Method and system for detecting surface defects of smooth materials

Abstract

The present invention relates to the field of detection and inspection technology, and discloses a method and system for detecting surface defects of smooth materials. The method for detecting surface defects of smooth materials comprises the following steps: S1. unfolding a surface, establishing a coordinate axis xOyOz, and obtaining contour data of the unfolded surface; S2. dividing the contour data along the z axis, obtaining K groups of curve data, and fitting each group of curve data at the coordinate x k O k y k The inner curve y k =f(x k ); S3. Get each coordinate x k O k y k Falls inside the curve y k =f(x k ) as the labeled data; S4. Connect the adjacent coordinates x k O k y k The marking data within the defect range M is obtained. The method and system for detecting surface defects of smooth materials disclosed in the present invention obtain defect information by analyzing contour data, thereby avoiding the defect that the image information of transparent materials cannot be accurately obtained in the visual detection method, and the defect that the existing laser contour detection method cannot accurately obtain the surface contour, and solves the problem that the defect information cannot be obtained because there is no standard data for comparison.

Description

Technical Field

[0001] The present invention relates to the field of detection and inspection technology, and in particular to a method and system for detecting surface defects of smooth materials. Background Art

[0002] Surface defect detection methods are technical means used to detect various flaws, damages and other defects on the surface of objects. A common method is machine vision detection, which uses cameras and other equipment to obtain images of the surface of objects, and then analyzes the images through image processing algorithms to identify defects. It has fast detection speed and high accuracy, and is widely used in industrial production lines such as metal sheets and plastic products. However, machine vision detection methods are easily affected by material properties and on-site noise. For example, the surface of transparent materials is reflective and confused with the background, so machine vision detection methods are no longer suitable.

[0003] A new surface defect detection method, laser profile detection, is proposed. That is, a coordinate axis is established and a line laser profile sensor is used to obtain the surface profile data of the product. The profile data is then compared with the standard data to determine whether there are defects and the location of the defects.

[0004] However, the laser profile detection method has new defects:

[0005] First, when there is a need for defect detection for a single customized product, the contour data obtained by the sensor has no standard data to compare with, and the defect location cannot be determined using traditional methods;

[0006] Second, the specific method of laser contour detection is to translate the linear laser contour sensor so that the linear light it emits (the linear light extends along the X-axis as a whole and is emitted along the Y-axis) is translated along the Z-axis. During the translation process, the Y-axis data of the surface corresponding to the light is obtained, so that the data set of the product surface contour in the coordinate axis can be obtained. By comparing the data set with the standard data, the defect information can be obtained. However, this method is not accurate for some curved surface data. This is because when the product curvature is such as Figure 1 As shown, when the light beam a is directed to a certain location, there are two Y-axis data, Ya and Ya'. When the sensor translates along the Z-axis, Ya and Ya' cannot be obtained at the same time, which will cause inaccurate defect detection. Summary of the invention

[0007] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, one object of the present invention is to provide a method for detecting surface defects of smooth materials.

[0008] Another object of the present invention is to provide a system for detecting surface defects of smooth materials.

[0009] According to a method for detecting surface defects of a smooth material proposed by the present invention, the detection method is applied to a curved surface and comprises the steps of:

[0010] S1. Unfold the surface, establish the coordinate axis xOyOz, and obtain the contour data of the unfolded surface;

[0011] S2. Split the contour data along the z axis, obtain K groups of curve data, and fit each group of curve data at the coordinate x k O k y k The inner curve y k =f(x k );

[0012] S3. Get each coordinate x k O k y k Falls inside the curve y k =f(x k ) as the labeled data;

[0013] S4. Connect adjacent coordinates x k O k y k The marked data within is used to obtain the defect range M.

[0014] The purpose of such setting is: the method first unfolds the surface, directly obtains the contour data of the surface, and obtains the defect information by analyzing the contour data, thereby avoiding the defect that the image information of transparent materials cannot be accurately obtained in the visual inspection method, and at the same time avoids the defect that the existing laser contour inspection method cannot accurately obtain the surface contour;

[0015] Secondly, the surface is divided into countless curves, and the mathematical expression of each curve is fitted. The coordinates that are not on the curve are obtained by calculation, so as to know the defect location, solving the problem of not being able to obtain defect information because there is no standard data for comparison.

[0016] In some examples of the present invention, step S1 includes: establishing an axis for the curved surface so that the curved surface can be completely exposed to the light beam of the line laser profile sensor when an angular displacement occurs along the axis, and the line laser profile sensor acquires profile data.

