A method for evaluating the quality of a roving line

Abstract

A kind of quantitative evaluation method of Roping line based on plate surface three-dimensional morphological image and mean profile curve, comprising the following steps, S1: for the plate surface three-dimensional morphological image obtained, establish the representation based on one-dimensional mean profile curve;S2: threshold search is carried out to mean profile curve, and peak and valley and characteristic parameter of mean profile curve are obtained according to search and calculation;S3: according to peak and valley and characteristic parameter, establish the Roping line intensity index of measurement mean profile curve, and form the quantitative evaluation of Roping line accordingly.The quantitative evaluation method of Roping line based on plate surface three-dimensional morphological image and mean profile curve of the present application, through the sample preparation and pretreatment of plate, the acquisition and image pretreatment of surface three-dimensional morphological image, and the calculation of surface mean profile curve and using the set Roping intensity formula, the intensity of plate Roping line is quantitatively evaluated.

Description

Technical Field

[0001] This invention belongs to the field of machine vision in the surface quality inspection of metal sheets, specifically involving a quantification evaluation method based on the three-dimensional morphological image and mean contour curve of the sheet surface. Background Technology

[0002] Sheet metal is one of the most important application forms of metal materials. Sheet metal is commonly used for the shells and covers of industrial products, such as aluminum alloy sheets commonly used in the automotive industry. Therefore, stringent requirements are placed on the surface quality of the formed sheet metal products.

[0003] Due to the unevenness of micro-deformation, during the stamping process of sheet metal, such as aluminum alloy sheet and stainless steel sheet, a series of lines extending along the rolling direction and spaced several millimeters apart are very likely to appear on the surface of the parts. These are called roping lines.

[0004] The strength of the stripe strength refers to the mechanical property parameter corresponding to the fine stripes (stripes) formed on the surface of aluminum alloy sheets during transverse stretching due to uneven deformation of the fiber structure along the rolling direction. Its strength is directly related to processes such as hot rolling coiling temperature and cold rolling reduction, and is usually optimized by adjusting the final hot rolling temperature (e.g., >370℃ for automotive outer panels). This parameter directly affects the surface quality and stamping performance of aluminum alloy automotive sheets.

[0005] These linear textures can reach lengths of tens or hundreds of millimeters, with peak-to-valley height differences of nearly 10–30 μm. They cannot be concealed by painting or baking, severely impacting the appearance quality of sheet metal parts. Therefore, the detection and grading of sheet metal linear textures is crucial for assessing sheet metal quality. Currently, there are only a few internal standards for sheet metal linear texture detection. This primarily involves stretching and slightly polishing the surface of the sheet metal, with technicians relying on their experience to visually inspect the number of linear textures for quality assessment. This process demands very high standards for the quality of the polishing and the experience of the technicians, is time-consuming and labor-intensive, and involves significant subjective factors.

[0006] Some researchers abroad have proposed using three-dimensional morphological information to study and evaluate the strength of sheet metal surface lines, including using profilometers to acquire surface morphological images and cameras to acquire grayscale images after polishing. Guilotin et al. proposed the APSD (Areal Power Spectral Density) method, which converts grayscale images to the frequency domain and uses the ratio of grayscale values ​​in anisotropic and isotropic component regions as a standard to distinguish the strength of the surface lines. However, this method has a large subjective factor in frequency domain region division, and the grading threshold cannot be generalized. Traditional detection methods based on grayscale images also heavily rely on the post-stretching polishing process. Three-dimensional morphological measurement provides an effective tool for the quantitative analysis of the strength of sheet metal surface lines, but quantitative evaluation methods based on morphological data have not yet been reported. Summary of the Invention

[0007] To address the shortcomings of existing methods for evaluating the flatness line of sheet materials, such as lack of objectivity, high experience requirements, and time-consuming and labor-intensive processes, this invention provides a quantitative evaluation method for the flatness line based on three-dimensional morphological images and mean contour curves of the sheet material surface. The specific technical solution is as follows:

