Rough surface reconstruction method, device, equipment and medium suitable for vibratory finishing

Abstract

The application relates to a rough surface reconstruction method, device, equipment and medium suitable for vibration polishing, the method first selects a vibration polishing surface morphology and an initial surface morphology of a part, then extracts a vibration polishing texture surface from the vibration polishing surface morphology and extracts key parameters therein, reconstructs the vibration polishing texture surface based on the surface key parameters and an exponential decay type autocorrelation function, and finally reconstructs a mathematical model capable of reflecting the surface morphology of the part after vibration polishing processing at any moment based on the reconstructed vibration polishing texture surface and the main texture of the surface in the initial surface morphology. The method can reconstruct a large number of vibration polishing related rough surfaces based on a small amount of measured vibration polishing surface morphology and initial surface morphology, can ensure that the morphology characteristics and autocorrelation function characteristics of the reconstructed modeling surface are consistent with the measured surface, the error of the height distribution parameters and the space parameters is small, and the reconstructed vibration polishing related rough surface has high precision.

Description

Technical Field

[0001] This application relates to the field of rough surface micromorphology reconstruction technology, and in particular to a rough surface reconstruction method, apparatus, device and medium suitable for vibration finishing. Background Technology

[0002] Vibration finishing is considered one of the most promising methods for ultra-high precision machining of free-form surfaces, and it is currently widely used to improve the surface integrity of key components such as aerospace gears. This is because after shot peening or grinding, a large number of peaks remain on the surface of the components, and vibration finishing can effectively reduce the height of these peaks, thereby improving surface quality.

[0003] Surface micromorphology can be viewed as the fingerprint of a component, influencing its wear, friction, contact, and other service performance characteristics. It serves as a fundamental bridge linking actual engineering manufacturing with service performance. After vibration finishing, most of the texture features of the original surface morphology are removed, while a small portion of the original surface morphology's main texture features coexist with the texture features of the vibration finishing process in the final surface morphology. Reconstructing and modeling the surface morphology after vibration finishing is key to overcoming the bottlenecks of extreme manufacturing, while also significantly reducing experimental processing and material costs. This represents a crucial fundamental research area in high-end manufacturing.

[0004] However, there is currently no effective method for establishing a mathematical model for reconstructing rough surfaces related to vibration finishing, which restricts the study of the correlation between the properties and morphology of such surfaces. Therefore, it is urgent to develop a reconstruction modeling method suitable for vibration-finished rough surfaces. Summary of the Invention

[0005] The following is an overview of the subject matter described in detail herein. This overview is not intended to limit the scope of the claims.

[0006] The main objective of this invention is to propose a method, apparatus, device, and medium for reconstructing rough surfaces suitable for vibration finishing, which can reconstruct a mathematical model of the surface morphology of a component at any time after vibration finishing, and the accuracy of the reconstructed modeled surface is high.

[0007] To achieve the above objective, a first aspect of the present invention provides a method for reconstructing a rough surface suitable for vibration finishing, the method comprising:

[0008] The vibration-finished surface morphology and the initial surface morphology of the component are obtained; wherein the vibration-finished surface morphology is obtained by performing a vibration-finishing process on the initial surface morphology;

[0009] The vibration-polished textured surface is extracted from the vibration-polished surface morphology, and key surface parameters are extracted from the vibration-polished textured surface. The reconstructed vibration-polished textured surface is obtained based on the key surface parameters and the exponentially decaying autocorrelation function.

[0010] The main texture of the surface is extracted from the initial surface morphology. Based on the superposition model of the reconstructed vibration finishing texture surface and the main texture, a mathematical model that can reflect the surface morphology of the part at any time after vibration finishing is reconstructed.

[0011] In some embodiments, extracting the vibration-polished texture surface from the vibration-polished surface morphology includes:

[0012] The main texture of the vibratory-finished surface morphology is obtained by B-spline surface fitting.

[0013] The vibration-polished surface morphology is arithmetically subtracted from the main texture of the vibration-polished surface morphology to obtain the vibration-polished textured surface.

