Scraping surface rigidity parameter acquisition method and device based on digital simulation

Abstract

The invention discloses a scraping surface stiffness parameter acquisition method based on digital simulation, which comprises the following steps: respectively calculating power spectral density of scraping surface topography data in an x direction and a y direction to obtain mean power spectral density; according to the mean power spectral density, obtaining a double-fractal characteristic parameter; inputting the double-fractal characteristic parameters into the morphology simulation formula to obtain a simulated double-fractal surface; setting a section height to cut off the simulated double-fractal surface to form a cut-off area and a cut-off part; calculating the area of each truncation region and the volume of the corresponding truncation part; taking the cut-off part as a micro-convex body, and determining the deformation of each micro-convex body; determining a deformation stage of each micro-convex body according to the deformation amount and the deformation amount critical value of the micro-convex body; and calculating the rigidity of each micro-convex body according to the deformation stage of each micro-convex body, and summing to obtain the total rigidity. The invention provides a scraping surface rigidity digital simulation calculation method which does not need to use a distribution law, and more accurate and more efficient digital simulation prediction of the rigidity of a multi-process machining surface such as scraping is realized.

Description

TECHNICAL FIELD

[0001] The application relates to a digital simulation-based scraped surface rigidity parameter acquisition method and device, and belongs to the field of digital simulation of scraped surfaces and multi-process surface rigidity. BACKGROUND

[0002] The structure of a mechanical processing device is usually formed by a large number of components connected to each other through a joint surface, and the guide rail joint surface has a key influence on the performance of the whole machine. The existence of these mechanical joint surfaces causes the structure to be discontinuous, which directly affects the dynamic characteristics of the whole machine. As an important dynamic parameter of the joint surface, the rigidity needs to be detected by effective means to determine whether the processed surface meets the design requirements.

[0003] Conventionally, the surface rigidity is measured by compression experiments, but this method may damage the surface topography, so the simulation calculation method for predicting the rigidity gradually becomes an important supplementary means. The surface obtained by actual mechanical processing is not an ideal smooth plane, but a complex rough structure composed of multi-scale topographic features. Such a surface can usually be characterized by a series of micro-convex bodies. Existing simulation methods are mostly based on the study of the contact behavior of a single micro-convex body, and then the results are extended to the entire contact area by a distribution law to calculate the total surface rigidity. For example, the fractal surface is calculated by the Mandelbrot area distribution law to calculate the total surface rigidity. However, this method assumes that the surface has fractal characteristics, which is suitable for general rough surfaces, but it is difficult to handle joint surfaces processed by scraping and other multi-processes. Scraping, as a traditional precision surface processing technology, is widely used in guide rail joint surface processing, aiming to improve the surface matching quality and mechanical performance. The surface formed by scraping processing has unique topographic features, which exhibit a bimodal fractal structure, i.e., regions containing two different fractal characteristics, so the traditional rigidity calculation method based on the Mandelbrot area distribution law cannot be directly used.

[0004] Therefore, for the rigidity simulation of scraped surfaces, a new digital simulation method independent of the distribution law is urgently needed. For this purpose, the application provides a digital simulation method for scraped surface rigidity independent of the distribution law. SUMMARY

[0005] The application provides a digital simulation-based scraped surface rigidity parameter acquisition method and device, which can be used for digital simulation prediction of the rigidity of scraped surfaces.

[0006] The technical solution of the application is as follows:

[0007] According to a first aspect of the application, a digital simulation-based scraped surface rigidity parameter acquisition method is provided, comprising:

[0008] Step 1: measure one-dimensional profiles of the x direction and the y direction of the scraped surface to obtain x direction and y direction scraped surface topography data.

[0009] Step 2: respectively calculate the power spectral density of the x direction and the y direction scraped surface topography data to obtain the mean power spectral density.