[0008] A quantitative evaluation method for Luo Ping lines based on three-dimensional morphological images and mean profile curves of sheet material surfaces is characterized by the following steps:

[0009] S1: Establish a representation based on a one-dimensional mean profile curve for the obtained three-dimensional morphological image of the plate surface;

[0010] S2: Search for peaks and valleys based on thresholds for the mean profile curve and calculate the characteristic parameters of the obtained peaks and valleys;

[0011] S3: Establish a Luoping line intensity index to measure the mean profile curve based on the characteristic parameters of peaks and valleys, and form a quantitative assessment of the Luoping line accordingly.

[0012] According to the present invention, a method for quantitative evaluation of the Luo Ping line based on three-dimensional morphological images and mean profile curves of a plate surface is characterized in that:

[0013] The characteristic parameters include: peak size, peak significance, distance between adjacent peaks, and positive or negative value of adjacent peaks;

[0014] in,

[0015] Peak size, peak significance, and distance between adjacent peaks are represented by values ​​based on the absolute value mean profile curve in each calculation;

[0016] The sign of adjacent peaks is determined based on the original mean profile curve.

[0017] The rolling strength index (RI) is a parameter for quantitatively evaluating the rolling strength of aluminum alloy sheets during the rolling process. The calculation formula is as follows:

[0018] RI = Total curve intensity / (Perfection penalty term × Hyperparameter α), where α is typically taken as 0.5. Typical value range:

[0019] Qiangluo Plain area: RI ≥ 0.75,

[0020] Regions with weak or no Luoping line: RI < 0.3.

[0021] According to the present invention, a method for quantitative evaluation of flattened lines based on three-dimensional morphological images and mean profile curves of sheet material surfaces is characterized by:

[0022] Based on the characteristic parameters of peaks and troughs, a Luoping line intensity index is established to measure the mean profile curve, specifically as follows:

[0023] First, based on the characteristic parameters of the peaks, the intensity index of the Luoping line for each peak is calculated, and the indexes of all peaks are statistically analyzed in ascending order.

[0024] Then, based on the average and extreme values ​​of all peaks, a Luoping line intensity index is established to measure the mean profile curve.

[0025] According to the present invention, a method for quantitative evaluation of flattened lines based on three-dimensional morphological images and mean profile curves of sheet material surfaces is characterized by:

[0026] The positive or negative sign of adjacent peaks is determined according to the established positive and negative rules and the parameters for measuring the positive and negative relationship between adjacent peaks.

[0027] According to the present invention, a method for quantitative evaluation of flattened lines based on three-dimensional morphological images and mean profile curves of sheet material surfaces is characterized by:

[0028] An index for the intensity of the Luo Ping line for each peak is calculated based on its characteristic parameters, and determined by the following formula:

[0029] ,

[0030] In the formula,

[0031] The index used to measure the intensity of the psilocybin line for each peak in a curve;

[0032] The height difference between the peak and zero is the peak value.

[0033] The vertical distance between the peak value and its lowest contour line, i.e., the significance of the peak value;

[0034] The length of the horizontal intercept of the profile curve when the peak significance decreases by half, i.e., the distance between adjacent peaks;

[0035] : A parameter that measures the positive or negative relationship between adjacent peaks.

[0036] According to the present invention, a method for quantitative evaluation of flattened lines based on three-dimensional morphological images and mean profile curves of sheet material surfaces is characterized by:

[0037] Based on the average index of all peaks and the index and value of a specified peak, a Luoping line intensity index for measuring the mean profile curve is established, determined by the following formula:

[0038] ,

[0039] In the formula,

[0040] : An index that measures the intensity of the mean profile curve;

[0041] x: Weight;

[0042] α: Hyperparameter.