[0014] In some embodiments, the key surface parameters include height distribution parameters and spatial distribution parameters. The height distribution parameters include root mean square height, skewness, and kurtosis. The spatial parameters include minimum autocorrelation length and aspect ratio of the surface properties. The reconstructed vibrational finish textured surface obtained based on the key surface parameters and the exponentially decaying autocorrelation function includes:

[0015] Specify the reconstructed surface size M T ×N T , and the root mean square height S qT skewness S skT and kurtosis S kuT ;

[0016] Generate a random matrix R; where R = ifft2(e i2πδ ); ifft2(.) represents the two-dimensional inverse Fourier transform, where δ includes:

[0017]

[0018] Based on the minimum autocorrelation length S alT Aspect Ratio S of Surface Properties trT Adjust the parameters of the preset exponentially decaying autocorrelation function to generate the autocorrelation function matrix;

[0019] Generate matrix Z using two-dimensional Fourier transform T : Where F is the autocorrelation function matrix, fft2(.) denotes the two-dimensional Fourier transform, and ° denotes the Hadamard product;

[0020] Using the Johnson transformation system, skewness and kurtosis were generated and compared with S. skT S kuT Closely related non-Gaussian matrices;

[0021] Adjusting matrix Z using time-frequency iterative method T Height distribution parameters: Among them, Z R It is a non-Gaussian matrix;

[0022] matrix Z T The root mean square height value is adjusted to S qT : Where std2(.) is the standard deviation operation;

[0023] Adjust the root mean square height value to S qT The matrix Z T As a reconstructed vibrational light-decorated textured surface.

[0024] In some embodiments, the matrix Z is... T The root mean square height value is adjusted to S qT Previously, the rough surface reconstruction method applicable to vibration finishing also included:

[0025] Calculate matrix Z R With Z T If the skewness and kurtosis errors exceed a specified value, then the time-frequency iteration method is used to adjust the matrix Z. T The height distribution parameters; if the error is less than the specified value, then the matrix Z... T The root mean square height value is adjusted to S qT .

[0026] In some embodiments, the autocorrelation function matrix includes:

[0027]

[0028] Where, τ x With τ y τ represents the hysteresis length along the x and y directions, respectively. λx With τ λy These represent the hysteresis lengths that decay to λ along the x and y directions, respectively, where λ is a preset value.

[0029] In some embodiments, the step of extracting the main texture of the surface from the initial surface morphology, and modeling based on the reconstructed vibration-finished textured surface and the main texture to obtain a mathematical model that reflects the surface morphology of the component at any time after vibration finishing includes:

[0030] Within the height range of the surface, upper and lower boundaries are set, and B-spline surface fitting with set fitting coefficients is used to extract the main texture of the surface between the upper and lower boundaries.

[0031] The intermediate texture is obtained by arithmetically adding the main texture to the reconstructed vibrational polished surface texture.

[0032] The Pawlus layered superposition theory with set superposition spacing parameters is used to superimpose and model the intermediate texture and the initial surface morphology to obtain a mathematical model that can reflect the surface morphology of the parts at any time after vibration finishing.

[0033] In some embodiments, the rough surface reconstruction method suitable for vibration finishing further includes:

[0034] The settings of the upper boundary, the lower boundary, the fitting coefficient, and the stacking spacing parameters are optimized as follows:

[0035] Based on the error between the height distribution parameter and the spatial distribution parameter, optimization objective functions T1 and T2 are given:

[0036]

[0037]

[0038] Among them, the objective functions T1 and T2 represent the height feature error and spatial feature error, respectively; Indicates the specified S q S sk S ku S al S tr Value, y sq y ssk y sku y sal y str S represents the surface reconstructed by the mathematical model. q S sk S ku S al S tr value;

[0039] The established superposition model is optimized based on a multi-objective optimization algorithm to search for the Pareto solution set;

[0040] The TOPSIS method is used to find the optimal solution from the Pareto set.

[0041] To achieve the above objective, a second aspect of the present invention provides a rough surface reconstruction apparatus suitable for vibration finishing, the rough surface reconstruction apparatus suitable for vibration finishing comprising:

[0042] A surface morphology acquisition unit is used to acquire the vibration-finished surface morphology and the initial surface morphology of the component; wherein, the vibration-finished surface morphology is obtained by performing a vibration-finishing process on the initial surface morphology;

[0043] The texture surface reconstruction unit is used to extract the vibration-polished texture surface from the vibration-polished surface morphology, extract key surface parameters from the vibration-polished texture surface, and obtain the reconstructed vibration-polished texture surface based on the key surface parameters and the exponentially decaying autocorrelation function.