[0010] Step 3: obtain the bifractal characteristic parameters according to the mean power spectral density; wherein the bifractal characteristic parameters include the first fractal dimension, the second fractal dimension, the first fractal coefficient, the second fractal coefficient, the maximum frequency index and the critical frequency index.

[0011] Step 4: input the bifractal characteristic parameters into the topography simulation formula to obtain the simulated bifractal surface.

[0012] Step 5: set the cross-section height to truncate the simulated bifractal surface to form the truncated area and the truncated part; calculate the area of each truncated area and the volume of the corresponding truncated part; take the truncated part as a microconvex body to determine the deformation amount of each microconvex body.

[0013] Step 6: determine the deformation stage of each microconvex body according to the deformation amount and the deformation amount critical value of the microconvex body; calculate the stiffness of each microconvex body according to the deformation stage of each microconvex body, and then sum up to obtain the total stiffness.

[0014] Further, the step 2 is specifically:

[0015] Step 2.1, adjust the mean line of the x direction and the y direction scraped surface topography data and to zero to obtain the x direction and the y direction scraped surface topography data after the mean line is adjusted to zero.

[0016] Step 2.2, calculate the power spectral density according to the x direction and the y direction scraped surface topography data after the mean line is adjusted to zero.

[0017] Step 2.3, double-logarithmic conversion is performed on the power spectral densities of the x and y directions, and the mean value of the double-logarithmic power spectral densities of the x and y directions is taken as the mean power spectral density.

[0018] Further, the step 3 is specifically:

[0019] Step 3.1, construct a fitting formula based on the Sigmoid function; take the mean power spectral density as the input of the fitting formula to obtain the undetermined parameters.

[0020] Step 3.2, calculate the first fractal dimension, the second fractal dimension, the maximum frequency index and the critical frequency index according to the undetermined parameters.

[0021] Step 3.3, calculate the first fractal coefficient and the second fractal coefficient according to the undetermined parameters and the fractal dimension.

[0022] Further, the topography simulation formula is:

[0023] ;

[0024] wherein Z(x, y) represents a simulated bifractal surface; is a constant; L represents a bifractal surface length; M is a number of superimposed cosine waves; 、 are respectively a first and a second fractal coefficient; 、 are respectively a first and a second fractal dimension; is a critical frequency exponent; n is a frequency exponent; is a random distribution in [0, 2π]; is an abscissa of a bifractal surface data point; is an ordinate of a bifractal surface data point; is a maximum frequency exponent.

[0025] Further, the step 5 is specifically:

[0026] Step 5.1, setting a section height to truncate the simulated bifractal surface to form a truncated region and a truncated part, and using an eight-connected domain method to identify each truncated region on the section.

[0027] Step 5.2, calculating an area of each truncated region and a volume of each truncated part.

[0028] Step 5.3, taking the truncated part as a microconvex body, determining a base length of each microconvex body according to the area of the truncated region and the volume of the corresponding truncated part, and determining a deformation amount of each microconvex body according to the base length of each microconvex body.

[0029] Further, the deformation amount ω calculation formula is:

[0030] ω = G D − 2 l 3 − D [ 1 − cos ( π r l ) ] ;

[0031] wherein, , is the area of the truncated region; if , = , = ; if , = 、 = ; and are respectively the first and the second fractal dimension, and is a first fractal coefficient; is a critical frequency index, is a constant; is a microconvex base length.

[0032] Further, the step 6 is specifically:

[0033] Step 6.1, according to the deformation amount of the microconvex and the deformation amount critical value, determine the deformation stage of each microconvex as the elastic deformation stage, the first elastic-plastic deformation stage, the second elastic-plastic deformation stage or the complete plastic deformation stage.

[0034] Step 6.2, according to the deformation stage of each microconvex, calculate the contact area, contact load and contact stiffness of each microconvex.

[0035] Step 6.3, according to the sum of the contact area, contact load and contact stiffness of all microconvex, obtain the total contact area, total contact load and total contact stiffness of the microconvex.