[0043] According to the present invention, a method for quantitative evaluation of flattened lines based on three-dimensional morphological images and mean profile curves of sheet material surfaces is characterized by:

[0044] The specific rules for positive and negative signs are as follows:

[0045] Ⅰ: Define the peak value found as positive if it is a local maximum in the original mean profile curve, and negative otherwise;

[0046] II: When the nth peak and trough When the positive and negative values ​​of the two peaks and valleys on the left and right are different, the positive and negative correlation is the best, and the Luoping line characteristic is the most typical.

[0047] According to the present invention, a method for quantitative evaluation of flattened lines based on three-dimensional morphological images and mean profile curves of sheet material surfaces is characterized by:

[0048] The parameter that measures the positive or negative relationship between adjacent peaks is determined according to the following formula:

[0049] ,,

[0050] In the formula,

[0051] : A parameter that measures the positive or negative relationship between adjacent peaks;

[0052] : XOR symbol, i.e., 1 when adjacent peaks and valleys are present, 0 otherwise;

[0053] The nth peak and valley;

[0054] The (n-1)th peak and valley;

[0055] The (n+1)th peak and valley;

[0056] a, b: Optimal selection parameters.

[0057] According to the present invention, a method for quantitative evaluation of Luoping line based on three-dimensional morphological image and mean profile curve of plate surface is characterized in that: the value range of the weight x is [0.2, 0.4].

[0058] According to the present invention, a method for quantitative evaluation of flattened lines based on three-dimensional morphological images and mean profile curves of sheet material surfaces is characterized by:

[0059] pass

[0060] First, preprocessing is performed sequentially, including interpolation denoising, board warpage removal, and height truncation based on a threshold.

[0061] Then, regularization and mean calculation in the width direction are performed sequentially to obtain a one-dimensional mean profile curve.

[0062] According to the present invention, a method for quantitative evaluation of Luo Ping lines based on three-dimensional morphological images and mean profile curves of sheet material surfaces is characterized in that: the obtained one-dimensional mean profile curve is subjected to median filtering to obtain the final mean profile curve.

[0063] According to the present invention, a method for quantitative evaluation of flattened lines based on three-dimensional morphological images and mean contour curves of sheet material surface is characterized in that: the removal of sheet material warpage is accomplished by subtracting the surface obtained by polynomial fitting from the curve after interpolation and denoising.

[0064] According to the present invention, a method for quantitative evaluation of Luo Ping lines based on three-dimensional morphological images and mean profile curves of sheet material surface is characterized by: regularization processing is completed through zero-mean and scaling.

[0065] According to the present invention, a method for quantitative evaluation of Luo Ping lines based on three-dimensional morphological images and mean profile curves of sheet material surface is characterized in that: the threshold in the height truncation based on the threshold is set to [-3μm, 3μm].

[0066] According to the present invention, a method for quantitative evaluation of Luo Ping lines based on three-dimensional morphological images and mean profile curves of sheet material surface is characterized in that: the polynomial fitting is a fifth-order polynomial fitting.

[0067] This invention proposes a quantitative evaluation method for the strength of the Luoping line based on three-dimensional morphological images and mean profile curves of the board surface. Through sample preparation and preprocessing of the board, acquisition and preprocessing of the three-dimensional morphological images of the surface, calculation of the mean profile curve, and the use of a predefined Luoping strength formula, the Luoping line strength of the board is quantitatively evaluated. This provides an effective means for processing large-area morphological images of the board surface and avoiding the influence of board warping. It helps to objectively and accurately evaluate the surface quality of the board, ensure detection efficiency, and reduce the influence of subjective factors. Attached Figure Description

[0068] Figure 1 This is a schematic diagram of the quantitative evaluation steps of the present invention;

[0069] Figure 2 This is a flowchart of the quantitative evaluation method in an embodiment of the present invention;

[0070] Figure 3 This is the preprocessing result of a three-dimensional morphological image of a plate surface with typical Luo Ping line features in an embodiment of the present invention;

[0071] Figure 4 This is the preprocessing result of a three-dimensional morphological image of the plate surface with atypical flat line features in an embodiment of the present invention;

[0072] Figure 5 The input morphological image and the peak and valley search results of the contour mean curve are used in the embodiments of the present invention.

