motor has a no-load current when continuous cutting is performed under the current cutting parameters and the current cutting trajectory;

[0073] If so, the curve data recorded in the current cutting track is cleared, and the feed current of the next cutting track is judged to determine whether there is no-load current.

[0074] If not, the feed current curve corresponding to the current cutting trajectory is marked as the initial record curve of multiple cutting processes.

[0075] In addition, before obtaining the feed current curve of the tool feed motor during each cutting process, a trial cutting rate curve of the part blank is configured according to the cutting force change characterized by the material abnormality of the part blank. The trial cutting rate curve is a curve showing the feed rate of the tool feed motor changing with the trial cutting trajectory.

[0076] According to the heat impact threshold of the qualified section of the part blank during thin-wall machining and the heat impact results of different cutting parameters, the test cutting parameters of the qualified section are obtained, wherein the test cutting parameters include the test cutting speed and the test cutting depth;

[0077] Perform a test cutting task on the qualified section according to the test cutting rate curve and test cutting parameters to obtain the test cutting current data fed back by the tool feed motor;

[0078] The cutting parameters of multiple cutting processes are obtained based on the trial cutting current data and the minimum fluctuating current characterized by the part blank when the material is abnormal.

[0079] Step 2: Based on the changing characteristics of multiple feed current curves in the same trajectory interval, determine whether there is an abnormal area on the cutting trajectory of the part blank, specifically:

[0080] The multiple feed current curves are divided into multiple trajectory intervals according to the fluctuation characteristics presented by them;

[0081] According to the slopes of the curves of the same monotonic features of the multiple feed current curves in the same trajectory interval, the similarity between the multiple curve segments in the same trajectory interval is obtained;

[0082] When the similarity between multiple curve segments in the same trajectory interval is greater than a preset value, the area where the part blank is located in the corresponding trajectory interval is determined to be an abnormal area.

[0083] Step 3: When an abnormal area exists in the part blank, a target feed curve for the thin-walled part is generated based on at least one feed current curve, wherein the target feed curve is a curve showing the feed rate of the tool feed motor changing with the cutting trajectory, specifically comprising the following steps:

[0084] Determine the abnormality type of the abnormal area according to the change characteristics represented by the multiple feed current curves of the abnormal area, wherein the abnormality type includes hardness distribution difference and residual stress distribution difference;

[0085] According to the abnormality type, a corresponding number of feed current curves are selected to generate the target feed curve for thin-walled parts, specifically:

[0086] When the abnormality type is a hardness distribution difference, generating a target feed curve based on the hardness variation of the abnormal region represented by the feed current curves that are less than the first number;

[0087] When the abnormality type is residual stress distribution difference, determining the cutting fluctuation amplitude and cutting fluctuation frequency of the abnormal area based on the feed current curve greater than the second number;

[0088] A target feed curve is generated according to the cutting fluctuation amplitude and cutting fluctuation frequency so that the cutting force fluctuation of the remaining material is less than a preset value.

[0089] Among them, the abnormal type of the abnormal area is determined according to the change characteristics represented by multiple feed current curves of the abnormal area, specifically:

[0090] According to the curve segment change characteristics corresponding to the abnormal area of ​​multiple feed current curves, the fluctuation frequency and maximum fluctuation mean of each curve segment are obtained, wherein the maximum fluctuation mean is the average value of all maximum peak currents on the curve segment;

[0091] When the fluctuation frequency is less than the first threshold and the maximum fluctuation mean is greater than the second threshold, determining that the abnormal type of the abnormal area is a hardness distribution difference;

[0092] When the fluctuation frequency is greater than or equal to the first threshold and the maximum fluctuation mean is less than or equal to the second threshold, it is determined that the abnormal type of the abnormal area is residual stress distribution difference.

[0093] Step 4: Cut the remaining material of the thin-walled part according to the target feed curve until the processing task of the thin-walled part is completed. This process is specifically achieved through the PID compensation mechanism:

[0094] When the tool enters the abnormal area, dynamic compensation is performed based on the deviation value ΔI between the real-time collected feed current data and the target feed curve. The compensation amount is calculated by the following formula:

[0095]

[0096] in, 、 、 They are proportional, integral and differential coefficients respectively, and their values ​​are determined by the material removal rate Q and cutting stiffness. Sure:

[0097]

[0098]

[0099]

[0100] Where α, β, and γ are material characteristic coefficients, and the feed rate after dynamic adjustment is .