[0036] Further, the deformation stage of each microconvex is determined according to the deformation amount of the microconvex and the deformation amount critical value, specifically: when the deformation amount ≤ , the microconvex is in the elastic deformation stage; when < ≤6 , the microconvex is in the first elastic-plastic deformation stage; when 6 < ≤110 , the microconvex is in the second elastic-plastic deformation stage; when 110 < , the microconvex is in the complete plastic deformation stage; wherein, is the deformation amount critical value.

[0037] According to the second aspect of the present application, a digital simulation-based scratch surface stiffness parameter acquisition device is provided, which includes the modules of the method in any one of the above.

[0038] According to the third aspect of the present application, a terminal is provided, which includes a processor, a memory, and a computer program stored in the memory and executable on the processor, and the processor is configured to execute the steps of the method in any one of the above.

[0039] The present application has the advantages that: the present application proposes a scratch surface stiffness digital simulation calculation method without using the distribution law; the method overcomes the deficiency that the traditional stiffness simulation calculation method cannot be used in the simulation calculation of the surface stiffness of multiple processes such as scratch, and realizes more accurate and efficient digital simulation prediction of the surface stiffness of multiple processes such as scratch. BRIEF DESCRIPTION OF DRAWINGS

[0040] Figure 1 A flow chart of the method of the present application.

[0041] Figure 2 A measured surface profile of a lapped surface.

[0042] Figure 3 A curve fitting result of a power spectral density of a lapped surface profile.

[0043] Figure 4 A bi-fractal simulated surface.

[0044] Figure 5 A schematic diagram of a cross-sectional truncated surface.

[0045] Figure 6 A schematic diagram of an 8-connected domain method.

[0046] Figure 7 A schematic diagram of a micro-asperity base length calculation.

[0047] Figure 8 A comparison chart of simulation results and experimental results in an embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of the present application. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other in any manner without conflict.

[0049] Embodiment 1: As shown, according to a first aspect of the embodiments of the present application, a lapped surface stiffness parameter acquisition method based on digital simulation is provided, comprising: Figures 1-8

[0050] Step 1: Measure one-dimensional profiles in x and y directions of a lapped surface to obtain lapped surface profile data in x and y directions and .

[0051] Step 2: Calculate power spectral densities of the lapped surface profile data in x and y directions respectively to obtain mean power spectral densities.

[0052] Step 3: Obtain bi-fractal characteristic parameters according to the mean power spectral densities; wherein the bi-fractal characteristic parameters include fractal dimension, fractal coefficient, maximum frequency exponent and critical frequency exponent.

[0053] ​Step 4: Input the bifractal feature parameters into the topography simulation formula to obtain the simulated bifractal surface.

[0054] Step 5: Set the cross-section height to truncate the simulated bifractal surface, forming truncated regions and truncated parts; calculate the area of ​​each truncated region and the volume of each truncated part; treat the truncated part as a micro-protrusion and determine the deformation of each micro-protrusion.

[0055] Step 6: Determine the deformation stage of each micro-protrusion based on its deformation amount and critical deformation value; calculate the stiffness of each micro-protrusion based on its deformation stage, and then sum them to obtain the total stiffness.

[0056] Furthermore, it also includes:

[0057] Step 7: Change the section height and repeat steps 5 and 6 to calculate the load-stiffness curve.

[0058] Step 8: Repeat steps 4, 5, 6 and 7, and take the average value of all load-stiffness curves for the same section height as the final result.

[0059] Furthermore, step 2 specifically includes:

[0060] Step 2.1: Scrape the surface morphology data in the x and y directions. and The mean line was adjusted to zero, and the surface morphology data of the scraped surface in the x and y directions after the mean line was zeroed were obtained. and .