[0073] Figure 6 This is a schematic diagram illustrating the characteristic parameters of the mean profile curve in an embodiment of the present invention.

[0074] Figure 7 These are grayscale images, contour curves, and calculated values ​​of the Luo Ping line intensity for typical and atypical samples in the embodiments of the present invention. Detailed Implementation

[0075] The following is a further detailed description of the Luo Ping line quantitative evaluation method based on three-dimensional morphological images and mean profile curves of a plate surface according to the present invention, with reference to the accompanying drawings and specific embodiments.

[0076] A quantitative evaluation method for Luo Ping lines based on three-dimensional morphological images and mean profile curves of sheet material surfaces includes the following steps:

[0077] S1: Establish a representation based on a one-dimensional mean profile curve for the obtained three-dimensional morphological image of the plate surface;

[0078] S2: Search for peaks and valleys based on thresholds for the mean profile curve and calculate the characteristic parameters of the obtained peaks and valleys;

[0079] S3: Establish a Luoping line intensity index to measure the mean profile curve based on the characteristic parameters of peaks and valleys, and form a quantitative assessment of the Luoping line accordingly.

[0080] in,

[0081] The characteristic parameters include: peak size, peak significance, distance between adjacent peaks, and positive or negative value of adjacent peaks;

[0082] in,

[0083] Peak size, peak significance, and distance between adjacent peaks are represented by numerical values ​​based on the absolute value mean profile curve in each calculation;

[0084] The sign of adjacent peaks is determined based on the original mean profile curve.

[0085] in,

[0086] Based on the characteristic parameters of peaks and troughs, a Luoping line intensity index is established to measure the mean profile curve, specifically as follows:

[0087] First, based on the characteristic parameters of the peaks, the intensity index of the Luoping line for each peak is calculated, and the indexes of all peaks are statistically analyzed in ascending order.

[0088] Then, based on the average and extreme values ​​of all peaks, a Luoping line intensity index is established to measure the mean profile curve.

[0089] in,

[0090] The positive or negative sign of adjacent peaks is determined according to the established positive and negative rules and the parameters for measuring the positive and negative relationship between adjacent peaks.

[0091] The present invention provides a method for quantitative evaluation of the Luoping line based on a three-dimensional morphological image and mean profile curve of a plate surface, characterized in that: an index for calculating the Luoping line intensity of each peak is established based on the characteristic parameters of the peak, and determined according to the following formula:

[0092] ,

[0093] In the formula,

[0094] The index used to measure the intensity of the psilocybin line for each peak in a curve;

[0095] The height difference between the peak and zero is the peak value.

[0096] The vertical distance between the peak value and its lowest contour line, i.e., the significance of the peak value;

[0097] The length of the horizontal intercept of the profile curve when the peak significance decreases by half, i.e., the distance between adjacent peaks;

[0098] : A parameter that measures the positive or negative relationship between adjacent peaks.

[0099] in,

[0100] Based on the average index of all peaks and the index and value of a specified peak, a Luoping line intensity index for measuring the mean profile curve is established, determined by the following formula:

[0101]

[0102] In the formula,

[0103] : An index that measures the intensity of the mean profile curve;

[0104] x: Weight;

[0105] α: Hyperparameter.

[0106] in,

[0107] The specific rules for positive and negative signs are as follows:

[0108] Ⅰ: Define the peak value found as positive if it is a local maximum in the original mean profile curve, and negative otherwise;

[0109] II: When the nth peak and valley When the positive and negative values ​​of the two peaks and valleys on the left and right are different, the positive and negative correlation is the best, and the Luoping line characteristic is the most typical.

