A surface polishing method for automotive parts

Abstract

This invention relates to the field of automotive parts polishing technology, and more particularly to a surface polishing method for automotive parts. The method includes: dividing the surface into analysis areas before polishing and identifying near-surface defect characteristics and hardness distribution characteristics; calculating the risk coefficient of the area based on this and the thickness to be removed, and performing rapid polishing or stable polishing; monitoring vibration during polishing and calculating the vibration wavelength matching degree to determine surface quality; for unqualified areas, adjusting process parameters according to the ripple depth for secondary polishing; verifying the control effect by calculating the ripple removal index, and initiating a multi-level optimization strategy if the target is not met; finally, determining the part's qualification by comparing the actual thickness with the thickness to be removed, thus completing the polishing process. This invention solves the problem of poor polishing quality caused by latent defects near the surface of the parts to be polished and uneven hardness distribution of the surface material.

Description

Technical Field

[0001] This invention relates to the field of automotive parts polishing technology, and more particularly to a surface polishing method for automotive parts. Background Technology

[0002] Traditional polishing methods for automotive parts suffer from poor surface quality consistency and are prone to defects due to the inability to predict the risks of microscopic material inhomogeneities and the lack of real-time monitoring and closed-loop control of process chatter. Furthermore, they struggle to balance efficiency and dimensional accuracy during rework. This invention aims to solve the problem of simultaneously achieving material risk avoidance, process chatter suppression, and precise control of material removal in a single polishing process, thereby achieving synergistic optimization of quality, efficiency, and accuracy.

[0003] Therefore, there is an urgent need for a polishing method that can integrate early risk assessment, online intelligent process monitoring, and adaptive closed-loop control to solve the aforementioned long-standing technical problems and achieve simultaneous improvement in the quality and efficiency of automotive parts surface polishing.

[0004] Chinese Patent Publication No. CN118720987A discloses an automotive parts grinding and polishing device and its usage method, belonging to the field of automotive parts polishing. The device includes a worktable, a clamping mechanism, a grinding mechanism, a push rod assembly, a connecting assembly, and a cleaning mechanism. The worktable features a sliding clamping mechanism to hold the automotive parts, and a grinding mechanism to grind and polish the edges and burrs of the parts. Grinding is performed after the parts are fixed by the clamping mechanism to ensure the stability and safety of the grinding process. A connecting assembly on the fixing frame and a push rod assembly on the clamping plate control the grinding timing, ensuring the stability and safety of the grinding process. A cleaning mechanism on the worktable removes iron powder from the parts, preventing iron powder accumulation and ensuring that repeated grinding does not cause iron powder to adhere to the polishing wheel, thus reducing its service life.

[0005] Therefore, the aforementioned automotive parts grinding and polishing device and its method have the problem that the polishing process does not take into account the actual near-surface defects of the parts and the uneven distribution of material hardness on the surface of the parts. It cannot automatically polish automotive parts with uneven microscopic material hardness and complex geometric features, resulting in poor surface quality and low polishing efficiency of the polished parts. Summary of the Invention

[0006] Therefore, the present invention provides a surface polishing method for automotive parts, which overcomes the problems in the prior art where the near-surface of the parts to be polished has hidden defects and the uneven hardness distribution of the surface material causes system vibration, resulting in poor quality during the polishing process.

[0007] To achieve the above objectives, the present invention provides a surface polishing method for automotive parts. It includes:

[0008] The automotive parts to be polished are divided into several surface analysis regions, and the regional defect characteristic parameters and surface hardness distribution parameters of the near-surface layer below the surface of several surface analysis regions are identified.

[0009] Based on the regional defect characteristic parameters and the regional hardness distribution parameters, combined with the thickness to be removed by polishing, a comprehensive risk coefficient characterizing the polishing risk of several surface analysis regions is determined, so as to determine the risk type of several surface analysis regions, and fast polishing and stable polishing are performed in combination with the risk type;

[0010] The theoretical vibration wavelength and the actual vibration wavelength of the surface ripples after the initial polishing are obtained. The wavelength matching degree is determined based on the theoretical vibration wavelength and the actual vibration wavelength, so as to determine whether the initial polishing quality is qualified according to the wavelength matching degree.

[0011] Based on the first contour ripple depth corresponding to the actual vibration wavelength, the spindle speed and feed rate are simultaneously reduced and the polishing path is switched to perform secondary targeted polishing on the surface area with vibration ripples.

[0012] The actual ripple removal index is determined based on the adjusted second contour ripple depth and the first contour ripple depth to determine whether the current adjustment is qualified.

[0013] Based on the absolute difference between the actual ripple removal index and the preset removal index, determine to simultaneously reduce the spindle speed and feed rate, increase the polishing path overlap rate, and calibrate the clamping force of the lathe for the automotive parts to be polished and the grinding head, and reset the polishing parameters.

[0014] The actual polishing removal thickness of the automotive parts to be polished is obtained to determine whether the automotive parts meet the process standards after polishing, thus completing the polishing process.

[0015] Furthermore, the process of determining the risk type of several of the surface analysis areas to execute a rapid polishing strategy and a stable polishing strategy includes,

[0016] The defect risk factor is calculated based on the average defect signal intensity, defect point distribution density, abnormal signal peak value, and the thickness to be polished and removed.

[0017] The hardness fluctuation factor is calculated based on the regional average hardness value, the regional maximum and minimum hardness values, and the regional hardness standard deviation.

[0018] The comprehensive risk coefficient is obtained by weighted summation of the defect risk factors and the defect risk factors.

[0019] The comprehensive risk coefficient is compared with the preset comprehensive risk coefficient;

[0020] Based on the comprehensive risk coefficient being less than or equal to the preset comprehensive risk coefficient, the current surface analysis area is determined to be a low-risk area. The rapid polishing strategy is then executed, which includes a spindle speed and feed rate that are both higher than the reference speed and feed rate, a polishing depth of 80% of the reference depth of cut, and a unidirectional feed polishing path.

