Roughness measuring system and method

Abstract

The invention discloses a roughness measuring system and method, and the system comprises a rotation displacement assembly, a light source emitter, a spectroscope, an image collector, and an image processor. The spectroscope is arranged at a first position along the optical axis direction of laser emitted by the light source emitter; the rotary displacement assembly and the image collector are respectively fixed at a second position and a third position on the two sides of the first position, the first position, the second position and the third position are coaxially arranged, and the connecting line of the first position, the second position and the third position is vertical to the optical axis of the laser; an object to be measured is accommodated on the rotary displacement assembly, and the surface to be measured of the object to be measured faces the image collector; the spectroscope can vertically reflect the laser to a to-be-measured surface and transmit reflected light reflected from the to-be-measured surface to the image collector; the image processor is suitable for extracting correlation features related to roughness from the image data so as to calculate the roughness value of the surface to be measured.

Description

Technical Field

[0001] The present invention relates to the technical field of precision measurement, and in particular to a roughness measurement system and method. Background Art

[0002] Accurate measurement of roughness is crucial to the quality assurance of mechanical products and the improvement of production processes. According to the different contact methods, it can be divided into contact measurement and non-contact measurement. Contact measurement is represented by the stylus method, which is widely used in engineering due to its simple operation and moderate price. However, the stylus method uses a diamond stylus to directly contact the surface of the workpiece, which inevitably scratches the surface and cannot achieve online measurement. The measurement result is affected by the texture placement of the sample block, and the accuracy is limited by linear sampling and the size of the stylus. Non-contact measurement mainly includes white light interferometer, confocal microscope, etc. These instruments are expensive and complicated to operate. They are mainly used in laboratories or places with high product added value and cannot achieve online measurement. Visual roughness measurement method has always been a hot topic in the field of roughness measurement because of its high measurement efficiency, non-contact, low cost and large amount of information obtained. However, in actual measurement, the visual method is often affected by various interference factors, such as light and texture direction. When the imaging environment is given, the texture placement direction of the sample block has a significant impact on the imaging result, which limits the engineering application of the visual roughness measurement method.

[0003] There have been many studies on the ablation of texture interference in the visual measurement process, but the influence of texture direction still exists and cannot be completely eliminated. Summary of the invention

[0004] In view of the above problems, the present invention is proposed to provide a roughness measurement system and method that overcomes the above problems or at least partially solves the above problems.

[0005] According to one aspect of the present invention, there is provided a roughness measurement system, comprising: a rotation displacement component, a light source transmitter, a spectroscope, an image collector and an image processor; the spectroscope is arranged at a first position along the direction of the laser optical axis emitted by the light source transmitter; the rotation displacement component and the image collector are respectively fixed at a second position and a third position on both sides of the first position, the first position, the second position and the third position are coaxially arranged, and a line connecting the first position, the second position and the third position is perpendicular to the optical axis of the laser; an object to be measured is accommodated on the rotation displacement component, and a surface to be measured of the object to be measured faces the image collector; the spectroscope can reflect the laser vertically to the surface to be measured, and transmit the reflected light reflected from the surface to be measured to the image collector; the image processor is connected to the image collector, and is suitable for receiving image data collected by the image collector, and extracting associated features related to roughness from the image data, so as to calculate the roughness value of the surface to be measured.

[0006] Optionally, in the measurement system according to the present invention, the light source transmitter includes a light source and a light source controller, and the light source controller can control the light source to emit circular structure laser with uniform energy distribution in the circumferential direction.

[0007] Optionally, in the measurement system according to the present invention, the image processor includes a processor and a calculator; the processor is suitable for cropping and grayscale processing the image data, and extracting the pixel values ​​of each detection point on the surface to be measured in the image from the processed image as associated features; the calculator is suitable for calculating the roughness value of the surface to be measured based on the pixel values.

[0008] Optionally, in the measuring system according to the present invention, the calculator calculates the roughness value of the surface to be measured based on the following formula: P x is the pixel value of the corresponding pixel point in the image at each detection point on the surface to be tested, R a is the roughness value of each test point on the surface to be tested.