[0044] The superposition modeling unit is used to extract the main texture of the surface from the initial surface morphology, and to superimpose the reconstructed vibration finishing texture surface and the main texture to reconstruct a mathematical model that can reflect the surface morphology of the part at any time after vibration finishing.

[0045] One embodiment of this application provides a method for reconstructing rough surfaces suitable for vibration finishing. First, the vibration-finished surface morphology and initial surface morphology of a component are selected. Then, a vibration-finished textured surface is extracted from the vibration-finished surface morphology, and key parameters are extracted. Based on the key surface parameters and an exponentially decaying autocorrelation function, the vibration-finished textured surface is reconstructed. Finally, based on the reconstructed vibration-finished textured surface and the main textures of the initial surface morphology, a mathematical model reflecting the surface morphology of the component at any time after vibration finishing is reconstructed. This method can reconstruct a large number of vibration-finished related rough surfaces based on a small number of measured vibration-finished surface morphologies and initial surface morphologies. Furthermore, it ensures that the morphological features and autocorrelation function features of the reconstructed modeled surface are consistent with the measured surface, and the height distribution parameters and spatial parameters have small errors, resulting in high accuracy of the reconstructed vibration-finished related rough surfaces.

[0046] To achieve the above objectives, a third aspect of the present invention provides an electronic device comprising: at least one control processor and a memory for communicatively connecting to the at least one control processor; the memory storing instructions executable by the at least one control processor, the instructions being executed by the at least one control processor to enable the at least one control processor to perform the rough surface reconstruction method of the first aspect applicable to vibration finishing described above.

[0047] To achieve the above objectives, a fourth aspect of the present invention provides a computer-readable storage medium storing computer-executable instructions for causing a computer to perform the rough surface reconstruction method of the first aspect applicable to vibration finishing.

[0048] It is understood that the beneficial effects of the second to fourth aspects compared with the related technologies are the same as the beneficial effects of the first aspect compared with the related technologies. Please refer to the relevant description in the first aspect above, which will not be repeated here. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is a schematic flowchart of a rough surface reconstruction method suitable for vibration finishing provided in one embodiment of this application;

[0051] Figure 2 This is a flowchart of a rough surface reconstruction method suitable for vibration finishing provided in another embodiment of this application;

[0052] Figure 3 This application provides an embodiment of the extracted vibrational polishing texture feature surface and the corresponding symmetric autocorrelation function;

[0053] Figure 4 This application provides a reconstructed vibrational polishing texture feature surface and its corresponding symmetric autocorrelation function in one embodiment.

[0054] Figure 5 This is a measured surface of a shot-peened surface after 1 hour and 2 hours of vibratory finishing, provided in one embodiment of this application;

[0055] Figure 6 This is a symmetric autocorrelation function corresponding to the measured surfaces after 1 hour and 2 hours of vibration finishing provided in one embodiment of this application;

[0056] Figure 7 This application provides an embodiment of the reconstructed surfaces obtained by vibration finishing for 1 hour and 2 hours;

[0057] Figure 8 This is a symmetric autocorrelation function corresponding to the reconstructed surface after 1 hour and 2 hours of vibration finishing provided in one embodiment of this application;

[0058] Figure 9 This is a schematic diagram of the structure of an electronic device provided in one embodiment of this application. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0060] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0061] Vibration finishing is considered one of the most promising methods for ultra-high precision machining of free-form surfaces, and it is currently widely used to improve the surface integrity of key components such as aerospace gears. This is because after shot peening or grinding, a large number of peaks remain on the surface of the components, and vibration finishing can effectively reduce the height of these peaks, thereby improving surface quality.

[0062] Surface micromorphology can be viewed as the fingerprint of a component, influencing its wear, friction, contact, and other service performance characteristics. It serves as a fundamental bridge linking actual engineering manufacturing with service performance. After vibration finishing, most of the texture features of the original surface morphology are removed, while a small portion of the original surface morphology's main texture features coexist with the texture features of the vibration finishing process in the final surface morphology. Reconstructing and modeling the surface morphology after vibration finishing is key to overcoming the bottlenecks of extreme manufacturing, while also significantly reducing experimental processing and material costs. This represents a crucial fundamental research area in high-end manufacturing.