[0021] Furthermore, the process of determining the risk type of several of the surface analysis regions to execute rapid polishing strategies and stable polishing strategies also includes,

[0022] Based on the fact that the comprehensive risk coefficient is greater than the preset comprehensive risk coefficient, the current surface analysis area is determined to be a high-risk area. The stable polishing strategy is then executed, which involves executing a spindle speed and feed rate that are both lower than the reference speed and feed rate, a polishing depth of 60% of the reference depth, and a reciprocating grating path with a high overlap rate of 70%.

[0023] Furthermore, the process of determining whether the initial polishing quality is qualified based on the wavelength matching degree includes,

[0024] The vibration time-domain signal during the polishing process is acquired in real time, and the inherent characteristic frequency peaks are extracted.

[0025] Obtain the linear velocity of the current polished surface of the automotive part relative to the polishing tool;

[0026] The theoretical tremor wavelength is calculated based on the inherent characteristic frequency peak and the linear velocity.

[0027] Obtain the actual vibration wavelength of the ripples on the polished surface;

[0028] The wavelength matching degree is calculated based on the theoretical tremor wavelength and the actual tremor wavelength.

[0029] The wavelength matching degree is compared with the preset matching degree;

[0030] Based on the wavelength matching degree being greater than the preset matching degree, it is determined that the initial polishing quality is unqualified.

[0031] Furthermore, the process of simultaneously reducing the spindle speed and feed rate and switching the polishing path to perform secondary targeted polishing on the surface area with vibration ripples, based on the first contour ripple depth corresponding to the actual vibration wavelength, includes:

[0032] Obtain the contour height data of the polished surface;

[0033] Extract the periodic ripple component corresponding to the actual flutter wavelength from the contour height data;

[0034] The average peak-valley height difference of the periodic ripple components is calculated as the first profile ripple depth.

[0035] The depth of the first contour ripple is compared with the preset contour ripple depth.

[0036] Based on the fact that the first contour ripple depth is less than the preset contour ripple depth, it is determined that the spindle speed and feed rate should be reduced simultaneously, while the polishing depth remains unchanged.

[0037] Furthermore, the process of simultaneously reducing the spindle speed and feed rate and switching the polishing path to perform secondary targeted polishing on the surface area with vibration ripples, based on the first contour ripple depth corresponding to the actual vibration wavelength, also includes...

[0038] Based on the fact that the first contour ripple depth is greater than or equal to the preset contour ripple depth, it is determined to simultaneously reduce the spindle speed and feed rate, switch the polishing path, and reduce the polishing depth.

[0039] Furthermore, the process of determining whether the current regulation is adequate includes,

[0040] Obtain the second profile ripple depth corresponding to the actual vibration wavelength after adjustment;

[0041] The actual ripple removal index is calculated based on the second contour ripple depth and the first contour ripple depth.

[0042] The actual ripple removal index is compared with the preset removal index;

[0043] Based on the fact that the actual ripple removal index is less than the preset removal index, the current control is determined to be unqualified.

[0044] Furthermore, the process of simultaneously reducing the spindle speed and feed rate, increasing the polishing path overlap rate, and calibrating the clamping force of the lathe for the automotive parts to be polished and the grinding head, based on the absolute difference between the actual ripple removal index and the preset removal index, and resetting the polishing parameters, includes:

[0045] The absolute difference is compared with a preset absolute difference.

[0046] Based on the fact that the absolute difference is less than or equal to the preset absolute difference, it is determined that there is only a slight deviation after adjustment. The spindle speed and feed rate are further reduced, and the overlap rate of the polishing path is increased.

[0047] Furthermore, the process of simultaneously reducing the spindle speed and feed rate, increasing the polishing path overlap rate, and calibrating the clamping force of the lathe for the automotive parts to be polished and the grinding head, based on the absolute difference between the actual ripple removal index and the preset removal index, and resetting the polishing parameters, also includes...

[0048] If the absolute difference is greater than the preset absolute difference, it is determined that there is still a large deviation after adjustment. The clamping force of the hydraulic chuck on the automotive parts to be polished and the grinding head, as well as the clamping force of the tool holder on the milling cutter, are recalibrated, and the polishing parameters are reset.

[0049] Furthermore, the process of determining whether the automotive parts meet the process standards after polishing includes the following steps:

[0050] Obtain initial values ​​for key feature dimensions used to control the final dimensions before polishing;

[0051] Obtain the final polishing values ​​of the same set of key feature dimensions of automotive parts after polishing is completed;

[0052] The actual polishing removal thickness is calculated based on the initial value and the final polishing value.

[0053] The actual polishing removal thickness is compared with the thickness to be polished and removed;

[0054] Based on the fact that the actual polishing removal thickness is less than or equal to the thickness to be polished, it is determined that the automotive parts after polishing meet the process standards, and polishing is completed.

[0055] Based on the fact that the actual polishing removal thickness is greater than the thickness to be polished, it is determined that the automotive parts after polishing do not meet the process standards and are therefore rejected.

[0056] Compared with existing technologies, the beneficial effects of this invention are as follows: by integrating online detection of near-surface defects and hardness distribution, this invention achieves accurate quantitative early warning of risks before polishing; furthermore, by comparing vibration signals and surface ripples in real time, and using vibration wavelength matching degree and ripple depth as the core dynamic criteria for process quality, a closed-loop control system from feature source diagnosis to exponential removal verification is constructed. Ultimately, under the premise of strictly ensuring that the material removal amount does not exceed the tolerance, regular surface defects caused by material inhomogeneity or system chatter are effectively suppressed, significantly improving the consistency, process stability and first-pass yield of polishing quality of complex automotive parts made of heterogeneous materials.