[0101] ,in Preset the target feed curve and satisfy the constraints .

[0102] In addition, when cutting the remaining material of thin-walled parts according to the target feed curve, a progressive adjustment strategy is also included:

[0103] A transition processing zone is established at the boundary of the abnormal area, and its width L is determined by the residual stress gradient ▽σ and the material elastic modulus E: ;

[0104] In the transition zone, progressive cutting parameter adjustment is adopted, and the feed rate changes follow: ;

[0105] Where x is the distance from the boundary of the abnormal area, k is the attenuation coefficient and k=3 / L, is the feed rate in the normal area, Optimized feed rate for abnormal areas;

[0106] At the same time, axial compensation is introduced , where μ is the compensation coefficient, is the maximum current deviation in the current cutting cycle, t is the cutting time, and the compensation direction is opposite to the cutting force direction.

[0107] Reference Figure 2 , showing the fluctuation characteristics of the three feed current curves l1, l2, and l3 in the same trajectory range. The abnormal area (35-40mm trajectory range) is as follows:

[0108] The curve slope similarity is greater than 0.85 (calculated by the DTW algorithm);

[0109] Abnormal hardness area: low frequency and high amplitude fluctuation (0-50Hz, I_peak>4.2A);

[0110] Residual stress zone: high frequency and low amplitude fluctuation (50-200Hz, I_peak≤3.8A).

[0111] In one specific embodiment, a method for intelligent processing of thin-walled parts includes the following steps:

[0112] Step 1: Perform three pre-cuts before finishing, using the same cutting parameters (cutting speed 120 m / min, feed rate 0.1 mm / r, depth of cut 0.2 mm). Use a current sensor mounted on the feed axis servo motor to record three feed current curves, l1, l2, and l3, at a sampling frequency of 10 kHz.

[0113] Step 2: Calculate the curve similarity using the dynamic time warping algorithm:

[0114] DTW is the dynamic time warping distance. When the similarity S of adjacent trajectory intervals is greater than 0.85, it is determined to be an abnormal area.

[0115] Step 3: Analyze the material characteristics of the abnormal area:

[0116] Calculate the fluctuation energy spectral density:

[0117] When the main energy is concentrated in 0-50Hz and the peak current I_peak>4.2A, it is judged as hardness abnormality (HB difference ≥30); when the energy is distributed in 50-200Hz and I_peak≤3.8A, it is judged as residual stress abnormality (stress difference ≥150MPa).

[0118] Step 4: Establish an adaptive processing model:

[0119] a. Use variable feed rate control for hardness abnormal areas:

[0120] Where h is the real-time cutting thickness, h c =0.18mm is the critical value, and Δh=0.02mm is the transition bandwidth.

[0121] b. Introducing phase compensation into the residual stress area:

[0122] Assume that the cutting force fluctuation is , by adjusting the feed phase angle Δφ:

[0123] Experimental results show that the optimal Δφ=π / 3 can reduce the vibration amplitude by 42%.

[0124] Step 5: Perform compensation processing:

[0125] The transition processing zone is activated at X=35.2mm, and a progressive adjustment strategy is adopted. When the real-time current deviation ΔI>15% is detected, the PID compensation mechanism is triggered. Finally, the part wall thickness tolerance is controlled within ±0.015mm, and the surface roughness Ra is <0.8μm.

[0126] In another embodiment, the present invention further provides a thin-walled part processing system, the processing system is used to implement any of the above-mentioned thin-walled part processing methods, and the processing system includes:

[0127] An acquisition module is used to perform multiple cutting operations on the part blank with the same cutting parameters and cutting trajectory before finishing the thin-walled part, so as to obtain a feed current curve for each cutting operation, wherein the feed current curve is a curve showing the feed current of the tool feed motor changing with the cutting trajectory;

[0128] A judgment module, configured to judge whether there is an abnormal area of ​​the part blank on the cutting trajectory based on the change characteristics of multiple feed current curves in the same trajectory interval;

[0129] a generating module, configured to generate a target feed curve for the thin-walled part according to at least one feed current curve when the abnormal area exists in the part blank, wherein the target feed curve is a curve showing a feed rate of the tool feed motor varying with a cutting trajectory;

[0130] A processing module is used to cut the remaining material of the thin-walled part according to the target feed curve until the processing task of the thin-walled part is completed.