[0009] Optionally, the measurement system according to the present invention further includes: a fixture, including a first fixture and a second fixture that intersect vertically; a spectrometer is arranged at the intersection of the first fixture and the second fixture; a light source emitter is arranged at one end of the first fixture, and an image collector is arranged at one end of the second fixture.

[0010] Optionally, the measuring system according to the present invention further comprises: a light shielding plate arranged at an end of the first fixture away from the light source emitter.

[0011] Optionally, in the measuring system according to the present invention, the diameter of the beam splitter is 50 mm and the model is 40R / 60T.

[0012] Optionally, in the measuring system according to the present invention, the image collector is a BASLER acA2500-14gc industrial camera, and the light source emitter is a KYX635N5-GS1240 circular light source.

[0013] According to another aspect of the present invention, there is provided a method for measuring the surface roughness of an object to be measured, which is suitable for being implemented by the above-mentioned system, and the method comprises: fixing the positions of a rotation displacement component, a light source transmitter, a spectroscope, and an image collector, respectively, wherein the spectroscope is arranged at a first position along the direction of the optical axis of the laser emitted by the light source transmitter, and the rotation displacement component and the image collector are respectively fixed at a second position and a third position on both sides of the first position, the first position, the second position and the third position are coaxially arranged, and a line connecting the first position, the second position and the third position is perpendicular to the optical axis of the laser; placing the object to be measured on the rotation displacement component, wherein the surface to be measured of the object to be measured faces the image collector; starting the light source transmitter and the image collector; sending image data collected by the image collector to an image processor; and using the image processor to extract associated features related to roughness from the image data, thereby calculating the roughness value of the surface to be measured.

[0014] Optionally, in the measurement method according to the present invention, an image processor is used to extract correlation features related to roughness from image data to calculate the roughness value of the surface to be measured, including: cropping and grayscale processing the image data, and extracting the pixel values ​​of each detection point of the surface to be measured in the image from the processed image as correlation features; based on the pixel values, calculating the roughness value of the surface to be measured.

[0015] Optionally, in the measuring method according to the present invention, the roughness value of the surface to be measured is calculated based on the following formula: P x is the pixel value of the corresponding pixel point in the image at each detection point on the surface to be tested, R a is the roughness value of each test point on the surface to be tested.

[0016] According to the solution of the present invention, the vertical light source incident mode can avoid the shadow effect caused by the light source irradiating the surface to be measured, and at the same time, it can reduce the non-negligible influence of slight changes in the texture direction of the surface to be measured on the scattered light field and the image generated by it.

[0017] According to the solution of the present invention, a circular structure laser with uniform energy distribution circumferentially is used to avoid the problem that the non-Gaussian surface formed on the surface to be measured has a certain texture, and the incident light field causes the scattered light field to change under the influence of the texture placement direction, thereby affecting the final image quality.

[0018] It effectively solves the problem of texture direction affecting visual measurement, and the generated feature information can be used for roughness evaluation.

[0019] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0021] Figure 1 A schematic diagram of measuring the surface roughness of an object using an oblique projection method according to an embodiment of the present invention is shown;

[0022] Figure 2 A schematic structural diagram of a roughness measurement system 100 according to an embodiment of the present invention is shown;

[0023] Figure 3 FIG. 1 shows a schematic diagram of the principle of a beam splitter 130 according to an embodiment of the present invention;

[0024] Figure 4 A schematic diagram showing the imaging principle of two grinding textures by the image collector 140 according to one embodiment of the present invention is shown;

[0025] Figure 5 Schematic diagrams of different rotationally symmetric graphics according to an embodiment of the present invention are shown;

[0026] Figure 6 A schematic diagram of a flow chart of a method for generating a simulated grinding surface according to an embodiment of the present invention is shown;

[0027] Figure 7 A schematic diagram of a simulated grinding surface according to an embodiment of the present invention is shown;