[0110] in,

[0111] The parameter that measures the positive or negative relationship between adjacent peaks is determined according to the following formula:

[0112] ,

[0113] In the formula,

[0114] : A parameter that measures the positive or negative relationship between adjacent peaks;

[0115] : XOR symbol, i.e., 1 when adjacent peaks and valleys are present, 0 otherwise;

[0116] The nth peak and valley;

[0117] The (n-1)th peak and valley;

[0118] The (n+1)th peak and valley;

[0119] a, b: Optimal selection parameters.

[0120] in,

[0121] The weight x has a value range of [0.2, 0.4].

[0122] in,

[0123] pass

[0124] First, preprocessing is performed sequentially, including interpolation denoising, board warpage removal, and height truncation based on a threshold.

[0125] Then, regularization and mean calculation in the width direction are performed sequentially to obtain a one-dimensional mean profile curve.

[0126] in,

[0127] The final mean profile curve is obtained by performing median filtering on the obtained one-dimensional mean profile curve.

[0128] in,

[0129] The aforementioned board warpage removal is achieved by subtracting the surface obtained through polynomial fitting from the curve that has undergone interpolation and denoising.

[0130] in,

[0131] Regularization is achieved through zero-mean and scaling.

[0132] The threshold for height truncation based on threshold is set to [-3μm, 3μm].

[0133] in,

[0134] The polynomial fitting described is a fifth-order polynomial fitting.

[0135] Working process, principle and implementation examples

[0136] For ease of understanding, please refer to the following explanations. Figures 1 to 7 The specific process is as follows:

[0137] Step 1: Sample Preparation and Pretreatment of the Aluminum Alloy Sheet. The dimensions of the aluminum alloy sheet sample are 250mm in length and 35mm in width, where the length represents the direction perpendicular to the rolling direction and the width represents the rolling direction. Lightly sand along the length with 2000-grit sandpaper to remove rolling marks from the surface. Use a universal testing machine to stretch the sheet sample to 10% of the engineering strain at a speed of 0.2mm / s. Wipe the surface of the aluminum alloy sheet with industrial alcohol to remove oil stains.

[0138] Step 2: Acquisition and Preprocessing of 3D Morphological Images of the Surface. A white light interferometer was used to acquire 3D morphological images of the deformed surface of the sheet material, specifically obtaining the coordinates of points within the region and surface height information. In the experiment, a region size of approximately 8.20 mm * 4.20 mm was selected, with 8.20 mm along the length direction and 4.20 mm along the width direction. Noise was filled by interpolation of the scanned morphological images, and a fifth-order polynomial fitting of the surface was subtracted to remove board warping. Then, a threshold was applied to truncate the height, with upper and lower limits selected as [-3 μm, 3 μm].

[0139] Step 3: Calculation of Surface Mean Profile Curve and Evaluation of Luoping Line Intensity Based on Intensity Formula Quantization Parameters. First, the preprocessed results of the 3D morphological image are zero-meaned and scaled to the range [-1, 1]. The mean is calculated along the width direction to obtain the mean profile curve. Median filtering is used to smooth the mean curve and reduce curve noise. For example, using n = N / 20 as the median filter parameter is reasonable, where N is the number of pixels in the image along the TD direction, which can preserve the overall curve characteristics and smooth noise fluctuations.

[0140] Subsequently, local maxima and minima (peaks and troughs) of the mean profile curve are searched based on thresholds. The absolute value of the curve is calculated; local maxima and minima are both local maxima within the absolute value curve. Local maxima and minima, i.e., peaks and troughs, are obtained by searching for thresholds based on peak significance, peak size, and distance to adjacent peaks. The peaks and troughs of the mean curve and their characteristic parameters, including peak size, peak significance, peak width, and the sign of adjacent peaks, can be calculated. The specific definitions of the characteristic parameters of the mean profile curve are as follows.

[0141] (1) Peak size is defined as the height difference between the peak's apex and zero, denoted as . .

[0142] (2) Peak prominence is defined as the degree to which a peak stands out from the surrounding signal baseline, and is defined as the vertical distance between the peak and its lowest contour line, denoted as . .