[0131] Furthermore, the acquisition module is configured as a processing terminal for the tool feed motor current sensor (sampling rate ≥ 10kHz). The processing terminal can be a single chip microcomputer that can perform data processing.

[0132] Furthermore, the processing system also includes a curve analysis module, a compensation control module and an execution module.

[0133] The curve analysis module is configured to perform the following operations:

[0134] a) Curve similarity calculation: The feed current curves obtained from multiple cutting operations are compared pairwise, and the similarity value S between each two curves is calculated using the dynamic time warping algorithm, where: , represents the dynamic time warping distance between the two curves;

[0135] It should be noted that the dynamic time warping algorithm is implemented using the following steps:

[0136] 1. Construct the distance matrix of two curves , where the elements .

[0137] 2. Calculate the cumulative distance .

[0138] 3. Output As the total distance of the regularized path.

[0139] b) Abnormal region determination: When the similarity value S of any two curves in the same trajectory interval is greater than 0.85, the trajectory interval is marked as a candidate abnormal region;

[0140] c) Anomaly type identification: Perform the following operations on candidate anomaly areas:

[0141] (c1) Extract the dominant fluctuation frequency of the current curve by fast Fourier transform;

[0142] It should be noted that the dominant fluctuation frequency is extracted by:

[0143] 1. Perform discrete Fourier transform on the current curve I(t):

[0144]

[0145] 2. Calculate energy spectral density ;

[0146] 3. The frequency corresponding to the maximum value is determined as the dominant fluctuation frequency.

[0147] (c2) Calculate the average value of all maximum peak currents on the curve segment as the maximum fluctuation mean value; (c3) If the dominant fluctuation frequency is less than 50 Hz and the maximum fluctuation mean value is greater than 4.2 A, it is determined that the hardness distribution difference is abnormal; (c4) If the dominant fluctuation frequency is within the range of 50-200 Hz and the maximum fluctuation mean value is less than or equal to 3.8 A, it is determined that the residual stress distribution difference is abnormal;

[0148] Compensation control module: including:

[0149] a) PID compensation unit: calculates the axial compensation value Δv in real time;

[0150] b) Transition zone control unit: Press Generate gradient feed instructions;

[0151] The execution module is used to control the servo motor driver and receive the axial compensation amount and gradient feed instructions to adjust the feed rate of the tool feed motor.

[0152] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A method for processing thin-walled parts, characterized in that: The steps include: Step 1: Before finishing the thin-walled part, the part blank is cut multiple times with the same cutting parameters and cutting trajectory to obtain a feed current curve for each cutting process, wherein the feed current curve is a curve of the feed current of the tool feed motor changing with the cutting trajectory; Step 2: judging whether there is an abnormal area on the cutting trajectory of the part blank based on the change characteristics of multiple feed current curves in the same trajectory interval; Step 3: When the abnormal area exists in the part blank, a target feed curve of the thin-walled part is generated according to at least one feed current curve, and the abnormal type of the abnormal area is determined according to the change characteristics of the abnormal area represented by multiple feed current curves, wherein the abnormal type includes hardness distribution difference and residual stress distribution difference; according to the abnormal type, a corresponding number of feed current curves are selected to generate the target feed curve of the thin-walled part; when the abnormal type is hardness distribution difference, the target feed curve is generated according to the hardness change of the abnormal area represented by less than a first number of feed current curves; when the abnormal type is residual stress distribution difference, the cutting fluctuation amplitude and cutting fluctuation frequency of the abnormal area are determined according to more than a second number of feed current curves; the target feed curve is generated according to the cutting fluctuation amplitude and the cutting fluctuation frequency, so that the cutting force fluctuation of the remaining material during cutting is less than a preset value; wherein the target feed curve is a curve of the feed rate of the tool feed motor changing with the cutting trajectory; Step 4: cutting the remaining material of the thin-walled part according to the target feed curve until the processing task of the thin-walled part is completed.