[0028] Figure 8 A schematic diagram of a simulation model according to an embodiment of the present invention is shown;

[0029] Fig. 9 A schematic diagram showing simulation results of grinding surfaces with different roughnesses according to an embodiment of the present invention is shown;

[0030] Fig.10 is the number of pixels (P) of the grinding surface with different roughness at different rotation angles (θ) x ) Line chart;

[0031] Fig.11 Flowchart for data analysis of measurement results;

[0032] Fig.12 A schematic diagram of the flow of image processing performed by an image processor;

[0033] Fig.13 It is the fitting curve of Ra and Px calculated based on 9 calibration samples under the 0° texture orientation;

[0034] Fig.14 The experimental results of grinding surfaces with different roughness at different rotation angles;

[0035] Fig.15 The grinding surfaces corresponding to different roughness are rotated with P x The relationship between values;

[0036] Fig.16 FIG. 1 is a schematic flow chart of a roughness measurement method 200 according to an embodiment of the present invention. DETAILED DESCRIPTION

[0037] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0038] like Figure 1 As shown, when the laser is used to measure the surface roughness of an object at an oblique angle, the incident light paths L1 and L2 are not equal, and the light source will produce a partial shadow when it shines on the surface of the object. A slight change in the texture direction has a non-negligible effect on the scattered light field and the image it generates.

[0039] In order to solve the problems existing in the above-mentioned prior art, the solution of the present invention is proposed. The present application proposes a surface roughness measurement system. The system uses a vertical light source incident mode to avoid the shadow effect caused by the light source irradiating the surface to be measured, and at the same time, it can reduce the non-negligible effect of a slight change in the texture direction of the surface to be measured on the scattered light field and the image generated by it.

[0040] In some embodiments, the surface to be tested of the object to be tested may be any surface with a roughness between 10nm and 100nm, and the types of the surface to be tested include Gaussian, non-Gaussian, lathe, grind, polish, etc. In this embodiment, the surface to be tested is a grinding surface as an example for description.

[0041] Figure 2 FIG. 1 is a schematic structural diagram of a roughness measurement system 100 according to an embodiment of the present invention.

[0042] like Figure 2 As described above, the system 100 includes a rotation displacement component 110 , a light source emitter 120 , a spectroscope 130 , an image collector 140 , an image processor 150 , a holder 160 and a light shield 170 .

[0043] The beam splitter 130 is arranged at a first position along the optical axis direction of the laser emitted by the light source emitter 120. The rotation displacement component 110 and the image collector 140 are respectively fixed at a second position and a third position on both sides of the first position. The first position, the second position and the third position are coaxially arranged, and the line connecting the first position, the second position and the third position is perpendicular to the optical axis of the laser. Figure 2 The light source emitted by the light source emitter 120 is horizontally incident, and after passing through the beam splitter 130 with an angle of 45° with the horizontal and vertical directions, the light is vertically irradiated onto the rotation displacement component 110 located at the second position.

[0044] The holder 160 includes a first holder 161 and a second holder 162 intersecting each other vertically. The spectroscope 130 is arranged at the intersection of the first holder 161 and the second holder 162. The light source emitter 120 is arranged at one end of the first holder 161, and the image collector 140 is arranged at one end of the second holder 162.

[0045] The light shielding plate 170 is disposed at an end of the first fixture 161 away from the light source emitter.

[0046] The rotation displacement assembly 110 is arranged directly below the above-mentioned intersection, so that the rotation displacement assembly 110, the beam splitter 130 and the image collector 140 are on the same straight line, and this straight line is perpendicular to the optical axis direction of the laser emitted by the light source emitter 120. It should be noted that the optical axis of the laser emitted by the light source emitter 120 passes through the center of the beam splitter 130.

[0047] In some embodiments, the diameter of the beam splitter is 50 mm, the model is 40R / 60T, the image collector is a BASLERacA2500-14gc industrial camera, and the light source emitter is a KYX635N5-GS1240 circular light source.