[0063] However, there is currently no effective method for establishing a mathematical model for reconstructing rough surfaces related to vibration finishing, which restricts the study of the correlation between the properties and morphology of such surfaces. Therefore, it is urgent to develop a reconstruction modeling method suitable for vibration-finished rough surfaces.

[0064] Reference Figure 1 One embodiment of this application provides a method for reconstructing rough surfaces suitable for vibration finishing, the method comprising steps S100 to S300:

[0065] Step S100: Obtain the vibration-finished surface morphology and the initial surface morphology of the component; wherein, the vibration-finished surface morphology is obtained by performing a vibration-finishing process on the initial surface morphology.

[0066] Step S200: Extract the vibration-polished textured surface from the vibration-polished surface morphology, extract the key surface parameters from the vibration-polished textured surface, and obtain the reconstructed vibration-polished textured surface based on the key surface parameters and the exponentially decaying autocorrelation function.

[0067] Step S300: Extract the main texture of the surface from the initial surface morphology, and build a mathematical model that can reflect the surface morphology of the part after vibration finishing at any time based on the reconstructed vibration finishing texture surface and the main texture superposition model.

[0068] First, taking an aircraft gear as an example, after shot peening or grinding, the initial surface morphology of the aircraft gear can be acquired using a white light interferometer (Contour GTK). After shot peening or grinding, a large number of peaks remain on the surface morphology of the aircraft gear. These peaks need to be removed using vibratory finishing to obtain the vibratory finished surface morphology.

[0069] After the vibration finishing process, the fine texture features of the initial surface morphology have been removed by the vibration finishing process. In some embodiments, in step S200, the vibration-finished textured surface can be extracted using the following steps S410 and S420:

[0070] Step S410: Perform B-spline surface fitting on the surface morphology of the vibration-polished surface to obtain the main texture of the surface morphology of the vibration-polished surface.

[0071] Step S420: Subtract the vibration-polished surface morphology from the vibration-polished surface morphology main texture by arithmetic to obtain the vibration-polished texture surface.

[0072] B-spline surface fitting is an extension of B-spline curve fitting used to handle surfaces in three-dimensional space. The basic principle of B-spline surface fitting is to perform B-spline surface fitting based on control points, which will not be elaborated here.

[0073] In some embodiments, key surface parameters include height distribution parameters and spatial distribution parameters. Height distribution parameters include root-mean-square height, skewness, and kurtosis. Spatial distribution parameters include minimum autocorrelation length and aspect ratio of the surface morphology. Typically, key surface parameters can be calculated using the following formula:

[0074]

[0075]

[0076]

[0077]

[0078]

[0079] Among them, S ur Let z(i,j) be the defined region, and t be the height matrix within the defined region. i t jThese represent the lag distances in the i and j directions, respectively.

[0080] In the above formulas (1)-(5), through S q S sk S ku S al S tr This refers to the root mean square height, skewness, kurtosis, minimum autocorrelation length, and aspect ratio of surface properties. In the following descriptions of embodiments, S is used. qT S skT S kuT S alT S trT This represents the specific values ​​of root mean square height, skewness, kurtosis, minimum autocorrelation length, and aspect ratio of surface properties.

[0081] Step S200, which involves obtaining the reconstructed vibrational finishing texture surface based on key surface parameters and an exponentially decaying autocorrelation function, includes the following steps S510 to S580:

[0082] Step S510: Specify the reconstructed surface dimension M T ×N T , and the root mean square height S qT skewness S skT and kurtosis S kuT .

[0083] Step S520: Generate a random matrix R;

[0084] R = ifft2(e i2πδ (6)

[0085] ifft2(.) represents the two-dimensional inverse Fourier transform;

[0086] δ includes:

[0087]

[0088] Step S530: Based on the minimum autocorrelation length S alT Aspect Ratio S of Surface Properties trT Adjust the parameters of the self-defined exponentially decaying autocorrelation function to generate the autocorrelation function matrix.

[0089] In some embodiments, the autocorrelation function matrix includes:

[0090]

[0091] Where, τ x With τ y τ represents the hysteresis length along the x and y directions, respectively. λx With τλy These represent the hysteresis lengths that decay to λ along the x and y directions, respectively, where λ is a preset value, usually set to 0.1.

[0092] Step S540: Generate matrix Z using two-dimensional Fourier transform. T :

[0093]

[0094] Where F is the autocorrelation function matrix, fft2(.) represents the two-dimensional Fourier transform, and ° represents the Hadamard product.