[0017] The purpose of such setting is: the principle of laser profile sensor is to emit a light beam, which is reflected after encountering the surface of an object. The contour information of the object surface can be obtained by calculating the propagation distance of the light beam. However, for curved surface structures, the contour information of the curved surface cannot be fully obtained by translation alone. The solution that can be chosen is to unfold the curved surface. Specifically, the laser profile sensor is stationary and the curved surface rotates, which is equivalent to the laser profile sensor still translating relative to the curved surface, that is, the curved surface is unfolded.

[0018] In some examples of the present invention, the displacement distance data of the line laser profile sensor passing through the curved surface is used as the z-axis data.

[0019] The purpose of this setting is to enable the sensor to obtain the contour data of the surface when it is unfolded by rotating the surface. These data need to be corresponded in the coordinate axis for subsequent calculations, where the width of the light beam emitted by the line laser contour sensor is used as the x-axis data, the distance between the sensor and the object surface is obtained as the y-axis data, and the z-axis data is represented by the distance the sensor is displaced relative to the object surface.

[0020] In some examples of the present invention, step S2 includes:

[0021] S2a. Select coordinate x k O k y k Discrete points on the inner curve;

[0022] S2b. Obtain the fitting curve based on the discrete points, marked as follows:

[0023] The fitting curve corresponding to Z1 is: y1=f(x1)=a1+b Z11 x1+b Z12 x1 2 +……+b Z1n x1 n ;

[0024] The fitting curve corresponding to Z2 is: y2=f(x2)=a2+b Z21 x2+b Z22 x2 2 +……+b Z2n x2 n ;

[0025] ……;

[0026] Z k The corresponding fitting curve is: k =f(x k )=a k +b Zk1 x k +b Zk2 x k 2 +……+b Zkn x k n .

[0027] The purpose of this setting is to divide the acquired surface contour data into several curves, take several points on each curve for fitting, and obtain the curve expression. Since this method is aimed at the detection of smooth surfaces, the surface contour is relatively smooth, and the segmented curves are also smooth curves. The fitted curve expression can basically cover all points on the curve, and the R of the fitted curve is 2 The value is very close to 1, so the fitted curve formula is used to represent the corresponding curve, and the set of all curves is used to represent the surface.

[0028] In some examples of the present invention, step S3 includes:

[0029] S3a. Get the coordinate x in segments k O k y k Substitute the discrete points on the inner curve into the corresponding fitting curve for verification, and mark the data that failed the verification;

[0030] S3b. Eliminate the marked data within the tolerance range;

[0031] S3c. Substitute the curve formula and traverse the adjacent data of the marked data until the data falls into the tolerance range again as the final marked data.

[0032] The purpose of such setting is that the resolution of the line laser sensor is at the nanometer level, while the general defect detection is at the micron level. If all points are substituted into the curve for verification, the calculation efficiency will decrease. Therefore, the coordinate values ​​can be obtained in segments for verification. The points that fail to be verified are points that are not on the coordinate axis; and the points that are not on the coordinate axis may be within the error range of the surface, so these marked points need to be eliminated. As for the remaining marked points, they are points within the defect range. The points adjacent to the point are verified. If the verification fails and the elimination fails, it is also marked as a defective point. Then the adjacent points are verified until the verification is successful or the elimination is successful, and the defective section on the curve can be obtained.

[0033] In some examples of the present invention, the segment distance in step S3a is less than the minimum possible defect length;

[0034] Specifically, for example, according to past experience, the defect type of a certain product is a tool scratch, and its minimum recorded width is 0.2 um, so the segment spacing in step S3a is less than 0.2 um.

[0035] In some examples of the present invention, the method for eliminating the marked data in step S3b is: substitute the x-axis value of the marked data into the y-axis value obtained by the corresponding curve formula, and obtain the tolerance range by the y-axis value ± error, and determine whether the y-axis value of the marked data falls within the tolerance range. If so, eliminate it, otherwise retain it.

[0036] In some examples of the present invention, step S5 is also included:

[0037] S5a. Split the contour data along the x-axis, obtain L groups of curve data, and fit each group of curve data at coordinate z L O L y L The inner curve y L =f(z L );

[0038] S5b. Get each coordinate z L O L y L Falls inside the curve y L =f(z L ) as the labeled data;

[0039] S5c. Connect adjacent coordinates z L O L y L The marking data within the defect range M' is obtained;

[0040] S5d. Obtain the combination of range M and range M'.