[0048] The grinding object is accommodated on the rotation displacement assembly 110 , and the grinding surface of the grinding object faces the image collector 140 .

[0049] In some embodiments, the light source emitter 140 includes an electrically connected light source and a light source controller, and the light source controller can control the light source to emit different types of lasers.

[0050] The beam splitter 130 can vertically reflect the laser light to the grinding surface, and transmit the reflected light reflected from the grinding surface to the image collector 140 .

[0051] In a specific example, refer to Figure 3 , Figure 3 FIG. 1 is a schematic diagram showing a principle of a beam splitter 130 according to an embodiment of the present invention.

[0052] like Figure 3 As shown, the laser emitted by the light source emitter 120 changes its angle through the beam splitter 130 and irradiates the grinding surface of the grinding object vertically, and the total length of its light path is equal, that is, L3+L4=L5+L6. Vertical incidence will not produce shadows, and the reflected light can fully carry the information of the rough surface. This embodiment uses the vertical light source incident method to avoid the shadow effect caused by the light source irradiating the grinding surface, and at the same time, it can reduce the non-negligible influence of the slight change in the texture direction of the grinding surface on the scattered light field and the image generated by it.

[0053] In addition, if Figure 4 As shown, Figure 4 A schematic diagram of the imaging principle of two grinding textures by the image collector 140 according to an embodiment of the present invention is shown.

[0054] refer to Figure 4 There are two textures in (a) and (b), one with a length of L a The light is incident vertically onto the rough surface through the beam splitter. When the surface texture direction changes by 90°, the images presented on the camera receiving surface are respectively b and length L c An image with a width of d that satisfies the following relationship: L b >L a >L c The reason for this phenomenon is that there are certain textures on the non-Gaussian surface. The incident light field changes the scattered light field under the effect of the texture placement direction, which in turn affects the image. To address this phenomenon, this application uses a special central rotation symmetric pattern (such as Figure 5 ) to overcome the influence of this phenomenon on the measurement results.

[0055] Figure 5 Schematic diagrams of different rotationally symmetric patterns according to an embodiment of the present invention are shown. The rotation periods are 120°, 90°, 72°, 60°, 45°, etc. However, after the object is rotated, in order to ensure that the image obtained by rotating the sample block at any angle is consistent with that before the rotation, a special rotationally symmetric pattern is required to ensure that the image completely overlaps with the original pattern after rotating at any angle.

[0056] The only plane figures that do not change after any angle transformation mentioned above are circles or rings. To describe a circle or ring pattern with a mathematical equation, you can use a parametric equation, as follows:

[0057] (1) Define the coordinates of the center of the circle, assuming it is (h, k).

[0058] (2) Define the radius, assume it is r.

[0059] (3) The parameter t is used to vary in the range [0,2π].

[0060] (4) Use the following parametric equation to describe the circle:

[0061] x=h+r*cos(t)

[0062] y=k+r*sin(t)

[0063] The above equation describes the coordinates of each point on the circle and the shape of a circle with a radius of r and a center at the center. If you want to describe a donut pattern, you can make some slight modifications based on the circle. Assume there is an inner radius r1 and an outer radius r2. The donut can be described using the following parametric equation:

[0064] x=h+(r2+r1*cos(t))*cos(t)

[0065] y=k+(r2+r1*cos(t))*sin(t)

[0066] The geometric shape and position of a circle or annulus can be conveniently described using parametric equations or polar coordinate equations, and the parameters and ranges can be adjusted as needed to obtain the desired pattern. The circular ring light sources available on the market have poor focusing performance and uneven energy distribution.

[0067] Therefore, in some embodiments, a circular structure light source with uniform energy distribution is used for experiments. Specifically, the light source emitter 120 includes a light source and a light source controller, and the light source controller can control the light source to emit a circular structure laser with uniform energy distribution.

[0068] The image processor 150 is connected to the image collector 140 and is adapted to receive the image data collected by the image collector 140 and extract the associated features related to the roughness from the image data, so as to calculate the roughness value of the grinding surface.