[0095] Step S550: Use the Johnson transformation system to generate skewness and kurtosis respectively, and then compare them with S... skT S kuT The closest non-Gaussian matrix, used here is Z. R This represents a non-Gaussian matrix.

[0096] Step S560: Adjust matrix Z using the time-frequency iteration method. T Height distribution parameters:

[0097]

[0098] Step S570: Calculate matrix Z R With Z T Skewness and kurtosis error:

[0099]

[0100] If the error is greater than the specified value, proceed to step S560; if the error is less than the specified value, proceed to the next step.

[0101] Step S580: Convert matrix Z T The root mean square height value is adjusted to S qT :

[0102]

[0103] Among them, std2(.) is the standard deviation operation.

[0104] Adjust the root mean square height value of the above steps to S. qT The matrix Z T As a reconstructed vibrational light-decorated textured surface.

[0105] In some embodiments, step S300 includes steps S610 to S630:

[0106] Step S610: Set the upper and lower boundaries within the height range of the surface, and use B-spline surface fitting with set fitting coefficients to extract the main texture of the surface between the upper and lower boundaries.

[0107] Step S620: Arithmetically add the main texture and the reconstructed vibrational surface texture to obtain the intermediate texture.

[0108] Step S630: The Pawlus layered superposition theory with set superposition spacing parameters is used to superimpose and model the intermediate texture and the initial surface morphology to obtain a mathematical model that can reflect the surface morphology of the parts at any time after vibration finishing.

[0109] Because the parts are affected by the original surface main texture and grinding size during the abrasive cutting process, not all positions on the surface to be processed will be processed by the abrasive. Therefore, it is assumed that the height of the micro-protrusion cut on the rough surface will always be within a certain range. Thus, step S610 sets the upper and lower boundaries for characterization, taking into account the influence of the original surface main texture and grinding size on the abrasive during cutting, thereby improving the reconstruction effect of the surface morphology of the parts after vibration finishing at any time.

[0110] In some embodiments, the settings of the upper boundary, lower boundary, fitting coefficient, and stacking spacing parameters are optimized through the following steps S710 to S730.

[0111] Step S710: Based on the error between the height distribution parameter and the spatial distribution parameter, give the optimization objective functions T1 and T2:

[0112]

[0113]

[0114] Among them, the objective functions T1 and T2 represent the height feature error and spatial feature error, respectively; Indicates the specified S q S sk S ku S al S tr Value, y sq y ssk ,y sku y sal y str S represents the surface reconstructed by the mathematical model. q S sk S ku ,S al S tr value.

[0115] Step S720: Optimize the established superposition model based on the multi-objective optimization algorithm and search for the Pareto solution set.

[0116] Step S730: Find the optimal solution from the Pareto solution set according to the TOPSIS method.

[0117] In steps S610 to S630, four parameters need to be set in advance: upper boundary, lower boundary, fitting coefficient, and stacking spacing. The specific values ​​of each parameter are obtained through steps S710 to S730. Steps S710 to S730 serve as an optimization model for the modeling process described in steps S610 to S630 above, providing objective functions T1 and T2. During the optimization process, y sq y ssk ,y sku y sal y str It will continue to change until the objectives T1 and T2 converge to a reasonable range.

[0118] Steps S710-S730 of this embodiment improve the Pawlus superposition theory by providing an optimization objective function based on the error between the height distribution parameter and the spatial distribution parameter, and then optimizing it to improve the modeling effect.

[0119] This embodiment provides a method for reconstructing rough surfaces suitable for vibration finishing. First, the vibration-finished surface morphology and initial surface morphology of the component are selected. Then, the vibration-finished textured surface is extracted from the vibration-finished surface morphology, and key parameters are extracted. Based on the key surface parameters and an exponentially decaying autocorrelation function, the vibration-finished textured surface is reconstructed. Finally, based on the reconstructed vibration-finished textured surface and the main textures of the initial surface morphology, a mathematical model reflecting the surface morphology of the component at any time after vibration finishing is reconstructed. This method can reconstruct a large number of vibration-finished related rough surfaces based on a small number of measured vibration-finished surface morphologies and initial surface morphologies. Furthermore, it ensures that the morphological features and autocorrelation function features of the reconstructed modeled surface are consistent with the measured surface, and the height distribution parameters and spatial parameters have small errors, resulting in high accuracy of the reconstructed vibration-finished related rough surfaces.