[0057] Furthermore, this invention achieves efficient and quantitative detection of near-surface defects and surface hardness distribution in automotive parts through in-situ scanning of pulsed eddy currents and ultrasonic contact impedance. Based on this, a defect risk factor is constructed that integrates defect signal intensity, distribution density, and correlation with removal thickness, as well as a hardness fluctuation factor characterizing the degree of hardness dispersion. The surface area is then accurately risk-classified using a comprehensive risk coefficient. Finally, based on the risk level, two sets of differentiated process parameters and path strategies—rapid polishing and stable polishing—are automatically matched. This transforms traditional experience-based blind polishing into intelligent polishing driven by data on the intrinsic properties of the material, effectively suppressing quality problems such as polishing vibration and surface peeling caused by material inhomogeneity or subsurface defects. While ensuring that the thickness to be polished does not exceed the required removal thickness, the first-pass yield, stability, and overall efficiency of the polishing process for complex heterogeneous material parts are significantly improved.

[0058] Furthermore, this invention acquires polishing vibration signals in real time and extracts inherent characteristic frequency peaks, then calculates the theoretical chatter wavelength by combining it with the processing line speed. Simultaneously, it uses a laser confocal sensor to scan and obtain the actual chatter wavelength of surface ripples, and then calculates the wavelength matching degree between the two to achieve an objective and quantitative determination of whether harmful chatter occurs during the polishing process. This transforms the traditional surface evaluation, which relies on subjective experience or roughness results, into a scientific diagnosis based on the causal relationship between vibration and morphology. It can accurately identify regular surface defects caused by material inhomogeneity or process instability, providing a precise basis for subsequent targeted control, thereby improving the stability of the polishing process and the consistency of surface quality from the source.

[0059] Furthermore, this invention classifies the severity of vibration problems detected after the initial polishing based on the quantitative index of the depth of the contour ripple, and triggers differentiated, step-by-step adaptive control strategies accordingly. For shallower ripples, a gentle correction is adopted, mainly by reducing speed and feed rate, to suppress the vibration source while ensuring efficiency. For deeper or more significant ripples, a combination of stronger intervention, including more significant parameter reduction, depth reduction, and path optimization, is implemented to completely break the vibration regeneration cycle. This overcomes the limitation of traditional polishing, which can only rely on experience to make single adjustments when facing vibration, and achieves precise and efficient compensation for different degrees of process instability, significantly improving the first-pass yield and process robustness of polishing complex parts.

[0060] Furthermore, this invention establishes a secondary polishing effect verification mechanism using the ripple removal index as a quantitative indicator and introduces absolute difference as a decision-making basis, forming a multi-level, closed-loop adaptive optimization system. This system can accurately evaluate the effectiveness of control strategies and automatically match gradient response schemes from parameter fine-tuning to system checks and extremely conservative process restarts based on the degree of deviation, ensuring that even in the face of stubborn vibrations, the quality target can be approached iteratively. Finally, combined with the final inspection of the actual polishing removal thickness, while successfully eliminating surface ripples, the dimensional accuracy of the parts is strictly guaranteed, achieving intelligent control that meets both surface integrity and geometric dimensions. This significantly reduces the scrap rate caused by over-polishing or process loss of control, and improves the predictability and robustness of the process. Attached Figure Description

[0061] Figure 1 This is a schematic diagram illustrating the steps of a surface polishing method for automotive parts according to an embodiment of the present invention;

[0062] Figure 2 This is a logic block diagram illustrating how an embodiment of the present invention determines the risk type of several surface analysis regions based on a comprehensive risk coefficient and executes a corresponding partitioned polishing strategy.

[0063] Figure 3 This is a logic block diagram of an embodiment of the present invention for determining and executing a corresponding control strategy based on the contour ripple depth;

[0064] Figure 4 This is a logic block diagram illustrating how an embodiment of the present invention determines the corresponding optimization strategy based on the absolute difference between the actual ripple removal index and the preset removal index. Detailed Implementation

[0065] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0066] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0067] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0068] Please see Figure 1As shown, it is a schematic diagram of the steps of a surface polishing method for automotive parts according to an embodiment of the present invention.

[0069] The present invention provides a surface polishing method for automotive parts, comprising:

[0070] Step S1: Divide the automotive parts to be polished into several surface analysis areas. Along the C-axis and Z-axis of the lathe, identify the regional defect characteristic parameters of the near-surface layer below the surface of several surface analysis areas using a pulsed eddy current probe and identify the regional hardness distribution parameters of the surface of several surface analysis areas using an ultrasonic contact impedance sensor.

[0071] Step S2: Based on the identified regional defect feature parameters and regional hardness distribution parameters of each of the surface analysis regions, as well as the thickness to be polished and removed, obtain the defect risk factor and hardness fluctuation factor, and calculate the comprehensive risk coefficient characterizing the polishing risk of several surface analysis regions based on the defect risk factor and the hardness fluctuation factor. Determine the risk type of several surface analysis regions according to the comprehensive risk coefficient, and execute the corresponding partitioned polishing strategy.

[0072] Step S3: During the polishing process, a triaxial accelerometer installed on the lathe spindle box and tool post collects the vibration time-domain signal of the polishing process in real time and extracts the inherent characteristic frequency peak. Based on the inherent characteristic frequency peak and the current polishing linear velocity, the theoretical vibration wavelength is calculated. After the initial polishing is completed, a laser confocal sensor performs a micro-area scan along the polishing path direction of the surface analysis area to obtain the actual vibration wavelength of the surface ripples. The quality of the initial polishing is determined based on the wavelength matching degree between the actual vibration wavelength and the theoretical vibration wavelength.

[0073] Step S4: If the initial polishing quality is found to be unqualified, determine and execute the corresponding control strategy based on the comparison result between the first contour ripple depth corresponding to the actual vibration wavelength and the preset ripple depth, so as to perform secondary targeted polishing on the surface area with vibration ripples.