[0069] In some embodiments, the image processor 150 includes a processor and a calculator. The processor is adapted to perform cropping and grayscale processing on the image data, and extract pixel values ​​of each detection point of the grinding surface in the image from the processed image as associated features. The calculator is adapted to calculate the roughness value of the grinding surface based on the pixel values.

[0070] The calculator calculates the ground surface roughness value based on the following formula:

[0071]

[0072] Px is the pixel value of the corresponding pixel point in the image at each detection point on the grinding surface, R a is the roughness value of each test point on the grinding surface.

[0073] In a specific example, the accuracy of the grinding object surface roughness measurement system 100 of the present application is verified by simulation.

[0074] Before verification, numerical simulation method is used to obtain the grinding surface with specified roughness value. Figure 6 As shown, Figure 6 A schematic flow chart of a method for generating a simulated grinding surface according to an embodiment of the present invention is shown.

[0075] First, generate a random array.

[0076] Then, the Gaussian to non-Gaussian transformation is achieved through Johnson transformation.

[0077] Afterwards, a two-dimensional linear filtering technique is used to transform it so that it has a corresponding length as the grinding wheel surface.

[0078] Subsequently, the kinematic equations of the grinding wheel and workpiece are established to simulate the grinding process.

[0079] Finally, the grinding surface (such as Figure 7 shown).

[0080] Among them, since the actual grinding wheel surface contains a specific autocorrelation function, it is necessary to transform the non-Gaussian surface using two-dimensional linear filtering technology so that it has the corresponding autocorrelation length. The transformation system is expressed as follows:

[0081]

[0082] In the formula, i = 0, 1, 2 ... M-1; j = 0, 1, 2 ... N-1; z(i, j) represents a grinding surface with a specific autocorrelation length; η(i, j) represents an input non-Gaussian surface; h(i, j) represents a two-dimensional linear filter. Through this process, a two-dimensional linear filter can be solved.

[0083] In this example, according to the kinematic theory of grinding process, the kinematic equation of abrasive particles is established, including: calculating the motion trajectory z of each point according to the interaction between the abrasive particles and the workpiece surface mn , and calculate the motion trajectory of the effective abrasive particles actually involved in the grinding process, so that the mathematical model of the grinding surface can be obtained:

[0084] gmnmin(zmn).

[0085] After the simulated grinding surface is obtained, a simulation model of the grinding object surface roughness measurement system 200 is constructed.

[0086] Simulation model such as Figure 8 As shown, the circular laser light source and the center of the beam splitter are on the same horizontal axis; the CCD camera, the center of the beam splitter and the grinding surface are on the same vertical axis. The beam splitter in the beam splitter is at a 45° angle to the horizontal plane. After the light passes through the beam splitter, a part of the light is vertically reflected to the grinding surface, and then reflected by the grinding surface to the CCD camera to obtain an image.

[0087] The simulation parameters are shown in Table 1. 14 simulated grinding surfaces were selected, with a roughness range of 0.1 μm to 1.4 μm and an interval of 0.1 μm. During the measurement process, an image was acquired at an interval of 30° in the texture direction of the sample, and a total of 98 images were acquired.

[0088] Table 1

[0089]

[0090]

[0091] Fig. 9 The simulation results of different roughness are shown. It can be seen intuitively from the figure that as the roughness increases, the scattering degree becomes more and more obvious, and the pattern area of ​​the imaging surface becomes larger and larger. As the texture placement angle changes, the image only changes in position, and its area and scattering degree do not change. Fig.10 is the number of pixels (P) of samples with different roughness at different rotation angles (θ) x ) line graph, from which we can see that when the roughness gradually increases, the P of the simulated image x The simulation results obtained after changing the rotation angles have not changed except for the coordinate position. x The simulation results prove that the grinding object surface roughness measurement system 200 of the present application is feasible for measuring roughness and is not affected by the placement angle.