[0061] Step 2.2: Based on the surface morphology data in the x and y directions after zeroing the mean line, calculate the power spectral density respectively. The calculation formula is:

[0062]

[0063] in, For Fourier transform, This represents the surface morphology data of the scraped surface in the x or y direction after the mean line has been zeroed. To measure the number of measurement points in the x or y direction of the scraped surface (when calculating the power spectral density based on the x-direction scraped surface morphology data after zeroing the mean line, then...) To measure the number of measurement points in the x-direction of the scraped surface; when calculating the power spectral density based on the y-direction scraped surface morphology data after zeroing the mean line, then... (To measure the number of measurement points in the y-direction of the scraped surface) Sampling frequency, This refers to the spatial frequency.

[0064] Step 2.3: Perform a double logarithmic transformation on the power spectral density in the x and y directions, and take the mean of the double logarithmic power spectral density in the x and y directions as the mean power spectral density. .

[0065] Furthermore, step 3 specifically includes:

[0066] Step 3.1: Construct a fitting equation based on the Sigmoid function; use the mean power spectral density as the input to the fitting equation to obtain the parameters to be determined.

[0067] The fitting formula is:

[0068] y 1 = [ 1 − U ( x 1 ) ] ⋅ ( k 1 x 1 + b 1 ) + L ( x 1 ) ( k 2 x 1 + b 2 ) ;

[0069] in, , , , , , and These are parameters to be determined. , ; For spatial frequency, This represents the mean power spectral density.

[0070] Step 3.2: Calculate the first fractal dimension based on the parameters to be determined. Second fractal dimension Maximum frequency index and critical frequency index .

[0071] The and The expression is:

[0072] ;

[0073] ;

[0074] The and The expression is:

[0075] n max = int [ log( f max ) log( γ ) ] ;

[0076] n c = int [ c log( γ ) ] ;

[0077] Where int represents integer division. It is the frequency of maximum mean power spectral density. The constant is taken as 1.5.

[0078] Step 3.3: Calculate the first fractal coefficient based on the undetermined parameters and fractal dimension. Second fractal coefficient The and The expression is:

[0079] ;

[0080] ;

[0081] in, Represents the natural constant.

[0082] Furthermore, the morphological simulation formula is as follows:

[0083] ;

[0084] Where Z(x,y) represents the simulated bifractal surface, that is, the height of the corresponding data point on the bifractal surface represents the simulated bifractal surface; L represents the length of the bifractal surface; This represents the spectrum of a bifractal surface; M is the number of superimposed cosine waves, typically M=10; n is the frequency index; It is a random distribution in the interval [0, 2π]. It is a constant; The x-coordinate of the data point on the bifractal surface; y is the ordinate of the data point on the bifractal surface.

[0085] Further, step 5 specifically includes:

[0086] Step 5.1: Set the section height h t The simulated bifractal surface is truncated to form truncated regions and truncated portions, and each truncated region on the cross-section is identified using the 8-connected domain method; among them... , For the maximum surface height, This is the cutoff factor; reference. Figure 5 The simulated bifractal surface is truncated at a set cross-sectional height, and multiple truncated regions are formed at the cross-sectional height of the simulated bifractal surface. The part that is detached from the simulated bifractal surface is the truncated part. One truncated region corresponds to one truncated part, that is, the number of truncated regions and truncated parts are equal.

[0087] Step 5.2: Calculate the area of ​​each cut-off region and the volume of each cut-off part.

[0088] The formula for calculating the area of ​​the cut-off region is:

[0089] ;

[0090] in, This represents the number of data points in the truncated region. The sampling interval is denoted as .

[0091] The formula for calculating the volume of the cut-off portion is:

[0092] ;

[0093] in, The height of the data points on the truncated section from the cross-section.

[0094] Step 5.3: Treat the cut-off portion as a micro-protrusion, determine the base length of each micro-protrusion based on the area of ​​the cut-off region and the corresponding volume of the cut-off portion; determine the deformation amount of each micro-protrusion based on the base length of each micro-protrusion.