[0074] Step S5: During the secondary targeted polishing process, the surface analysis area undergoing secondary polishing is scanned again using the laser confocal sensor to obtain the second contour ripple depth corresponding to the actual vibration wavelength after adjustment, and the actual ripple removal index is calculated to determine whether the current adjustment is qualified based on the actual ripple removal index.

[0075] Step S6: Under the condition that the current regulation is unqualified, determine the corresponding optimization strategy to be executed based on the absolute difference between the actual ripple removal index and the preset removal index.

[0076] Step S7: After optimization, obtain the actual polishing removal thickness of the automotive parts to be polished, and determine whether the final polished automotive parts meet the process standards based on the actual polishing removal thickness and the removal thickness to be polished, and complete the polishing.

[0077] Specifically, this invention achieves precise quantitative early warning of pre-polishing risks by integrating online detection of near-surface defects and hardness distribution. Furthermore, through real-time comparison of vibration signals and surface ripples, and using vibration wavelength matching degree and ripple depth as the core dynamic criteria for process quality, a closed-loop control system from feature source diagnosis to exponential removal verification is constructed. Ultimately, under the premise of strictly ensuring that the material removal amount does not exceed the tolerance, regular surface defects caused by material inhomogeneity or system chatter are effectively suppressed, significantly improving the consistency, process stability, and first-pass yield of polishing quality of complex automotive parts made of heterogeneous materials.

[0078] In this embodiment of the invention, the specific process of dividing the automotive parts to be polished into several surface analysis regions in step S1 is as follows: First, the CAD three-dimensional model of the automotive parts to be polished is imported into the system; then, the system automatically partitions the surfaces based on curvature changes, feature boundaries, and process accessibility; continuous surfaces with gentle curvature changes, such as planes and cylindrical surfaces, are divided into independent analysis regions; locations where the curvature of the surface changes abruptly, such as fillet transitions, and intersections of different features, such as the intersection of a plane and a hole wall, are designated as another independent analysis region; simultaneously, feature surfaces with poor tool accessibility, such as deep cavities and slits, are divided into yet another independent analysis region; finally, the surface of the parts is divided into several non-overlapping continuous analysis regions and assigned a unique identifier.

[0079] In this embodiment of the invention, the specific process of obtaining the regional defect characteristic parameters in step S1 is as follows: after completing the regional division, the pulsed eddy current probe is installed on the lathe turret, and the probe is controlled to perform grating scanning along the C-axis and Z-axis of the lathe; during the scanning process, the probe emits high-frequency electromagnetic pulses and receives eddy current distortion signals caused by pores, inclusions, and microcracks in the near-surface layer of the workpiece; the system records the signal amplitude attenuation and phase shift at each measurement point in real time.

[0080] After scanning, the system first normalizes the signal amplitude attenuation and phase shift, and then sets a joint threshold based on a statistical confidence interval, such as a 95% confidence level, to screen out suspected defect points. Secondly, it performs spatial clustering analysis on the suspected defect points based on their location coordinates, grouping nearby anomalies into potential defect domains representing the same physical defect. Finally, based on the clustering analysis results, it performs statistical calculations and outputs the defect characteristic parameters of the region, including: the arithmetic mean of the normalized amplitude attenuation of all suspected defect points, as the average defect signal strength; the proportion of suspected defect points to the total number of measurement points in the region, as the defect point distribution density; and the maximum comprehensive signal strength extracted from all potential defect domains, as the peak value of the anomalous signal characterizing the largest potential defect size.

[0081] In this embodiment of the invention, the specific process for obtaining the regional hardness distribution parameters in step S1 is as follows: First, the ultrasonic contact impedance sensor is replaced and installed at the original probe position of the lathe turret; a 5mm×5mm equally spaced grid is set in each region, and measurement points are selected; each measurement point is positioned sequentially, and a constant small contact force of 5N is applied to excite ultrasonic waves and, based on the principle of ultrasonic contact impedance, its contact resonance frequency is accurately measured; there is a hardness-frequency conversion relationship between the contact resonance frequency and the micro Vickers hardness value of the material surface obtained through pre-calibration using a standard hardness block, thus obtaining the micro Vickers hardness value at that point; after all measurements are completed, the hardness measurement values ​​in each region are statistically analyzed to obtain the hardness distribution parameters, including: the regional average hardness value, the regional maximum and minimum hardness values, and the regional hardness standard deviation; finally, a color cloud map of the hardness distribution of the entire component surface is generated using a spatial interpolation algorithm.

[0082] Please see Figure 2 As shown, it is a logic block diagram of an embodiment of the present invention that determines the risk type of several surface analysis areas based on a comprehensive risk coefficient and executes the corresponding partitioned polishing strategy.

[0083] Specifically, based on the regional defect characteristic parameters and regional hardness distribution parameters of each identified surface analysis region, as well as the thickness to be removed during polishing, a defect risk factor and a hardness fluctuation factor are obtained. A comprehensive risk coefficient characterizing the polishing risk of several surface analysis regions is calculated based on the defect risk factor and the hardness fluctuation factor. The risk type of several surface analysis regions is determined according to the comparison result between the comprehensive risk coefficient and a preset comprehensive risk coefficient, and a corresponding zoned polishing strategy is executed.

[0084] If the comprehensive risk coefficient is less than or equal to the preset comprehensive risk coefficient, the current surface analysis area is determined to be a low-risk area, and a rapid polishing strategy is executed.

[0085] If the overall risk coefficient is greater than the preset overall risk coefficient, the current surface analysis area is determined to be a high-risk area, and a stable polishing strategy is executed.