[0092] In order to verify whether the rotated image changes, the application quantitatively characterizes the similarity of the images by calculating the SSIM value of the two images. SSIM is an indicator for comparing the structural similarity between two images, taking into account the differences in brightness, contrast and structure. The value of SSIM is between -1 and 1, and the closer to 1, the more similar the two images are. Generally, when the SSIM value is greater than 0.9, the two images can be considered to be almost the same. Because rotation can cause the rearrangement of pixels in the image, even if the image content remains completely unchanged, the change in pixel position will affect the SSIM value. Therefore, even the SSIM value between the images obtained after simulation does not reach 1.

[0093] The image at 0 angle is used as the reference image, and the other six angles are used as distorted images to calculate the SSIM value. The results are shown in Table 2. The SSIM values ​​are all greater than 0.9, which proves that the rotated image is almost the same as the unrotated image, and can overcome the influence of the texture placement direction on the visual roughness measurement results, thereby improving the measurement accuracy.

[0094] Table 2

[0095]

[0096]

[0097] In another specific example, the grinding object surface roughness measuring system 100 of the present application is used to conduct experiments, and the experimental results are compared with the simulation data in the above example to further verify the accuracy of the grinding object surface roughness measuring system 100 of this embodiment.

[0098] On the one hand, 30 grinding objects with 30 mm × 30 mm × 5 mm grinding surfaces of different roughness levels were obtained by changing the grinding wheel grit, cutting depth and cutting speed on the AB51-4 grinding machine. Subsequently, these grinding samples were calibrated using the SSR300 stylus measuring instrument.

[0099] In this embodiment, Ra is selected to characterize the roughness of the sample block. In order to reduce the system error, when measuring each grinding surface, 6 different positions are selected for measurement and then the average value is taken. One piece of the roughness sample block of each level is selected as the calibration sample block of the prediction model, and 9 samples of different levels are selected. The measurement results are shown in Table 3.

[0100] Table 3

[0101]

[0102]

[0103] The surface roughness measurement system 100 for grinding objects was built. A 60mm cage system was used on the basic framework, and a clamping device that can adjust the position of the light source and industrial camera was equipped to ensure the coaxiality and stability of the system. The main components selected include a BASLER acA2500-14gc industrial camera, a 40R / 60T spectroscope with a diameter of 50mm, a KYX635N5-GS1240 circular light source, and an RS60-L rotating platform.

[0104] During the construction process, first connect the industrial camera to the computer (image processor) and make sure that the power of the industrial camera and light source is turned on. Secondly, place the grinding object and adjust the position of the light source and camera so that the image obtained in the industrial camera presents a complete and clear form. Then, use the light source controller to adjust the brightness of the light source to ensure that the circular pattern in the industrial camera is not overexposed, which will affect the accuracy of the measurement. Finally, make fine adjustments to obtain the most complete and clear circular pattern and fix the position of all parts.

[0105] After adjusting the parameters of the above components, the rotation displacement component 110 is started, and an image is collected every 30° rotation, and 7 images are collected for each sample block. Then, the above experiment is repeated by replacing samples with different roughness, and a total of 210 images are collected. During the experiment, the parameters and positions of the laser, spectroscope and camera remain fixed.

[0106] Finally, the results are analyzed. Fig.11 The following is a data analysis flow chart. First, the image captured by the camera is cropped to a uniform size and then grayed to obtain the corresponding image. Finally, the Px value is calculated for data analysis. Fig.12 The result of the image processing process.

[0107] Fig.13 The Ra and Px fitting curves are calculated based on the 9 calibration samples under the 0° texture orientation, so the roughness calculation formula can be obtained as follows:

[0108]

[0109] This application uses a variety of function fitting comparisons, such as polynomial, Fourier function, and exponential function. The exponential function has the best fitting effect in the range of 0.460-1.444μm. Finally, the exponential function was selected, and the R-square of the fitting curve reached 0.998 and the RMSE was 0.021.