[0041] The purpose of such setting is to segment the contour data along the x-axis, obtain the defect range of the contour surface again, and compare the range M with the range M' to verify or check for omissions and fill in gaps.

[0042] According to the detection system of smooth material surface defects proposed by the present invention, it is applied to the above-mentioned detection method of smooth material surface defects, including a line laser profile sensor, a data acquisition module, a conversion module, a segmentation module, a calculation module and a display module; the laser profile sensor is used to collect distance data from the measured surface to the laser profile sensor and width data of the measured surface, respectively as y-axis data and x-axis data, and the data acquisition module is used to collect displacement distance data of the line laser profile sensor passing through the curved surface as z-axis data; the output end of the laser profile sensor and the output end of the data acquisition module are both electrically connected to the input end of the conversion module, and the conversion module is used to convert the data collected by the laser profile sensor and the data acquisition module into coordinate values ​​to establish a profile model of the measured surface; the output end of the conversion module is electrically connected to the input end of the segmentation module, and the segmentation module is used to segment the profile model along the Z axis or along the X axis to obtain multiple groups of curve data; the output end of the segmentation module is electrically connected to the input end of the calculation module, and the calculation module is used to calculate the defect range; the output end of the conversion module and the output end of the calculation module are both electrically connected to the input end of the display module, and the display module is used to display the profile model of the measured surface and the defect range.

[0043] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 It is a schematic diagram of obtaining the surface profile by using a line laser profile sensor in the background technology of the present invention;

[0046] Figure 2 This is a schematic diagram of the structure of the product to be detected in an embodiment of the present invention;

[0047] Figure 3 is a contour model of the outer surface of the product to be inspected after being unfolded in the embodiment of the present invention;

[0048] Figure 4 Schematic diagram of the defect range of the outer surface of the product in an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "multiple" means two or more.

[0051] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0052] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The embodiments described below are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0053] Please see attached Figure 2 , which is a structural diagram of a customized product, whose outer surface is a smooth curved surface. Taking this product as an example, the method for detecting surface defects of smooth materials provided in this embodiment is described, that is, this method is used to detect whether the outer surface of the product has defects.

[0054] In order to verify the detection effect, a 3um thick machining knife was used to scratch the product surface before the test.

[0055] The specific detection method is:

[0056] For the first step, please see the attached Figure 2 , establish axis L for the outer surface of the product, make the outer surface rotate along axis L from curve Q, and the rotation direction is g. The line laser profile sensor emits light along direction F in a stationary state to ensure that the light width d completely covers the width of the outer surface of the product. Establish the coordinate axis xOyOz, and obtain the distance from the line laser profile sensor to the product surface as the y-axis data, the width data of the outer surface as the x-axis data, and the displacement distance data of the line laser profile sensor passing through the curved surface as the z-axis data. Figure 3 The contour model after the outer surface is unfolded is shown. In this contour model, the x-axis range is 0~2.6cm, the y-axis range is 0.16~1.32cm, and the z-axis range is 0~3.46cm.

[0057] The second step is to segment the contour model along the z-axis with a segmentation interval of 2um, and obtain K=3.46cm / 2um=173 groups of curve data, marked as K1, K2, ..., K 173 , 130 discrete points are taken on each curve, the spacing between discrete points is 2um, and the 130 discrete points corresponding to each curve are fitted using polynomial fitting to obtain the fitting curve:

[0058] The fitting curve corresponding to Z1 is: y1=f(x1)=-0.0007x1 2 +0.2882x1+14.294, R 2 =0.9937;

[0059] ……;

[0060] Z 45 The corresponding fitting curve is: 45 =f(x 45 )=-0.0019x 45 2 +0.8259x 45 +38.428, R 2 =0.9918;

[0061] ……;

[0062] Z 173 The corresponding fitting curve is: 173 =f(x 173 )=-0.0007x 173 2 +0.2753x 173 +13.67, R 2 =0.9956;

[0063] Each fitting curve y k =f(x k ) 2 The values ​​are all greater than 0.99.

