JP2001099632A - Normal reflection type surface shape measuring method and device with ccd camera - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a method and device of measuring surface shape capable of measuring surface shape of coarse surface object mainly causing normal reflection more in detail direction of surface roughness, surface reflectance, color tone unevenness, flaw, etc., in addition to the conventional roughness parameter Ra. non-touch, quantitatively, accurately and easily. SOLUTION: By illuminating a reference pattern 2 with a light source 3, projecting the reference pattern to the surface of a coarse object 1, photographing the virtual image 4 due to normal reflection with a CCD camera 5, and image-processing the light intensity (image signal 6) received by an image element forming the reflection image 4 with a computer 8, data is converted to brightness distribution showing the fluctuation of the reflection image 4. This statistical quantity of the distribution is captured as the amplitude of the brightness value, and the standard deviation as the fluctuation is calculated. The surface coarseness Ra of the coarse surface object 1 measured in advance in plotted on the horizontal axis and the standard deviation is plotted on the vertical axis to get strong relation map. From this correlation line map, various information of the surface state such as surface roughness and the direction of the coarseness can be obtained.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0101]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method and an apparatus for measuring the surface properties of a rough object having a surface that causes specular reflection, and more particularly, to quantitatively and functionally determine the functional surface properties of a stainless steel plate finished surface. The present invention relates to a technology for easily measuring.

[0092]

2. Description of the Related Art Stainless steel sheets have excellent surface decoration, corrosion resistance, workability, etc., and are widely used in building interior and exterior materials, food / chemical / chemical manufacturing plants, kitchen equipment, western dishes, food equipment, etc. Used, but its functional surface properties,
That is, a method of quantitatively measuring and evaluating the fine shape of the unevenness that exerts a function has not been established yet. In particular, as an inspection / evaluation method in the commercial market for steel sheets, for example, a test piece is visually inspected under a reference piece and a fluorescent lamp, etc. to determine the degree of reflection image (degree of fluctuation / blur), color tone, luminance, scratches, etc. A so-called visual appearance inspection method, such as comparing and judging, is used. For this reason, troubles due to the ambiguity of visual inspection (qualitative evaluation), which is a criterion depending on human sensuality, occur frequently, and there is a strong demand in the trade industry for the development of a quantifiable measurement / evaluation device. Similarly, in the steel plate manufacturing line and the steel plate finishing industry, the surface properties of these steel plates are automatically, quantitatively, and accurately determined in order to automate inspection, increase efficiency, and save labor in the manufacturing or processing process. There is a need for a method and apparatus for measuring.

[0003] Conventionally, as a method for directly measuring the surface properties of a rough object, that is, the geometrical shape of the surface, a stylus type in which the surface is traced (scanning) with a stylus having a sharp tip to measure the roughness (scanning). Surface roughness measurements are most commonly used. This stylus type is most suitable not only for quick and accurate determination of the cross-sectional curve, but also recently, most of the roughness measuring instruments have a built-in signal processing unit in the roughness meter. Is occupied by this type of stylus. A stylus having a tip curvature radius of about 1 to 10 μm is used.

As a non-contact type surface roughness measuring method using light, light interference in the optical path of light reflected from a standard reflecting mirror surface and a sample surface, specified in JIS B 0652-1973, is used. `` Light wave interference type surface roughness measurement method ''
And is generally used as a desk inspection method.
The light wave interference method covers cases where the stylus method is inappropriate, such as a mirror surface or a soft object, and is indispensable as a roughness measurement method together with the stylus method.

[0005] In addition, a total reflection critical method for optically measuring displacement from a reference focal point position, and an electron microscopic three-dimensional photographing method for precisely measuring surface irregularities by the principle of triangulation are known.

On the other hand, an ARS method (Angle-Resolv) obtained from the angular distribution of scattered light is used as a light scattering method for statistically analyzing the reflected scattered light pattern of light to determine the surface roughness.
edScattering) or TIS method (Total
(Integrated Scattering) is used. FIG. 15 shows the measurement principle of the ARS method. FIG. 2A shows that the surface of a rough object 1 having a relatively smooth surface is irradiated with a laser beam 3a to obtain a Gaussian-type angular distribution of the scattered light intensity I (θ), and then the standard angular distribution is obtained. The root mean square roughness Rrms (<h ² ) in the Z (longitudinal) direction of the surface from the scattered light intensity near the average value θ = 0 of the angle θ corresponding to the deviation.
> ^1/2 ) to R′r in the Y (lateral) direction (not shown).
ms is obtained from the variance SN = 4 / (KR′rms) ^{2 of} the scattered light intensity I (θ) derived from the scalar theory.
FIG. 1B shows a Gaussian angular distribution obtained from a relatively rough surface of a rough object.
s (vertical direction) and dispersed light SN = 8 / (Rrms / R′r
ms) R′rms can be determined from ² . In the field, the angular distribution of these scattered lights can be measured by electrically measuring the surface of the object to be measured with a linear image sensor, or by using a light receiving element (Si photodetector) having a small opening around the object to be rotated. The axis is obtained by scanning and measuring the surface area.

FIG. 16 shows a measurement principle diagram of the TIS method. According to this principle, the specular reflection light component and the scattered light component of the illumination laser light are optically separated, and only the scattered light is detected to determine the surface roughness. This measuring device comprises a laser light source 3a, a rotating mirror M, an integrating sphere S for collecting all scattered light from the surface of the object to be measured, and two detectors D1 and D2. The detector D1 measures the total scattered light intensity _RD from the surface of the object to be measured, and the detector D2 measures the light source intensity _RD = _RS + _RD . From now on Rs
Since / _RD is required, Rrms of the unevenness on the sample surface can be obtained. This method has the advantage that an amount directly proportional to Rrms is obtained. The measurement range is Rr
This is effective for measuring a very smooth surface with ms <0.01 μm.