[0120] Reference Figures 2 to 8 This application provides a method for reconstructing and modeling rough surfaces related to vibration finishing, comprising the following steps S810 to S840:

[0121] Step S810: Measurements were performed using a white light interferometer, Wyko NT910. The surfaces measured were shot-peened surfaces and shot-peened-vibration-finished surfaces that had undergone vibration finishing for 1 hour, 2 hours, and 5 hours.

[0122] Step S820: The vibration-finished texture feature surface extracted from the shot-peening-vibration-finished surface after 5 hours of vibration finishing and the corresponding symmetric autocorrelation function are as follows: Figure 3 As shown, the reconstructed vibrational polishing texture feature surface and the corresponding symmetric autocorrelation function are as follows: Figure 4 As shown. The formula for calculating the autocorrelation function is as follows:

[0123]

[0124] In the above formula, E() represents the expectation operation, and std2(.) represents the standard deviation operation. i =0,1,…,n i -1,t j =0,1,…,n j -1 represents the hysteresis distance in the i and j directions, respectively. After calculating the autocorrelation function of the surface morphology, in F... U The symmetric autocorrelation function is obtained by symmetrically performing the i and j directions at (1,1).

[0125] Step S830: Superimpose and model the measured shot peening surface and the reconstructed vibration-polished texture feature surface.

[0126] Step S840: Calculate the height distribution parameters and spatial parameters of the surface after 1 hour and 2 hours of vibration finishing, and use them as optimization targets to inversely calculate the parameters of the mathematical model established in S3.

[0127] The measured surface morphology of shot peening-vibration finishing after 1 hour and 2 hours of vibration finishing and the corresponding symmetric autocorrelation functions are as follows: Figure 5 , Figure 6 As shown. The reconstructed surface morphology of shot peening-vibration finishing after 1 hour and 2 hours of processing and the corresponding symmetric autocorrelation functions are as follows. Figure 7 , Figure 8 As shown.

[0128] The key parameters and percentage errors between the reconstructed surface and the measured surface are shown in Table 1 below. As can be seen from Table 1, the percentage errors of all key parameters are less than 6%, indicating that the method has high accuracy.

[0129]

[0130] Table 1

[0131] This embodiment has the following beneficial effects:

[0132] (1) A large number of vibration-related rough surfaces can be reconstructed based on a small amount of measured data.

[0133] (2) It takes into account that the abrasive grains will be affected by the original surface texture and grinding size during cutting.

[0134] (3) Improve Pawlus superposition theory to apply it to superposition modeling of vibration-decorated rough surfaces.

[0135] (4) The height distribution parameters and spatial parameters between the reconstructed model surface and the measured surface are all less than 6%, indicating high accuracy.

[0136] One embodiment of this application provides a rough surface reconstruction apparatus suitable for vibration finishing. The rough surface reconstruction apparatus suitable for vibration finishing includes:

[0137] The surface morphology acquisition unit is used to acquire the vibration-finished surface morphology and the initial surface morphology of the component; wherein, the vibration-finished surface morphology is obtained by performing a vibration-finishing process on the initial surface morphology.

[0138] The texture surface reconstruction unit is used to extract the vibration-polished texture surface from the vibration-polished surface morphology, extract the key surface parameters from the vibration-polished texture surface, and obtain the reconstructed vibration-polished texture surface based on the key surface parameters and the exponentially decaying autocorrelation function.

[0139] The superposition modeling unit is used to extract the main texture of the surface from the initial surface morphology. Based on the superposition modeling of the reconstructed vibration finishing texture surface and the main texture, a mathematical model that can reflect the surface morphology of the part after any time of vibration finishing is obtained.

[0140] This embodiment is based on the same inventive concept as the above method embodiment, so it will not be described again here.

[0141] like Figure 9 This application also provides an electronic device, which includes:

[0142] At least one memory;

[0143] At least one processor;

[0144] At least one program;

[0145] The program is stored in memory, and the processor executes at least one program to implement the rough surface reconstruction method applicable to vibration finishing described above in this disclosure.

[0146] This electronic device can be any smart terminal, including mobile phones, tablets, personal digital assistants (PDAs), and in-vehicle computers.