[0064] The third step is that the thickness of the machining tool is 3um, and it is inferred that the minimum possible defect length on the product is 3um. Therefore, taking the x-axis coordinate as the reference and 2um as the interval, 130 discrete points are obtained on each curve and substituted into y1=f(x1), y2=f(x2), ..., y 173 =f(x 173 ) for verification;

[0065] It is found that the data that failed the verification appears in Z 39 ~Z 70 On the corresponding curve, the coordinates of the failed verification are shown in Table 1:

[0066] Table 1

[0067] <![CDATA[Z 39 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 40 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 41 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 42 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 43 ]]> <![CDATA[(x 30 ,and 30 )]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 44 ]]> <![CDATA[(x 30 ,and 30 )]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[(x 35 ,and 35 )]]> <![CDATA[Z 45 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[(x 35 ,and 35 )]]> <![CDATA[Z 46 ]]> <![CDATA[(x 30 ,and 30 )]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 47 ]]> <![CDATA[(x 30 ,and 30 )]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 48 ]]> <![CDATA[(x 30 ,and 30 )]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 49 ]]> <![CDATA[(x 30 ,and 30 )]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 50 ]]> <![CDATA[(x 30 ,and 30 )]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 51 ]]> <![CDATA[(x 30 ,and 30 )]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[(x 35 ,and 35 )]]> <![CDATA[Z 52 ]]> <![CDATA[(x 30 ,and 30 )]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 53 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 54 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 55 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 56 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 57 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[(x 35 ,and 35 )]]> <![CDATA[Z 58 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[(x 35 ,and 35 )]]> <![CDATA[Z 59 ]]> <![CDATA[(x 30 ,and 30 )]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[(x 35 ,and 35 )]]> <![CDATA[Z 60 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[(x 35 ,and 35 )]]> <![CDATA[Z 61 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 62 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 63 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 64 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 65 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 66 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 67 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 68 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 69 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 70 ]]> <![CDATA[(x 32 ,and 32 )]]>

[0068] Substitute the x-axis value of the marked data in Table 1 into the corresponding curve formula to obtain the y-axis value. The y-axis value ±0.5um is the tolerance range. For example: 45 The corresponding x31 =62um Substitute into curve y 45 =f(x 45 )=-0.0019x 45 2 +0.8259x 45 +38.428, the y value is 96.9374um, and the range of 96.9374um±0.5um is 96.4374um~97.4374um, while y 31 The value is 97.1254um, which falls within the tolerance range and should be eliminated;

[0069] The coordinate range of the retained marker data is shown in Table 2:

[0070] Table 2

[0071] <![CDATA[Z 39 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[Z 40 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[Z 41 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[Z 42 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[Z 43 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 44 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 45 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 46 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 47 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 48 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 49 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 50 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 51 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 52 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 53 ]]> <![CDATA[(x 31 ,and 31 )]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 54 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 55 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 56 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 57 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 58 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 59 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 60 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[(x 34 ,and 34 )]]> <![CDATA[Z 61 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 62 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 63 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 64 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 65 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 66 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 67 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[(x 33 ,and 33 )]]> <![CDATA[Z 68 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[Z 69 ]]> <![CDATA[(x 32 ,and 32 )]]> <![CDATA[Z 70 ]]>

[0072] Traverse the adjacent data of each labeled data in Table 2, for example, (x 32 ,y 32 )'s adjacent coordinates (x 31 ,y 31 )(x 33 ,y 33 ) are substituted into y 45 =f(x 45 ) to verify and find that the coordinates (x 31 ,y 31 ) Although the verification fails, it is within the tolerance range and is eliminated. (x 33 ,y 33 ) then the verification fails and is out of tolerance, so it is marked. Then (x 33 ,y 33 ) is verified by the adjacent coordinates and it is found that 35 ,y 35 ), the data falls back into the tolerance range, so Z 45 The corresponding coordinates (x 32 ,y 32 ), (x 33 ,y 33 )、(x 34 ,y 34 ) are used as the final labeled data.

[0073] Step 4: Connect adjacent coordinates x k O k y k The marking data within the defect range M is obtained. For example, the coordinates x 45 O 45 y 45 The coordinates (x 32 ,y32 ) and coordinate x 43 O 43 y 43 The coordinates (x 32 ,y 32 ), and the coordinate x 45 O 45 y 45 The coordinates (x 32 ,y 32 ) and coordinate x 46 O 46 y 46 The marker coordinates (x 32 ,y 32 ) connection; get the tag range M.

[0074] The fifth step is to split the contour data along the x-axis, obtain L groups of curve data, and fit each group of curve data at the coordinate z L O L y L The inner curve y L =f(z L ); Then get each coordinate z L O L y L Falls inside the curve y L =f(z L ) as the label data; then connect the adjacent coordinates z L O L y L The marked data in the range is obtained to obtain the defect range M'; finally, the combination of the range M and the range M' is obtained;

[0075] It is found that the combination of range M and range M' is still as shown in Table 2, which means that in the coordinate axis Figure 4 shown.