[0095] The length of the micro-convex body substrate is determined based on the area of ​​the cut-off region and the corresponding volume of the cut-off portion, expressed as follows:

[0096] v c = G D − 2 l 5 − D π [ 2 c o s ( π r l ) − 2 − ( π r l ) 2 c o s ( π r l ) + 2 π r l s i n ( π r l ) ]

[0097] Among them, the equivalent radius of the truncated region ,like ,but = , = ;like ,but = , = ; and The first and second fractal dimensions are, and These are the first and second fractal coefficients; This is the critical frequency index. Let 1.5 be a constant. Given the area of ​​the cut-off region and the corresponding volume of the cut-off portion, the length of the micro-convex substrate can be determined using the above formula. .

[0098] The formula for calculating the deformation ω is: ω = G D − 2 l 3 − D [ 1 − cos ( π r l ) ] .

[0099] Furthermore, step 6 specifically includes:

[0100] Step 6.1: Based on the deformation amount and the critical value of the deformation amount of the micro-protrusion, determine the deformation stage of each micro-protrusion as the elastic deformation stage, the first elastic-plastic deformation stage, the second elastic-plastic deformation stage, or the fully plastic deformation stage.

[0101] The deformation level of each micro-protrusion is determined based on its deformation amount and critical deformation value. Specifically, when the deformation amount... ≤ At that time, the micro-protrusion is in the elastic deformation stage; when < ≤6 At that time, the micro-protrusion is in the first stage of elastic-plastic deformation; when 6 < ≤110 At that time, the micro-protrusion is in the second stage of elastic-plastic deformation; when 110 < The micro-protrusions are in the stage of complete plastic deformation.

[0102] The critical value of deformation for:

[0103] ;

[0104] Critical value of contact area for:

[0105] ;

[0106] in, This is the hardness coefficient. , is Poisson's ratio; E is the equivalent elastic modulus; H is the hardness of the material.

[0107] Step 6.2, according to the... The deformation stage of the micro-convex body is calculated. Contact area of ​​each micro-protrusion Contact load Contact stiffness ;Specifically:

[0108] If the micro-protrusion is in the elastic deformation stage, then the contact area of ​​the micro-protrusion in the elastic deformation stage is... Contact load and contact stiffness The expression is:

[0109] ;

[0110] ;

[0111] ;

[0112] in, This represents the radius of curvature of the micro-convex body.

[0113] If the micro-protrusion is in the first elastic-plastic deformation stage, then the contact area of ​​the micro-protrusion in the first elastic-plastic deformation stage is... Contact load and contact stiffness The expression is:

[0114] ;

[0115] ;

[0116] ;

[0117] in, ;

[0118] If the micro-protrusion is in the second elastic-plastic deformation stage, then the contact area of ​​the micro-protrusion in the second elastic-plastic deformation stage is... Contact load and contact stiffness The expression is:

[0119] ;

[0120] ;

[0121] ;

[0122] If the micro-protrusion is in the fully plastic deformation stage, then the contact area of ​​the micro-protrusion in the fully plastic deformation stage is... Contact load and contact stiffness The expression is:

[0123] ;

[0124] ;

[0125] .

[0126] Based on the above, when the first The deformation stages of each micro-convex body are different, therefore the first... Contact area of ​​each Contact load Contact stiffness The calculation methods differ, and the contact area will be used as an example. If the micro-protrusion is in the elastic deformation stage, then... Pick If the micro-protrusion is in the first stage of elastic-plastic deformation, then Pick If the micro-protrusion is in the second stage of elastic-plastic deformation, then Pick If the micro-protrusion is in the fully plastic deformation stage, then Pick Contact load Contact stiffness Similarly.

[0127] Step 6.3: Sum the contact area, contact load, and contact stiffness of all micro-protrusions to obtain the total contact area, total contact load, and total contact stiffness of the micro-protrusions.

[0128] , ,

[0129] in, Indicates the total number of micro-protrusions; ; , , These represent the total contact area, total contact load, and total contact stiffness of the micro-protrusion, respectively.