[0086] In this embodiment of the invention, the specific process for obtaining the defect risk factor is as follows: First, normalization processing is performed, dividing the average defect signal intensity by the maximum defect signal intensity in the current automotive parts to be polished to obtain the normalized average defect signal intensity Savg, and dividing the thickness to be polished by the average thickness to be removed of all automotive parts to be polished in the current batch to obtain the normalized thickness to be polished Tnorm. Then, the defect risk factor is calculated using the following formula.

[0087]

[0088] In the formula, As a defect risk factor, The normalized average signal intensity of the defect. The density of defect points. This is an abnormal signal peak value. The normalized thickness to be removed during polishing. This is the weighting coefficient for the normalized average defect signal intensity, with a value of 0.4. This is the weighting coefficient for the defect point distribution density, with a value of 0.3. for The weighting coefficient is 0.3.

[0089] In this embodiment of the invention, the hardness fluctuation factor is calculated according to the following formula:

[0090]

[0091] In the formula, This is the hardness fluctuation factor. This represents the average hardness value for the region. The standard deviation of regional hardness. This represents the maximum regional hardness. This represents the minimum regional hardness. is the adjustment coefficient, and is a constant with a value range of 0.1 to 0.3, preferably 0.2.

[0092] In this embodiment of the invention, the comprehensive risk coefficient is calculated according to the following formula:

[0093]

[0094] In the formula, To assess the overall risk factor, As a defect risk factor, This is the hardness fluctuation factor. This is a weighting coefficient, with a value ranging from 0.7 to 0.9, preferably 0.8.

[0095] In this embodiment of the invention, the preset comprehensive risk coefficient ranges from 0.3 to 0.5, preferably 0.4. The preferred range and preferred value can be determined according to the actual situation, and are not specifically limited here.

[0096] In this embodiment of the invention, the rapid polishing strategy aims primarily at high efficiency. The rapid polishing strategy involves executing spindle speeds and feed rates higher than the reference values, as well as a polishing depth of 80% of the reference depth. For example, a spindle speed 20%–30% higher than the reference speed is used as the spindle speed for the rapid polishing strategy, and a feed rate 15%–25% higher than the reference feed rate is used as the feed rate for the rapid polishing strategy. A simplified unidirectional feed path is also executed.

[0097] In this embodiment of the invention, the stable polishing strategy takes stability as its main objective, and executes spindle speed, feed rate and polishing depth of cut all lower than the reference values. For example, it executes 70% to 90% of the reference speed, preferably 80%, as the spindle speed, 50% to 70% of the reference feed rate, preferably 60%, as the feed rate, and 60% of the reference depth of cut as the polishing depth, and executes a reciprocating grating path with a high overlap rate, for example, an overlap rate of 70%.

[0098] The reference rotation speed, the reference feed rate, and the reference depth of cut are a set of standard process parameters that can obtain a basically qualified surface, determined based on the material type and initial surface condition of the automotive parts to be polished, and the standard finishing process manual or previous process tests of the current material. It can be understood that the reference depth of cut is usually less than or equal to the thickness to be removed during polishing.

[0099] Specifically, this invention achieves efficient and quantitative detection of near-surface defects and surface hardness distribution in automotive parts through in-situ scanning of pulsed eddy currents and ultrasonic contact impedance. Based on this, a defect risk factor is constructed that integrates defect signal intensity, distribution density, and correlation with removal thickness, as well as a hardness fluctuation factor characterizing the degree of hardness dispersion. The surface area is then accurately classified into risk levels using a comprehensive risk coefficient. Finally, based on the risk level, two sets of differentiated process parameters and path strategies—rapid polishing and stable polishing—are automatically matched. This transforms traditional experience-based blind polishing into intelligent polishing driven by data on the intrinsic properties of the material, effectively suppressing quality problems such as polishing vibration and surface peeling caused by material inhomogeneity or subsurface defects. While ensuring that the thickness to be polished does not exceed the required removal thickness, the first-pass yield, stability, and overall efficiency of the polishing process for complex heterogeneous material parts are significantly improved.

[0100] Specifically, during the polishing process, triaxial accelerometers mounted on the lathe spindle box and tool post collect vibration time-domain signals in real time, extracting inherent characteristic frequency peaks. Based on these inherent characteristic frequency peaks and the current linear velocity of the polished automotive parts, the theoretical vibration wavelength is calculated. After the initial polishing, a laser confocal sensor performs a micro-area scan along the polishing path of the surface analysis area to obtain the actual vibration wavelength of the surface ripples. The quality of the initial polishing is determined by comparing the wavelength matching degree between the actual vibration wavelength and the theoretical vibration wavelength with a preset matching degree.

[0101] If the wavelength matching degree is less than or equal to the preset matching degree, the initial polishing quality is determined to be qualified.

[0102] If the wavelength matching degree is greater than the preset matching degree, the initial polishing quality is determined to be unqualified.

[0103] In this embodiment of the invention, the theoretical tremor wavelength is calculated according to the following formula:

[0104] λtheory=V / fchatter

[0105] In the formula, λtheory is the theoretical vibration wavelength, fchatter is the inherent characteristic frequency peak, and V is the current linear velocity of the polished surface of the automotive part, that is, the linear velocity of the polished surface of the automotive part relative to the polishing tool.

[0106] The inherent characteristic frequency peaks are obtained by performing a fast Fourier transform on the vibration time-domain signal to obtain the frequency domain spectrum; and inherent characteristic frequency peaks that are independent of the main shaft rotation frequency and its harmonics and whose amplitudes are significantly higher than the background noise are extracted from the frequency domain spectrum.

[0107] In this embodiment of the invention, the actual flutter wavelength is calculated according to the following formula:

[0108] λactual=fsurface / 1

[0109] In the formula, λactual is the actual flutter wavelength, and fsurface is the maximum dominant spatial frequency component.