[0110] like Fig.14 and 15 As shown in Figure 2, as the roughness increases, the P of the laser point captured by the camera x The value is increasing, and the P of the laser point at different rotation angles x The value is basically unchanged. The experimental results are basically consistent with the simulation, which demonstrates the feasibility of the grinding object surface roughness measurement system 100 proposed in this embodiment for roughness measurement, and in principle can overcome the influence of texture placement direction on visual roughness measurement results. Due to the small influence of the external environment in the actual experiment, the data after different rotation angles have slight fluctuations.

[0111] The 0° image is used as the reference image, and the other six angles are used as comparison images to calculate the SSIM values. As shown in Table 4, the SSIM values ​​obtained at different angles after rotation in the actual experiment are all greater than 0.9, and are generally higher than the values ​​in the simulation process. This is because the lines of the simulated image are too obvious. x The value changes in a wide range. The data in Table 4 proves that the image after rotation is basically consistent with the image before rotation in the actual experiment. It proves that the grinding object surface roughness measurement system 100 provided in this embodiment can overcome the interference caused by the texture placement direction.

[0112] Table 4

[0113]

[0114] The remaining 21 samples were used for experimental verification, and the roughness values ​​of the remaining samples were calculated by the prediction model in the above example. Table 5 shows the prediction values. The maximum prediction value error of the remaining 21 samples is 0.049 μm, the minimum is 0.007 μm, and the average error is 0.22 μm. This proves that the grinding object surface roughness measurement system 100 provided in this embodiment can effectively measure roughness samples of different levels. It also proves that the grinding object surface roughness measurement system 100 provided in this embodiment can effectively eliminate the influence of texture direction on measurement.

[0115] According to the grinding object surface roughness measurement system 100 of the present invention, the vertical light source incident mode can be used to avoid the shadow effect caused by the light source irradiating the grinding surface. At the same time, the non-negligible influence of the slight change in the texture direction of the grinding surface on the scattered light field and the image generated by it can be reduced.

[0116] According to 100 of the present invention, a circular structure laser with uniform energy distribution in the circumferential direction is used to avoid the problem that a certain texture exists on the non-Gaussian surface formed on the grinding surface, and the incident light field causes the scattered light field to change under the influence of the texture placement direction, thereby affecting the final image quality.

[0117] Fig.16 A schematic flow chart of a roughness measurement method 200 according to an embodiment of the present invention is shown. The method 200 is implemented by the roughness measurement system 100 described above.

[0118] The method 200 starts at step 202, wherein the positions of the rotational displacement component 110, the light source transmitter 120, the beam splitter 130, and the image collector 140 are fixed respectively, wherein the beam splitter 130 is arranged at a first position along the direction of the laser optical axis emitted by the light source transmitter 120, and the rotational displacement component 110 and the image collector 140 are fixed at a second position and a third position on both sides of the first position respectively, the first position, the second position, and the third position are coaxially arranged, and the line connecting the first position, the second position, and the third position is perpendicular to the optical axis of the laser.

[0119] Step 204 , placing the object to be measured on the rotation displacement assembly 110 , wherein the surface to be measured of the object to be measured faces the image collector 140 .

[0120] Step 206 , starting the light source emitter 120 and the image collector 140 .

[0121] Step 208 : sending the image data acquired by the image acquirer 140 to the image processor 150 .

[0122] Step 210: extracting the associated features related to the roughness from the image data using the image processor 150, thereby calculating the roughness value of the surface to be measured.

[0123] It should be noted that the working principle and process of the method 200 provided in this embodiment are similar to those of the above-mentioned system 100. For relevant details, reference may be made to the description of the above-mentioned system 100, which will not be repeated here.

[0124] B11. The method as described in B9, wherein the image processor is used to extract the correlation features related to the roughness from the image data, thereby calculating the roughness value of the surface to be measured, including: cropping and graying the image data, and extracting the pixel values ​​of each detection point of the surface to be measured in the image from the processed image as the correlation features; and calculating the roughness value of the surface to be measured based on the pixel values. B12. The method as described in B10, wherein the roughness value of the surface to be measured is calculated based on the following formula: The P x is the pixel value of the corresponding pixel point in the image at each detection point on the surface to be tested, and the R a is the roughness value of each test point on the surface to be tested.