[0130] As can be seen from the above, by repeatedly executing steps 5.2, 5.3, 6.1, and 6.2, we can analyze... We can obtain the total contact area, total contact load, and total contact stiffness of each micro-protrusion by summing them up.

[0131] Furthermore, in step 7, the cross-sectional height h is changed. t Repeat steps 5 and 6 to calculate the load-stiffness curve.

[0132] Further, in step 8, steps 4, 5, 6 and 7 are repeated, and the average value of all load-stiffness curves for the same cross-sectional height is taken as the final result.

[0133] Taking a real scraped surface as an example, according to Figure 1 The flowchart shown illustrates the principle of the present invention: digital simulation calculation method for the stiffness of scraped surfaces.

[0134] 1) A contact profilometer was used to measure the actual scraped surface, and one-dimensional height data in the x and y directions of the scraped surface were extracted as the scraped surface morphology data. and ,like Figure 2 As shown.

[0135] 2) Calculate the power spectral density of the scraped surface morphology data in the x and y directions respectively to obtain the mean power spectral density:

[0136] 2.1) Collect surface morphology data in the x and y directions. and The mean line was adjusted to zero, and the surface morphology data of the scraped surface in the x and y directions after the mean line was zeroed were obtained;

[0137] 2.2) Based on the surface morphology data in the x and y directions after zeroing the mean line, calculate the power spectral density respectively, such as... Figure 3 The PSD curve shown.

[0138] 2.3) Perform a double logarithmic transformation on the power spectral density in the x and y directions, and take the mean of the double logarithmic power spectral density in the x and y directions as the mean power spectral density.

[0139] 3) Obtain bifractal characteristic parameters based on the mean power spectral density; among which, the bifractal characteristic parameters include fractal dimension, fractal coefficient, maximum frequency index, and critical frequency index.

[0140] 3.1) Construct a fitting formula based on the Sigmoid function; use the fitting formula to fit the curve, and the fitting result is as follows: Figure 3 As shown, the first asymptote The second asymptote The fitting yielded =-1.24、 =-2.37、 =-26.6765、 =-17.5879、 =0.49 and =7.92.

[0141] 3.2) Calculate the first fractal dimension based on the undetermined parameters. Second fractal dimension Maximum frequency index and critical frequency index ,get =2.88、 =2.315、 =25 and =19.

[0142] 3.3) Calculate the first fractal coefficient based on the undetermined parameters and fractal dimension. Second fractal coefficient Specific values: =3× m、 =4× m.

[0143] 4) Input the bifractal feature parameters into the topography simulation formula to obtain the simulated bifractal surface. The results are as follows: Figure 4 As shown.

[0144] 5) Set the cross-sectional height to truncate the simulated bifractal surface, forming truncated regions and truncated portions; calculate the area of ​​each truncated region and the volume of each truncated portion; treat the truncated portion as a micro-protrusion and determine the deformation of each micro-protrusion:

[0145] 5.1) Set the cross-sectional height to simulate a bifractal surface, such as... Figure 5 As shown. , initial value The value is 1. Each truncated region is identified using the 8-connected component method. Figure 6 This is a schematic diagram of the method.

[0146] 5.2) Calculate the area of ​​each cut-off region and the volume of each cut-off part.

[0147] 5.3) Treating the truncated portion as a micro-protrusion, determine the base length of each micro-protrusion based on the area of ​​the truncated region and the corresponding volume of the truncated portion; determine the deformation amount of each micro-protrusion based on the base length of each micro-protrusion. Figure 7 This is a schematic diagram of the method.

[0148] 6) Based on the deformation amount and critical value of each micro-protrusion, determine the deformation stage of each micro-protrusion; calculate the stiffness of each micro-protrusion based on its deformation stage, and then sum them to obtain the total stiffness.

[0149] 6.1) Determine the deformation stage of each micro-protrusion.