[0110] Specifically, the maximum dominant spatial frequency component is obtained by performing micro-area scanning along the polishing path direction of the surface analysis area using a laser confocal sensor after the initial polishing, acquiring high-resolution surface contour height data; performing spectral analysis on the contour height data to obtain its spatial frequency spectrum; and extracting the dominant spatial frequency component with the largest amplitude from the spatial frequency spectrum.

[0111] In this embodiment of the invention, the wavelength matching degree is calculated using the following formula:

[0112]

[0113] In the formula, M is the wavelength matching degree, λactual is the actual flutter wavelength, and λtheory is the theoretical flutter wavelength.

[0114] In this embodiment of the invention, the preset matching degree ranges from 0.8 to 0.95, preferably 0.9. The preferred range and preferred value can be determined according to the actual situation, and are not specifically limited here.

[0115] Specifically, this invention acquires polishing vibration signals in real time and extracts inherent characteristic frequency peaks, then calculates the theoretical chatter wavelength by combining it with the processing line speed. Simultaneously, it uses a laser confocal sensor to scan and obtain the actual chatter wavelength of surface ripples, and then calculates the wavelength matching degree between the two to achieve an objective and quantitative determination of whether harmful chatter occurs during the polishing process. This transforms the traditional surface evaluation, which relies on subjective experience or roughness results, into a scientific diagnosis based on the causal relationship between vibration and morphology. It can accurately identify regular surface defects caused by material inhomogeneity or process instability, providing a precise basis for subsequent targeted control, thereby improving the stability of the polishing process and the consistency of surface quality from the source.

[0116] Please see Figure 3 As shown, it is a logic block diagram of an embodiment of the present invention for determining and executing the corresponding control strategy based on the contour ripple depth.

[0117] Specifically, if the initial polishing quality is determined to be substandard, a corresponding control strategy is executed based on the comparison between the first contour ripple depth corresponding to the actual vibration wavelength and the preset contour ripple depth. This strategy is used to perform a secondary targeted polishing on the surface area with vibration ripples.

[0118] If the depth of the first contour ripple is less than the preset contour ripple depth, then the first control strategy is determined to be executed.

[0119] If the depth of the first contour ripple is greater than or equal to the preset contour ripple depth, then the second control strategy is determined to be executed.

[0120] In this embodiment of the invention, the first contour ripple depth is obtained by extracting the periodic ripple component corresponding to the actual vibration wavelength from the contour height data of the surface obtained by scanning the laser confocal sensor, and calculating the average peak-valley height difference of the periodic ripple component as the first contour ripple depth.

[0121] In this embodiment of the invention, the preset contour ripple depth ranges from 1μm to 2μm, preferably 1.5μm. The preferred range and preferred value can be determined according to the actual situation, and are not specifically limited here.

[0122] In this embodiment of the invention, the first control strategy is to reduce the spindle speed by 10% to 20%, preferably 15%, and the feed rate by 20% to 30%, preferably 25%, based on the polishing parameters corresponding to the partitioned polishing strategy executed in the initial polishing, so as to perform secondary targeted polishing on the surface area with vibration ripples.

[0123] In this embodiment of the invention, the second control strategy is to reduce the spindle speed by 15% to 25%, preferably 20%, and the feed rate by 25% to 35%, preferably 30%, based on the polishing parameters corresponding to the partitioned polishing strategy executed in the initial polishing, and reduce the polishing depth to 40% to 50%, preferably 45%, of the original value; at the same time, if a simplified path of unidirectional feed is executed, the polishing path mode is switched to a reciprocating grating path with a high overlap rate; if the polishing path corresponding to the stable polishing strategy is executed, it is maintained, so as to perform secondary targeted polishing on the surface area with vibration ripples.

[0124] Specifically, this invention classifies the severity of vibration problems detected after the initial polishing based on the quantitative index of the first contour ripple depth, and triggers differentiated, step-by-step adaptive control strategies accordingly. For shallower ripples, a gentle correction is adopted, mainly by reducing speed and feed rate, to suppress vibration sources while ensuring efficiency. For deeper or more significant ripples, a combination of stronger intervention, including more significant parameter reduction, depth reduction, and path optimization, is implemented to completely break the vibration regeneration cycle. This overcomes the limitation of traditional polishing, which can only rely on experience to make single adjustments when facing vibration, and achieves precise and efficient compensation for different degrees of process instability, significantly improving the first-pass yield and process robustness of polishing complex parts.

[0125] Specifically, after completing the secondary targeted polishing process, the surface analysis area where the secondary polishing was performed is scanned again using the laser confocal sensor to obtain the second contour ripple depth corresponding to the adjusted actual vibration wavelength, and the actual ripple removal index is calculated. The current adjustment is then determined to be satisfactory based on the comparison between the actual ripple removal index and the preset removal index.

[0126] If the actual ripple removal index is less than the preset removal index, then the current control is determined to be unqualified.

[0127] If the actual ripple removal index is greater than or equal to the preset removal index, then the current control is deemed qualified.

[0128] In this embodiment of the invention, the actual ripple removal index is calculated according to the following formula:

[0129]

[0130] In the formula, η is the actual ripple removal index, Dtremor is the first profile ripple depth, and Dtremor_post is the second profile ripple depth.

[0131] In this embodiment of the invention, the preset removal index ranges from 85% to 95%, preferably 90%. The preferred range and preferred value can be determined according to the actual situation, and are not specifically limited here.

[0132] Please see Figure 4 As shown, it is a logic block diagram of an embodiment of the present invention that determines the corresponding optimization strategy based on the absolute difference between the actual ripple removal index and the preset removal index.

[0133] Specifically, if the current control is determined to be unqualified, a corresponding optimization strategy is determined based on the comparison between the absolute difference between the actual ripple removal index and the preset removal index and the preset absolute difference.