[0147] The electronic devices according to embodiments of this application will now be described in detail.

[0148] The processor 1600 can be implemented using a general-purpose central processing unit (CPU), microprocessor, application specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present invention.

[0149] The memory 1700 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 1700 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the program code is stored in the memory 1700 and is called and executed by the processor 1600 to execute the rough surface reconstruction method for vibration finishing according to the embodiments of the present invention.

[0150] The input / output interface 1800 is used to implement information input and output.

[0151] The communication interface 1900 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0152] Bus 2000 transmits information between various components of the device (e.g., processor 1600, memory 1700, input / output interface 1800, and communication interface 1900);

[0153] The processor 1600, memory 1700, input / output interface 1800 and communication interface 1900 are connected to each other within the device via bus 2000.

[0154] This invention also provides a storage medium, which is a computer-readable storage medium storing computer-executable instructions for causing a computer to perform the above-described rough surface reconstruction method suitable for vibration finishing.

[0155] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0156] The embodiments described in this invention are intended to more clearly illustrate the technical solutions of the embodiments of this invention, and do not constitute a limitation on the technical solutions provided by the embodiments of this invention. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this invention are also applicable to similar technical problems.

[0157] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present invention, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0158] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0159] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0160] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0161] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0162] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0163] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0164] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0165] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause an electronic device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0166] The above is a detailed description of the preferred embodiments of this application. However, the embodiments of this application are not limited to the above-described implementation methods. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the embodiments of this application. All such equivalent modifications or substitutions are included within the scope defined by the claims of the embodiments of this application.

Claims

1. A method for reconstructing rough surfaces suitable for vibration finishing, characterized in that, The rough surface reconstruction method applicable to vibration finishing includes: The vibration-finished surface morphology and the initial surface morphology of the component are obtained; wherein the vibration-finished surface morphology is obtained by performing a vibration-finishing process on the initial surface morphology; The vibration-polished textured surface is extracted from the vibration-polished surface morphology, and key surface parameters are extracted from the vibration-polished textured surface. The reconstructed vibration-polished textured surface is obtained based on the key surface parameters and the exponentially decaying autocorrelation function. The main texture of the surface is extracted from the initial surface morphology. Based on the superposition of the reconstructed vibration finishing texture surface and the main texture, a mathematical model that can reflect the surface morphology of the part at any time after vibration finishing is reconstructed. The key surface parameters include height distribution parameters and spatial distribution parameters. The height distribution parameters include root mean square height, skewness, and kurtosis. The spatial parameters include minimum autocorrelation length and aspect ratio of the surface properties. The reconstructed vibrational finish texture surface obtained based on the key surface parameters and the exponentially decaying autocorrelation function includes: Specify the reconstructed surface dimensions × , and root mean square height skewness and kurtosis ; Generate random matrices ;in, ; This represents the two-dimensional inverse Fourier transform. include: Based on the minimum autocorrelation length Aspect Ratio of Surface Properties Adjust the parameters of the preset exponentially decaying autocorrelation function to generate the autocorrelation function matrix; Generating matrices using two-dimensional Fourier transform : ;in, The autocorrelation function matrix, Represents a two-dimensional Fourier transform. It represents the Hadamardi (or Hadama) stack; Using the Johnson transformation system, skewness and kurtosis were generated and compared with... , Closely related non-Gaussian matrices; Adjusting the matrix using the time-frequency iterative method Height distribution parameters: ;in, It is a non-Gaussian matrix; matrix The root mean square height value is adjusted to : ,in, For standard deviation calculation; Adjust the root mean square height value to matrix As a reconstructed vibrational light-decorated textured surface.

2. The rough surface reconstruction method for vibration finishing according to claim 1, characterized in that, The step of extracting the vibration-polished texture surface from the vibration-polished surface morphology includes: The main texture of the vibratory-finished surface morphology is obtained by B-spline surface fitting. The vibration-polished surface morphology is arithmetically subtracted from the main texture of the vibration-polished surface morphology to obtain the vibration-polished textured surface.

3. The rough surface reconstruction method for vibration finishing according to claim 1, characterized in that, In the matrix The root mean square height value is adjusted to Previously, the rough surface reconstruction method applicable to vibration finishing also included: Calculate matrix and If the skewness and kurtosis errors exceed a specified value, the matrix is ​​further adjusted using the time-frequency iteration method. The height distribution parameters; if the error is less than the specified value, then the matrix will be... The root mean square height value is adjusted to .