2. A method for processing thin-walled parts according to claim 1, characterized in that: Before obtaining the feed current curve of the tool feed motor during each cutting process, the method further includes: Determining whether a no-load current exists in the feed current of the tool feed motor when continuous cutting processing is performed under current cutting parameters and a current cutting trajectory; If so, clear the curve data recorded in the current cutting track, and continue to determine whether the feed current of the next cutting track has a no-load current; If not, the feed current curve corresponding to the current cutting trajectory is marked as the initial recorded curve of the multiple cutting processes.

3. A method for processing thin-walled parts according to claim 1, characterized in that: Before obtaining the feed current curve of the tool feed motor during each cutting process, the method further includes: According to the cutting force change characterized by the abnormality of the material of the part blank, a trial cutting rate curve of the part blank is configured, wherein the trial cutting rate curve is a curve showing the feed rate of the tool feed motor changing along the trial cutting trajectory; According to the heat impact threshold of the qualified section of the part blank during thin-wall machining and the heat impact results of different cutting parameters, the test cutting parameters of the qualified section are obtained, wherein the test cutting parameters include the test cutting speed and the test cutting depth; Performing a test cutting task on the qualified section according to the test cutting rate curve and the test cutting parameters to obtain test cutting current data fed back by the tool feed motor; Cutting parameters of the multiple cutting processes are obtained based on the trial cutting current data and the minimum fluctuating current characterized by the part blank when the material is abnormal.

4. A method for processing thin-walled parts according to claim 1, characterized in that: Judging whether there is an abnormal area in the part blank of the thin-walled part based on the change characteristics of the plurality of feed current curves in the same trajectory interval specifically includes the following steps: Dividing the plurality of feed current curves into a plurality of trajectory intervals according to fluctuation characteristics presented by the plurality of feed current curves; Obtaining similarities between multiple curve segments within the same trajectory interval based on curve slopes of the multiple feed current curves having the same monotonic characteristics within the same trajectory interval; When the similarity between the multiple curve segments in the same trajectory interval is greater than a preset value, it is determined that the area where the part blank is located in the corresponding trajectory interval is an abnormal area.

5. A method for processing thin-walled parts according to claim 1, characterized in that: Determining the abnormal type of the abnormal area according to the change characteristics of the abnormal area represented by the multiple feed current curves specifically includes the following steps: Obtaining the fluctuation frequency and maximum fluctuation mean of each curve segment according to the curve segment change characteristics corresponding to the abnormal area of ​​the plurality of feed current curves, wherein the maximum fluctuation mean is the average value of all maximum peak currents on the curve segment; When the fluctuation frequency is less than a first threshold and the maximum fluctuation mean is greater than a second threshold, determining that the abnormality type of the abnormal area is a hardness distribution difference; When the fluctuation frequency is greater than or equal to a first threshold and the maximum fluctuation mean is less than or equal to a second threshold, it is determined that the abnormal type of the abnormal area is residual stress distribution difference.

6. A method for processing thin-walled parts according to claim 1, characterized in that: The remaining material of the thin-walled part is cut according to the target feed curve. Specifically, when the tool enters the abnormal area, dynamic compensation is performed based on the deviation value ΔI between the feed current data collected in real time and the target feed curve.

7. A method for processing thin-walled parts according to claim 1, characterized in that: When cutting the remaining material of the thin-walled part according to the target feed curve, it also includes: establishing a transition processing zone at the boundary of the abnormal area, using progressive cutting parameter adjustment in the transition processing zone, and introducing axial compensation, and the compensation direction is opposite to the cutting force direction.

8. A processing system for thin-walled parts, characterized in that: The processing system is used to implement the processing method of the thin-walled parts described in any one of claims 1 to 7, and the processing system includes: An acquisition module is used to perform multiple cutting operations on the part blank with the same cutting parameters and cutting trajectory before finishing the thin-walled part, so as to obtain a feed current curve for each cutting operation, wherein the feed current curve is a curve showing the feed current of the tool feed motor changing with the cutting trajectory; A judgment module, configured to judge whether there is an abnormal area of ​​the part blank on the cutting trajectory based on the change characteristics of multiple feed current curves in the same trajectory interval; a generating module, configured to generate a target feed curve for the thin-walled part according to at least one feed current curve when the abnormal area exists in the part blank, wherein the target feed curve is a curve showing a feed rate of the tool feed motor varying with a cutting trajectory; A processing module is used to cut the remaining material of the thin-walled part according to the target feed curve until the processing task of the thin-walled part is completed.

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