[0076] Other components of the method for detecting surface defects of smooth materials according to the embodiment of the present invention, such as a line laser profile sensor and the like, and operations are known to those skilled in the art and will not be described in detail here.

[0077] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0078] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

Claims

1. A method for detecting surface defects of smooth materials, characterized in that: The detection method is applied to a curved surface and comprises the steps of: S1. Unfold the surface, establish the coordinate axis xOyOz, and obtain the contour data of the unfolded surface, including: An axis is established for the curved surface so that the curved surface can be completely exposed to the beam of the line laser profile sensor when the curved surface is angularly displaced along the axis, and the line laser profile sensor obtains profile data, and the line laser profile sensor obtains the distance from the line laser profile sensor to the product surface as y-axis data, the width data of the outer surface as x-axis data, and the displacement distance data of the line laser profile sensor passing through the curved surface as z-axis data; S2. Segment the contour data along the z axis, obtain K groups of curve data, and fit each group of curve data at the coordinate x. k O k y k The inner curve y k =f(x k );include: S2a. Select coordinate x k O k y k Discrete points on the inner curve; S2b. Obtain the fitting curve based on the discrete points, marked as follows: The fitting curve corresponding to Z1 is: y1=f(x1)=a1+b Z11 x1+b Z12 x1 2 +……+b Z1n x1 n ; The fitting curve corresponding to Z2 is: y2=f(x2)=a2+b Z21 x2+b Z22 x2 2 +……+b Z2n x2 n ; ……； Z k The corresponding fitting curve is: k =f(x k )=a k +b Zk1 x k +b Zk2 x k 2 +……+b Zkn x k n ; S3. Get each coordinate x k O k y k Falls inside the curve y k =f(x k ) as label data; including: S3a. Get the coordinate x in segments k O k y k Substitute the discrete points on the inner curve into the corresponding fitting curve for verification, and mark the data that failed the verification; S3b. Eliminate the marked data within the tolerance range; the marked data is eliminated by substituting the x-axis value of the marked data into the corresponding curve formula to obtain the y-axis value, the y-axis value ± error to obtain the tolerance range, and determine whether the y-axis value of the marked data falls within the tolerance range. If so, it is eliminated, otherwise it is retained; S3c. Substitute the curve formula and traverse the adjacent data of the marked data until the data falls into the tolerance range again as the final marked data; S4. Connect adjacent coordinates x k O k y k The marked data within is used to obtain the defect range M.

2. The method for detecting surface defects of a smooth material according to claim 1, characterized in that: The segmentation distance in step S3a is smaller than the possible minimum defect length.

3. The method for detecting surface defects of a smooth material according to claim 1 or 2, characterized in that: The step S5 is also included: S5a. Split the contour data along the x-axis, obtain L groups of curve data, and fit each group of curve data at coordinate z L O L y L The inner curve y L =f(z L ); S5b. Get each coordinate z L O L y L Falls inside the curve y L =f(z L ) as the labeled data; S5c. Connect adjacent coordinates z L O L y L The marking data within the defect range M' is obtained; S5d. Obtain the combination of range M and range M'.

4. A system for detecting surface defects of smooth materials, characterized in that: A method for detecting surface defects of smooth materials as described in any one of claims 1 to 3, comprising a line laser profile sensor, a data acquisition module, a conversion module, a segmentation module, a calculation module and a display module; the laser profile sensor is used to collect distance data from a measured surface to the laser profile sensor and width data of the measured surface as y-axis data and x-axis data, respectively, and the data acquisition module is used to collect displacement distance data of the line laser profile sensor passing through a curved surface as z-axis data; the output end of the laser profile sensor and the output end of the data acquisition module are both electrically connected to the input end of the conversion module, and the conversion module is used to collect the displacement distance data of the line laser profile sensor passing through a curved surface as z-axis data; the output end of the laser profile sensor and the output end of the data acquisition module are both electrically connected to the input end of the conversion module, and the conversion module is used to collect the displacement distance data of the line laser profile sensor passing through a curved surface as z-axis data. The conversion module is used to convert the data collected by the laser contour sensor and the data acquisition module into coordinate values ​​to establish a contour model of the measured surface; the output end of the conversion module is electrically connected to the input end of the segmentation module, and the segmentation module is used to segment the contour model along the Z axis or along the X axis to obtain multiple groups of curve data; the output end of the segmentation module is electrically connected to the input end of the calculation module, and the calculation module is used to calculate the defect range; the output end of the conversion module and the output end of the calculation module are both electrically connected to the input end of the display module, and the display module is used to display the contour model of the measured surface and the defect range.

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