[0150] 6.2) Calculate the contact area, contact load, and contact stiffness of each micro-protrusion based on its deformation stage.

[0151] 6.3) Summing up the contact area, contact load, and contact stiffness of all micro-protrusions respectively, we can obtain the total contact area, total contact load, and total contact stiffness of the micro-protrusions.

[0152] 7) Change the cutoff coefficient with a step size of 0.01 (in this embodiment) It takes values ​​in the range of 1 to 0.4, the first... The cutoff coefficient in the next cycle satisfy: , Step size, (Initial value is 1, total number of cycles is preset value), change the section height, repeat steps 5) and 6) to calculate the load-stiffness curve.

[0153] 8) Repeat steps 4), 5), 6), and 7), and take the average value of all load-stiffness curves as the final simulation result, such as... Figure 8 As shown. A compression experiment was conducted on a real surface, and the experimental results are as follows. Figure 8As shown, the load-stiffness curve results are in good agreement, verifying the rationality of the method provided by this invention.

[0154] According to a second aspect of the present invention, a device for acquiring the stiffness parameters of a scraped surface based on digital simulation is provided, comprising modules of any of the methods described above. Specifically, it includes: a first module for performing step 1: measuring the one-dimensional profile of the scraped surface in the x and y directions to obtain surface topography data in the x and y directions; a second module for performing step 2: calculating the power spectral density of the surface topography data in the x and y directions respectively to obtain the mean power spectral density; a third module for performing step 3: obtaining bifractal characteristic parameters based on the mean power spectral density; wherein the bifractal characteristic parameters include a first fractal dimension, a second fractal dimension, a first fractal coefficient, a second fractal coefficient, a maximum frequency exponent, and a critical frequency exponent; and a fourth module. The first module is used to execute step 4: inputting the bifractal feature parameters into the topography simulation formula to obtain the simulated bifractal surface; the second module is used to execute step 5: setting the cross-sectional height to truncate the simulated bifractal surface, forming truncated regions and truncated parts; calculating the area of ​​each truncated region and the volume of the corresponding truncated part; treating the truncated part as a micro-protrusion and determining the deformation amount of each micro-protrusion; the third module is used to execute step 6: determining the deformation stage of each micro-protrusion based on the deformation amount and the deformation threshold; calculating the stiffness of each micro-protrusion based on the deformation stage of each micro-protrusion, and then summing them to obtain the total stiffness. For parts of each module not described in detail, please refer to the relevant descriptions in other embodiments.

[0155] According to a third aspect of the present invention, a terminal is provided, including a processor, a memory, and a computer program stored in the memory and executable on the processor, the processor being configured to perform the steps of the method described in any one of the foregoing embodiments.

[0156] The specific embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention.

Claims

1. A method for obtaining a lapping surface stiffness parameter based on digitized simulation, characterized in that, The method comprises the following steps: Step 1: measure the one-dimensional profile of the x-direction and y-direction of the scraped surface to obtain the x-direction and y-direction scraped surface topography data; Step 2: calculate the power spectral density of the x-direction and y-direction scraped surface topography data respectively to obtain the mean power spectral density; Step 3: obtain the bifractal characteristic parameters according to the mean power spectral density; wherein the bifractal characteristic parameters include the first fractal dimension, the second fractal dimension, the first fractal coefficient, the second fractal coefficient, the maximum frequency index and the critical frequency index; Step 4: input the bifractal characteristic parameters into the topography simulation formula to obtain the simulated bifractal surface; Step 5: set the cross-sectional height to truncate the simulated bifractal surface to form a truncated region and a truncated part; calculate the area of each truncated region and the volume of the corresponding truncated part; take the truncated part as a microconvex body to determine the deformation amount of each microconvex body; Step 6: determine the deformation stage of each microconvex body according to the deformation amount and the deformation amount critical value of the microconvex body; calculate the contact area, contact load and contact stiffness of each microconvex body according to the deformation stage of each microconvex body; and sum up the contact area, contact load and contact stiffness of all microconvex bodies to obtain the total contact area, total contact load and total contact stiffness of the microconvex body.