[0143] (3) Peak Width is defined as the length of the horizontal intercept of the profile curve when the peak significance decreases by half, denoted as ;

[0144] (4) Peak Valuance, defined as a parameter that measures the positive or negative relationship between adjacent peaks, is denoted as . The sign of a single peak refers to the fact that a peak found in the searched curve is considered positive if it corresponds to a local maximum in the original mean profile curve, and negative otherwise. When the nth peak... When the positive and negative values ​​of the two peaks and valleys on the left and right are different, the positive and negative correlation is the best, and the Luoping line characteristic is the most typical. The calculation formula is as follows:

[0145] ,

[0146] This represents the XOR symbol, which is 1 when there are adjacent peaks and valleys, and 0 otherwise. a and b are the selection parameters.

[0147] definition Peak Intensity is an index that measures the intensity of the peak line in a curve. The calculation formula is as follows:

[0148] ,

[0149] Assume there is a total Each peak, recorded The overall ordinal statistic is ;

[0150] definition (Roping Intensity) is an index that measures the overall roping intensity of the curve; the denominator is a penalty term, which may indicate excessive fluctuations in brightness or darkness in the graph, possibly due to rolling stripes or other interfering factors; α is a hyperparameter, for example, α = 0.5. The calculation formula is as follows:

[0151] ,

[0152] The constant parameters above are only the current test parameters for the board material. Experimental test results show that the typical Luoping line area... faint or no Luoping line area .

[0153] When evaluating the strength of the flat surface of a sheet material, 3 to 5 typical and flat areas on the sample can be scanned, and the resulting three-dimensional morphological images can be processed using the algorithm described above to calculate the strength. The average value can be used to obtain the quantitative assessment value of the target board strength in Luoping.

[0154] This invention proposes a quantitative evaluation method for the strength of the Luoping line based on three-dimensional morphological images and mean profile curves of the board surface. Through sample preparation and preprocessing of the board, acquisition and preprocessing of the three-dimensional morphological images of the surface, calculation of the mean profile curve, and the use of a predefined Luoping strength formula, the Luoping line strength of the board is quantitatively evaluated. This provides an effective means for processing large-area morphological images of the board surface and avoiding the influence of board warping. It helps to objectively and accurately evaluate the surface quality of the board, ensure detection efficiency, and reduce the influence of subjective factors.

Claims

1. A quantitative evaluation method for Luo Ping lines based on three-dimensional morphological images and mean profile curves of sheet material surfaces, characterized in that... Includes the following steps: S1: Establish a representation based on a one-dimensional mean profile curve for the obtained three-dimensional morphological image of the plate surface; S2: Search for peaks and valleys based on thresholds for the mean profile curve and calculate the characteristic parameters of the obtained peaks and valleys; S3: Based on the characteristic parameters of peaks and valleys, establish a Luoping line intensity index to measure the mean profile curve, and form a quantitative assessment of the Luoping line accordingly. The characteristic parameters include: peak size, peak significance, distance between adjacent peaks, and positive or negative value of adjacent peaks; The Rib strength index (RI) is used to quantitatively evaluate the rib strength of sheet metal after processing and forming. in, Peak size, peak significance, and distance between adjacent peaks are represented by numerical values ​​based on the absolute value mean profile curve in each calculation; The sign of adjacent peaks is determined based on the original mean profile curve. Based on the characteristic parameters of peaks and troughs, a Luoping line intensity index is established to measure the mean profile curve, specifically as follows: First, based on the characteristic parameters of the peaks, the intensity index of the Luoping line for each peak is calculated, and the indexes of all peaks are statistically analyzed in ascending order. Then, based on the average and extreme values ​​of all peaks, a Luoping line intensity index is established to measure the mean profile curve. An index for the intensity of the Luo Ping line for each peak is calculated based on its characteristic parameters, and determined by the following formula: ， In the formula, The index used to measure the intensity of the psilocybin line for each peak in a curve; The height difference between the peak and zero is the peak value. The vertical distance between the peak value and its lowest contour line, i.e., the significance of the peak value; The length of the horizontal intercept of the profile curve when the peak significance decreases by half, i.e., the distance between adjacent peaks; : A parameter that measures the positive or negative relationship between adjacent peaks; Based on the average index of all peaks and the index and value of a specified peak, a Luoping line intensity index for measuring the mean profile curve is established, determined by the following formula: ， In the formula, : An index that measures the intensity of the mean profile curve; Average PI value PI(i): The PI of the i-th peak / valley. n: The total number of peaks / valleys. `sign`: The sign function. It returns 1 if the input is greater than 0, -1 if the input is less than 0, and 0 if the input is equal to 0. 8: Peak / Valley Reference Value x: Weight; α: Hyperparameter.