4. The rough surface reconstruction method for vibration finishing according to claim 3, characterized in that, The autocorrelation function matrix includes: in, and They represent along , hysteresis length in the direction, and They represent along , Attenuation in direction The lag length, This is the default value.

5. The rough surface reconstruction method for vibration finishing according to claim 3, characterized in that, The step of extracting the main texture of the surface from the initial surface morphology, and modeling the reconstructed vibration-finished texture surface and the main texture to reconstruct a mathematical model that can reflect the surface morphology of the component at any time after vibration finishing includes: Within the height range of the surface, upper and lower boundaries are set, and B-spline surface fitting with set fitting coefficients is used to extract the main texture of the surface between the upper and lower boundaries. The intermediate texture is obtained by arithmetically adding the main texture to the reconstructed vibrational polished surface texture. The Pawlus layered superposition theory with set superposition spacing parameters is used to superimpose and model the intermediate texture and the initial surface morphology to obtain a mathematical model that can reflect the surface morphology of the parts at any time after vibration finishing.

6. The rough surface reconstruction method for vibration finishing according to claim 5, characterized in that, The rough surface reconstruction method applicable to vibration finishing also includes: The settings of the upper boundary, the lower boundary, the fitting coefficient, and the stacking spacing parameters are optimized as follows: The optimization objective function is given based on the error between the height distribution parameter and the spatial distribution parameter. and : Among them, the objective function is optimized. and These respectively characterize the height feature error and the spatial feature error; Indicates the specified value, Represents the mathematical model reconstructing the surface value; The established superposition model is optimized based on a multi-objective optimization algorithm to search for the Pareto solution set; The TOPSIS method is used to find the optimal solution from the Pareto set.

7. A rough surface reconstruction device suitable for vibration finishing, characterized in that, The rough surface reconstruction device suitable for vibration finishing includes: A surface morphology acquisition unit is used to acquire the vibration-finished surface morphology and the initial surface morphology of the component; wherein, the vibration-finished surface morphology is obtained by performing a vibration-finishing process on the initial surface morphology; The texture surface reconstruction unit is used to extract the vibration-polished texture surface from the vibration-polished surface morphology, extract key surface parameters from the vibration-polished texture surface, and obtain the reconstructed vibration-polished texture surface based on the key surface parameters and the exponentially decaying autocorrelation function. The superposition modeling unit is used to extract the main texture of the surface from the initial surface morphology, and to superimpose the reconstructed vibration finishing texture surface and the main texture to create a mathematical model that can reflect the surface morphology of the part at any time after vibration finishing. The key surface parameters include height distribution parameters and spatial distribution parameters. The height distribution parameters include root mean square height, skewness, and kurtosis. The spatial parameters include minimum autocorrelation length and aspect ratio of the surface properties. The reconstructed vibrational finish texture surface obtained based on the key surface parameters and the exponentially decaying autocorrelation function includes: Specify the reconstructed surface dimensions × , and root mean square height skewness and kurtosis ; Generate random matrices ;in, ; This represents the two-dimensional inverse Fourier transform. include: Based on the minimum autocorrelation length Aspect Ratio of Surface Properties Adjust the parameters of the preset exponentially decaying autocorrelation function to generate the autocorrelation function matrix; Generating matrices using two-dimensional Fourier transform : ;in, The autocorrelation function matrix, Represents a two-dimensional Fourier transform. It represents the Hadamardi (or Hadama) stack; Using the Johnson transformation system, skewness and kurtosis were generated and compared with... , Closely related non-Gaussian matrices; Adjusting the matrix using the time-frequency iterative method Height distribution parameters: ;in, It is a non-Gaussian matrix; matrix The root mean square height value is adjusted to : ,in, For standard deviation calculation; Adjust the root mean square height value to matrix As a reconstructed vibrational light-decorated textured surface.

8. An electronic device, characterized in that, include: At least one control processor and a memory for communicatively connecting to the at least one control processor; The memory stores instructions that can be executed by the at least one control processor to enable the at least one control processor to perform the rough surface reconstruction method for vibration finishing as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions for causing a computer to perform the rough surface reconstruction method for vibration finishing as described in any one of claims 1 to 6.

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