2. The method of claim 1, wherein, The step 2 is specifically: Step 2.1: adjust the mean line of the x-direction and y-direction scraped surface topography data and to zero to obtain the x-direction and y-direction scraped surface topography data after the mean line is adjusted to zero; Step 2.2: calculate the power spectral density according to the x-direction and y-direction scraped surface topography data after the mean line is adjusted to zero; Step 2.3: perform double logarithmic conversion on the power spectral density of the x-direction and y-direction, and take the mean value of the double logarithmic power spectral density of the x-direction and y-direction as the mean power spectral density.

3. The method of claim 1, wherein, The step 3 is specifically: Step 3.1: construct a fitting formula based on the Sigmoid function; take the mean power spectral density as the input of the fitting formula to obtain the undetermined parameters by fitting; Step 3.2: calculate the first fractal dimension, the second fractal dimension, the maximum frequency index and the critical frequency index according to the undetermined parameters; Step 3.3: calculate the first fractal coefficient and the second fractal coefficient according to the undetermined parameters and the fractal dimension.

4. The method of claim 1, wherein, The topography simulation formula is: ； wherein represents a simulated bifractal surface; is a constant; represents a bifractal surface length; is the number of superimposed cosine waves; , are first and second fractal coefficients, respectively; , are first and second fractal dimensions, respectively; is a critical frequency exponent; is a frequency exponent; is a random distribution between [0, 2π]; is an abscissa of a bifractal surface data point; is an ordinate of a bifractal surface data point; is a maximum frequency exponent.

5. The method of claim 1, wherein, The step 5 is specifically: Step 5.1: set the cross-sectional height to truncate the simulated bifractal surface to form a truncated region and a truncated part, and use the eight-connected domain method to identify each truncated region on the cross section; Step 5.2: calculate the area of each truncated region and the volume of each truncated part; Step 5.3: take the truncated part as a microconvex body, determine the base length of each microconvex body according to the area of the truncated region and the volume of the corresponding truncated part, and determine the deformation amount of each microconvex body according to the base length of each microconvex body.

6. The method of claim 1, wherein, The deformation amount ω calculation formula is: ； wherein , is the area of the truncated region; if , = 1 , = 0 ; if , = 1 , = 0 ; and are the first and second fractal dimensions, and are the first and second fractal coefficients; is the critical frequency exponent, is a constant; is the micro-asperity base length.

7. The method of claim 1, wherein, The step 6 is specifically: Step 6.1: determine the deformation stage of each microconvex body as the elastic deformation stage, the first elastic-plastic deformation stage, the second elastic-plastic deformation stage or the complete plastic deformation stage according to the deformation amount and the deformation amount critical value of the microconvex body; Step 6.2: calculate the contact area, contact load and contact stiffness of each microconvex body according to the deformation stage of each microconvex body; Step 6.3: sum up the contact area, contact load and contact stiffness of all microconvex bodies to obtain the total contact area, total contact load and total contact stiffness of the microconvex body.

8. The method of claim 7, wherein, The deformation level of each micro-protrusion is determined based on its deformation amount and critical deformation value. Specifically, when the deformation amount... ≤ At that time, the micro-protrusion is in the elastic deformation stage; when < ≤6 At that time, the micro-protrusion is in the first stage of elastic-plastic deformation; when 6 < ≤110 At that time, the micro-protrusion is in the second stage of elastic-plastic deformation; when 110 < The micro-protrusions are in the stage of complete plastic deformation; among them, This is the critical value for deformation.

9. A device for obtaining a scribing surface stiffness parameter based on digitized simulation, characterized in that, A module comprising the method of any of claims 1-8.

10. A terminal, characterized by: A processor, a memory, and a computer program stored in the memory and executable on the processor, the processor being configured to perform the method of any of claims 1-8.

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