[0134] If the absolute difference is less than or equal to the preset absolute difference, it is determined that there is only a slight deviation after adjustment, and the first optimization strategy is executed.

[0135] If the absolute difference is greater than the preset absolute difference, it is determined that there is still a large deviation after adjustment, and the second optimization strategy is executed.

[0136] In this embodiment of the invention, the absolute difference is the difference between the actual ripple removal index and the preset removal index.

[0137] In this embodiment of the invention, the preset absolute difference ranges from 3% to 8%, preferably 5%. The preferred range and preferred value can be determined according to the actual situation, and are not specifically limited here.

[0138] In this embodiment of the invention, the first optimization strategy is based on the first control strategy and the second control strategy, that is, the spindle speed is further reduced by 5% to 10%, preferably 8%, the feed rate is further reduced by 5% to 15%, preferably 10%, and a reciprocating grating path with a higher overlap rate is adopted, for example, an overlap rate of 85%.

[0139] In this embodiment of the invention, the second optimization strategy is to stop the current polishing, manually check whether the clamping force of the hydraulic chuck on the automotive parts has changed and whether the grinding head is loose, and recalibrate the clamping force of the hydraulic chuck and the clamping force on the grinding head. Then, more conservative polishing parameters are reset, including setting the spindle speed to 40% to 60% of the reference value, preferably 50%, the feed rate to 30% to 40% of the reference value, preferably 35%, the polishing depth to an extremely shallow value, for example, 0.01mm to 0.02mm, and repeating the polishing at least 3 times using a spiral path with an extremely high overlap rate, for example, an overlap rate of 90%.

[0140] Specifically, after optimization, the actual polishing removal thickness of the automotive parts to be polished is obtained. Based on the comparison between the actual polishing removal thickness and the thickness to be polished, it is determined whether the final polished automotive parts meet the process standards, and polishing is completed.

[0141] If the actual polishing removal thickness is less than or equal to the thickness to be polished, then the final polished automotive parts are determined to meet the process standards, and polishing is completed.

[0142] If the actual polishing removal thickness is greater than the thickness to be polished, then the final polished automotive parts are determined to be non-compliant with the process standards and are rejected to complete the polishing process.

[0143] In this embodiment of the invention, the process of obtaining the actual polishing removal thickness is as follows: before the polishing process begins, the clamped parts are measured to obtain the initial values ​​of the key feature dimensions that are directly related to the polishing target surface and are used to control the final dimensions. After polishing, without disassembling the workpiece and under a unified machine tool coordinate system, a non-contact laser displacement sensor mounted on the lathe turret is used to measure the same set of key feature dimensions of the part, such as the outer diameter and end face position, to obtain the final polishing value.

[0144] Understandably, for planar polished surfaces, the actual polishing removal thickness is obtained by directly calculating the difference between the initial value and the final polishing value. For polished surfaces with rotational symmetry, such as outer circles or inner holes, the actual polishing removal thickness is calculated according to the following formula.

[0145]

[0146] In the formula, Tactual is the actual polishing removal thickness, Dinitial is the initial polishing value, and Dfinal is the final polishing value.

[0147] In this embodiment of the invention, the thickness to be removed by polishing is the theoretical value of the total thickness of material that can be removed from the surface of the part as determined by the process planning before polishing. The value can be determined according to the actual situation, and no specific limitation is made here.

[0148] Specifically, this invention establishes a secondary polishing effect verification mechanism using the ripple removal index as a quantitative indicator and introduces absolute difference as a decision-making basis, forming a multi-level, closed-loop adaptive optimization system. It can accurately evaluate the effectiveness of the control strategy and automatically match a gradient response plan from parameter fine-tuning to system inspection and extreme conservative process restart according to the degree of deviation, ensuring that even in the face of stubborn vibrations, it can approach the quality target in the iteration. Finally, combined with the final inspection of the actual polishing removal thickness, it successfully eliminates surface ripples while strictly ensuring the dimensional accuracy of the parts, achieving intelligent control that meets both surface integrity and geometric dimensions, significantly reducing the scrap rate caused by over-polishing or process loss of control, and improving the predictability and robustness of the process.

[0149] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A surface polishing method for automotive parts, characterized in that, include, The automotive parts to be polished are divided into several surface analysis regions, and the regional defect characteristic parameters and surface hardness distribution parameters of the near-surface layer below the surface of several surface analysis regions are identified. Based on the regional defect characteristic parameters and the regional hardness distribution parameters, combined with the thickness to be removed by polishing, a comprehensive risk coefficient characterizing the polishing risk of several surface analysis regions is determined, so as to determine the risk type of several surface analysis regions, and fast polishing and stable polishing are performed in combination with the risk type; The theoretical vibration wavelength and the actual vibration wavelength of the surface ripples after the initial polishing are obtained. The wavelength matching degree is determined based on the theoretical vibration wavelength and the actual vibration wavelength, so as to determine whether the initial polishing quality is qualified according to the wavelength matching degree. Based on the first contour ripple depth corresponding to the actual vibration wavelength, the spindle speed and feed rate are simultaneously reduced and the polishing path is switched to perform secondary targeted polishing on the surface area with vibration ripples. The actual ripple removal index is determined based on the adjusted second contour ripple depth and the first contour ripple depth to determine whether the current adjustment is qualified. Based on the absolute difference between the actual ripple removal index and the preset removal index, determine to simultaneously reduce the spindle speed and feed rate, increase the polishing path overlap rate, and calibrate the clamping force of the lathe for the automotive parts to be polished and the grinding head, and reset the polishing parameters. The actual polishing removal thickness of the automotive parts to be polished is obtained to determine whether the automotive parts meet the process standards after polishing, thus completing the polishing process.