[0125] Although the present invention has been described in terms of a limited number of embodiments, it will be apparent to those skilled in the art, having benefit of the above description, that other embodiments are contemplated within the scope of the invention thus described. Furthermore, it should be noted that the language used in this specification is selected primarily for readability and didactic purposes, rather than for the purpose of explaining or defining the subject matter of the present invention. Therefore, many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the appended claims.

Claims

1. A roughness measurement system, comprising: Rotational displacement assembly, light source emitter, beam splitter, image collector and image processor; The beam splitter is arranged at a first position along the direction of the laser optical axis emitted by the light source emitter; The rotation displacement assembly and the image collector are respectively fixed at a second position and a third position on both sides of the first position, the first position, the second position and the third position are coaxially arranged, and a line connecting the first position, the second position and the third position is perpendicular to the optical axis of the laser; The object to be measured is accommodated on the rotation displacement assembly, and the surface to be measured of the object to be measured faces the image collector; The beam splitter can vertically reflect the laser to the surface to be measured, and transmit the reflected light reflected from the surface to be measured to the image collector; The image processor is connected to the image collector, and is suitable for receiving image data collected by the image collector, and extracting associated features related to roughness from the image data, so as to calculate the roughness value of the surface to be measured.

2. The system of claim 1, wherein: The light source transmitter comprises a light source and a light source controller, and the light source controller can control the light source to emit circular structure laser with uniform energy distribution in the circumferential direction.

3. The system of claim 1, wherein: The image processor includes a processor and a calculator; The processor is adapted to perform cropping and grayscale processing on the image data, and extract pixel values ​​of each detection point on the surface to be measured in the image from the processed image as the associated features; The calculator is adapted to calculate the roughness value of the surface to be measured based on the pixel value.

4. The system of claim 3, wherein: The calculator calculates the surface roughness value to be measured based on the following formula: The P x is the pixel value of the corresponding pixel point in the image at each detection point on the surface to be tested, and the R a is the roughness value of each test point on the surface to be tested.

5. The system of claim 1, wherein: Also includes: A fixer, comprising a first fixer and a second fixer that intersect perpendicularly; The beam splitter is arranged at the intersection of the first fixture and the second fixture; The light source emitter is arranged at one end of the first fixture, and the image collector is arranged at one end of the second fixture.

6. The system of claim 5, wherein: Also includes: The light shielding plate is arranged at an end of the first fixture away from the light source emitter.

7. The system of claim 5, wherein: The diameter of the beam splitter is 50 mm, and the model is 40R / 60T.

8. The system according to any one of claims 1 to 7, wherein: The image collector is a BASLER acA2500-14gc industrial camera, and the light source emitter is a KYX635N5-GS1240 circular light source.

9. The system according to any one of claims 1 to 8, wherein: The object to be measured is a grinding object, and the surface to be measured is a grinding surface.

10. A method for measuring surface roughness, suitable for being implemented by the system according to any one of claims 1 to 8, the method comprising: The positions of the rotation displacement component, the light source transmitter, the beam splitter, and the image collector are fixed respectively, wherein the beam splitter is arranged at a first position along the optical axis direction of the laser emitted by the light source transmitter, and the rotation displacement component and the image collector are fixed at a second position and a third position on both sides of the first position respectively, the first position, the second position, and the third position are coaxially arranged, and the connecting line of the first position, the second position, and the third position is perpendicular to the optical axis of the laser; Placing the object to be measured on the rotation displacement assembly, wherein the surface to be measured of the object to be measured faces the image collector; Starting the light source emitter and the image collector; Sending the image data collected by the image collector to an image processor; An image processor is used to extract correlation features related to roughness from the image data, thereby calculating the roughness value of the surface to be measured.

Images