2. The method for quantitative evaluation of Luo Ping lines based on three-dimensional morphological images and mean profile curves of sheet material surface according to claim 1, characterized in that: The positive or negative sign of adjacent peaks is determined according to the established positive and negative rules and the parameters for measuring the positive and negative relationship between adjacent peaks.

3. The method for quantitative evaluation of Luo Ping lines based on three-dimensional morphological images and mean profile curves of sheet material surface according to claim 2, characterized in that: The specific rules for positive and negative signs are as follows: Ⅰ: Define the peak value found as positive if it is a local maximum in the original mean profile curve, and negative otherwise; II: When the nth peak and valley When the positive and negative values ​​of the two peaks and valleys on the left and right are different, the positive and negative correlation is the best, and the Luoping line characteristic is the most typical.

4. The method for quantitative evaluation of Luo Ping lines based on three-dimensional morphological images and mean profile curves of sheet material surface according to claim 2, characterized in that: The parameter that measures the positive or negative relationship between adjacent peaks is determined according to the following formula: ， In the formula, : A parameter that measures the positive or negative relationship between adjacent peaks; : XOR symbol, i.e., 1 when adjacent peaks and valleys are present, 0 otherwise; The nth peak and valley; The (n-1)th peak and valley; The (n+1)th peak and valley; a, b: Optimal selection parameters.

5. The method for quantitative evaluation of Luo Ping lines based on three-dimensional morphological images and mean profile curves of sheet material surface according to claim 1, characterized in that: The weight x has a value range of [0.2, 0.4].

6. The method for quantitative evaluation of Luo Ping lines based on three-dimensional morphological images and mean profile curves of sheet material surface according to claim 1, characterized in that: First, preprocessing is performed sequentially, including interpolation denoising, board warpage removal, and height truncation based on a threshold. Then, regularization and mean calculation in the width direction are performed sequentially to obtain a one-dimensional mean profile curve.

7. The method for quantitative evaluation of Luo Ping lines based on three-dimensional morphological images and mean profile curves of sheet material surface according to claim 6, characterized in that: The final mean profile curve is obtained by performing median filtering on the obtained one-dimensional mean profile curve.

8. The method for quantitative evaluation of Luo Ping lines based on three-dimensional morphological images and mean profile curves of sheet material surface according to claim 6, characterized in that: The aforementioned board warpage removal is achieved by subtracting the surface obtained through polynomial fitting from the curve that has undergone interpolation and denoising.

9. The method for quantitative evaluation of Luo Ping lines based on three-dimensional morphological images and mean profile curves of sheet material surface according to claim 6, characterized in that: Regularization is achieved through zero-mean and scaling.

10. The method for quantitative evaluation of Luo Ping lines based on three-dimensional morphological images and mean profile curves of sheet material surface according to claim 6, characterized in that: The threshold in the height truncation based on the threshold is set to [-3μm, 3μm].

11. The method for quantitative evaluation of Luo Ping lines based on three-dimensional morphological images and mean profile curves of sheet material surface according to claim 8, characterized in that: The polynomial fitting described is a fifth-order polynomial fitting.

Images