2. The surface polishing method for automotive parts according to claim 1, characterized in that, The process of determining the risk type of several of the surface analysis regions in order to execute a rapid polishing strategy and a stable polishing strategy includes, The defect risk factor is calculated based on the average defect signal intensity, defect point distribution density, abnormal signal peak value, and the thickness to be polished and removed. The hardness fluctuation factor is calculated based on the regional average hardness value, the regional maximum and minimum hardness values, and the regional hardness standard deviation. The comprehensive risk coefficient is obtained by weighted summation of the defect risk factors and the defect risk factors. The comprehensive risk coefficient is compared with the preset comprehensive risk coefficient; Based on the comprehensive risk coefficient being less than or equal to the preset comprehensive risk coefficient, the current surface analysis area is determined to be a low-risk area. The rapid polishing strategy is then executed, which includes a spindle speed and feed rate that are both higher than the reference speed and feed rate, a polishing depth of 80% of the reference depth of cut, and a unidirectional feed polishing path.

3. The surface polishing method for automotive parts according to claim 2, characterized in that, The process of determining the risk type of several of the surface analysis regions in order to implement rapid polishing strategies and stable polishing strategies also includes, Based on the fact that the comprehensive risk coefficient is greater than the preset comprehensive risk coefficient, the current surface analysis area is determined to be a high-risk area. The stable polishing strategy is then executed, which involves executing a spindle speed and feed rate that are both lower than the reference speed and feed rate, a polishing depth of 60% of the reference depth, and a reciprocating grating path with a high overlap rate of 70%.

4. The surface polishing method for automotive parts according to claim 3, characterized in that, The process of determining whether the initial polishing quality is qualified based on the wavelength matching degree includes: The vibration time-domain signal during the polishing process is acquired in real time, and the inherent characteristic frequency peaks are extracted. Obtain the linear velocity of the current polished surface of the automotive part relative to the polishing tool; The theoretical tremor wavelength is calculated based on the inherent characteristic frequency peak and the linear velocity. Obtain the actual vibration wavelength of the ripples on the polished surface; The wavelength matching degree is calculated based on the theoretical tremor wavelength and the actual tremor wavelength. The wavelength matching degree is compared with the preset matching degree; Based on the wavelength matching degree being greater than the preset matching degree, it is determined that the initial polishing quality is unqualified.

5. The surface polishing method for automotive parts according to claim 4, characterized in that, The process of simultaneously reducing the spindle speed and feed rate and switching the polishing path to perform secondary targeted polishing on the surface area with vibration ripples, based on the first contour ripple depth corresponding to the actual vibration wavelength, includes... Obtain the contour height data of the polished surface; Extract the periodic ripple component corresponding to the actual flutter wavelength from the contour height data; The average peak-valley height difference of the periodic ripple components is calculated as the first profile ripple depth. The depth of the first contour ripple is compared with the preset contour ripple depth. Based on the fact that the first contour ripple depth is less than the preset contour ripple depth, it is determined that the spindle speed and feed rate should be reduced simultaneously, while the polishing depth remains unchanged.

6. The surface polishing method for automotive parts according to claim 5, characterized in that, The process of determining the first profile ripple depth corresponding to the actual vibration wavelength, simultaneously reducing the spindle speed and feed rate, and switching the polishing path to perform secondary targeted polishing on the surface area with vibration ripples also includes... Based on the fact that the first contour ripple depth is greater than or equal to the preset contour ripple depth, it is determined to simultaneously reduce the spindle speed and feed rate, switch the polishing path, and reduce the polishing depth.

7. The surface polishing method for automotive parts according to claim 6, characterized in that, The process of determining whether the current regulation is adequate includes, Obtain the second profile ripple depth corresponding to the actual vibration wavelength after adjustment; The actual ripple removal index is calculated based on the second contour ripple depth and the first contour ripple depth. The actual ripple removal index is compared with the preset removal index; Based on the fact that the actual ripple removal index is less than the preset removal index, the current control is determined to be unqualified.

8. The surface polishing method for automotive parts according to claim 7, characterized in that, The process of simultaneously reducing the spindle speed and feed rate, increasing the polishing path overlap rate, and calibrating the clamping force of the lathe for the automotive parts to be polished and the grinding head, based on the absolute difference between the actual ripple removal index and the preset removal index, and resetting the polishing parameters includes: The absolute difference is compared with a preset absolute difference. Based on the fact that the absolute difference is less than or equal to the preset absolute difference, it is determined that there is only a slight deviation after adjustment. The spindle speed and feed rate are further reduced, and the overlap rate of the polishing path is increased.

9. The surface polishing method for automotive parts according to claim 8, characterized in that, The process of determining, based on the absolute difference between the actual ripple removal index and the preset removal index, to simultaneously reduce the spindle speed and feed rate, increase the polishing path overlap rate, and calibrate the clamping force of the lathe for the automotive parts to be polished and the grinding head, and to reset the polishing parameters, also includes... If the absolute difference is greater than the preset absolute difference, it is determined that there is still a large deviation after adjustment. The clamping force of the hydraulic chuck on the automotive parts to be polished and the grinding head, as well as the clamping force of the tool holder on the milling cutter, are recalibrated, and the polishing parameters are reset.

10. The surface polishing method for automotive parts according to claim 9, characterized in that, The process of determining whether the polished automotive parts meet the process standards includes the following steps: Obtain initial values ​​for key feature dimensions used to control the final dimensions before polishing; Obtain the final polishing values ​​of the same set of key feature dimensions of automotive parts after polishing is completed; The actual polishing removal thickness is calculated based on the initial value and the final polishing value. The actual polishing removal thickness is compared with the thickness to be polished and removed; Based on the fact that the actual polishing removal thickness is less than or equal to the thickness to be polished, it is determined that the automotive parts after polishing meet the process standards, and polishing is completed. Based on the fact that the actual polishing removal thickness is greater than the thickness to be polished, it is determined that the automotive parts after polishing do not meet the process standards and are therefore rejected.

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