[0008] In addition, there are a speckle contrast method for measuring a change in speckle contrast, a moment method for measuring a change in speckle size, and a speckle correlation method for measuring an intensity correlation of speckle by two-beam illumination. These methods can measure with high accuracy if there is similarity in the fine shape of the surface.

[0009] On the other hand, the surface texture can be identified by human sensation.
The visual inspection method for determining pass / fail is used in principle for the appearance inspection of a steel material such as a stainless steel plate. As this visual inspection method, in a commercial market or a site of surface polishing, for example, a method of judging pass / fail by comparing and observing a steel plate test piece and a reference piece under sunlight, a fluorescent lamp, or the like is often used. In the production line, a method such as a pass / fail selection is visually observed by an inspector.

[0010]

However, in the stylus type surface roughness measuring method, fine scratches are formed on the surface of the object to be measured, and the roughness pitch (wavelength) component smaller than the radius of curvature of the tip of the stylus is cut. And the measurement time is long, and only one-dimensional measurement can be performed.

In addition, the light interference type surface roughness measuring method based on JIS B 0652-1973 is limited in the size of the field of view because a microscope is used, and the maximum measurable roughness is limited to within several μmRy. In addition, when a light source having a relatively wide spectrum width is used, there is a drawback that adjustment is very difficult until interference fringes are generated.

[0012] In addition, the total reflection critical method, the electron microscopic three-dimensional photographing method, and the like require that careful attention must be paid to the measurement, precise adjustment and maintenance of a reliable measurement environment are required in order to exhibit their performance. Has disadvantages such as that it is a large-sized device made of precision optical parts, and that it takes a lot of time for measurement.

The light scattering method such as the ARS method or the TIS method obtains surface roughness, mainly root mean square roughness Rrms, by statistical analysis of light scattered from the object surface due to light. There is a drawback that the method cannot be applied to a rough object having a surface having a large amount of components, that is, a material having a high specularity such as a stainless steel plate surface.

In the visual inspection method, since the determination is made based on the human sensuality of visual inspection, the criteria for the determination are ambiguous.
There are drawbacks such as that there is variation in judgment due to individual differences among inspectors and that the examiner is physiologically and psychologically susceptible to the influence of the surrounding environment. Also, for simple inspections,
Due to the drawbacks of being unable to withstand continuous conditions and being easily fatigued, realization of automatic visual inspection by a machine is desired.

On the other hand, in view of the diversification of demand in the stainless steel sheet market in recent years, in addition to the stainless steel sheet of the surface treatment specified in JIS G4305, for the purpose of seeking added value as a product, a higher level of luster is required by decorative polishing. 2. Description of the Related Art Steel sheets provided with gloss, texture such as finish and satin finish, decorative polishing finish such as streak pattern, scratch pattern, hairline, and the like have come on the market.

As a method for measuring various surface properties of such a stainless steel sheet, the above-described various measuring methods include:
It is only possible to obtain parameters of surface unevenness information such as Ra, Ry, Rz, and Rrms, and it is impossible to know the diversified functional surface properties of these steel sheets, and the development of more appropriate measuring means is awaited. I have.

On the other hand, from the production point of view, in the production process, the progress of automation in both processing and assembly is remarkable, and there are many cases where the intervention of the visual inspection by humans hinders the flow as a whole. The development of is strongly desired.

SUMMARY OF THE INVENTION The present invention has been made to eliminate the above-mentioned conventional problems, and is intended mainly for a rough surfaced object having a surface which causes specular reflection, particularly for a stainless steel plate in a commercial market and in a production, processing and assembly stage. Various functional surface properties,
More specifically, in addition to the conventional parameters of surface irregularities, the surface, which can accurately, quantitatively, and easily measure the amplitude, directionality, inclination distribution, color tone, unevenness, gloss, scratches, and the like of the surface irregularities. It is an object of the present invention to provide a method and apparatus for measuring properties.

[0019]

Means for Solving the Problems As an improvement of the visual inspection method, the present inventors use a large number of samples having different surface reflectivity, gloss, and surface roughness of a stainless steel plate, and use the surface as a reference. A pattern (bright and dark stripes) was projected, and various studies were conducted on the relationship between the fluctuation of the reflected image and the surface roughness of the sample. As a result, as shown in FIG. 14 (B), the surface is extremely smooth and has a specular reflection (specular reflection).
In a steel sheet with a surface with a large long wavelength component,
The fluctuation state of the reflection image of the reference pattern projected on the surface is extracted as an electric signal, and converted into a light-dark intensity distribution on the vertical axis and a light-dark intensity distribution indicating the position of the virtual image plane on the horizontal axis, and further the light-dark intensity For example, when the amplitude is taken as the statistic and the standard deviation is calculated, it has been found that there is a strong correlation between the standard deviation of the luminance amplitude and the value of the surface roughness Ra.

Further, the present inventors conducted a measurement experiment based on the regular reflection of light by computer simulation and confirmed whether or not a reflection image similar to the experiment could be obtained. A device model consisting of the same rough surface object and pattern as the above experimental device was set, and the surface of the rough surface object was regarded as a set of micro mirrors, and geometrical optics was assumed to have sine waveform irregularities. Is calculated using only
The intensity distribution and the standard deviation of the reflection image (virtual image) were obtained. As a result, as shown in FIG. 13, a phenomenon was observed in which the amplitude of the intensity distribution of the reflected image was attenuated in the same manner as in the experimental result (8a in FIG. 8). As described above, the relationship between the reflection image of the surface irregularities of the stainless steel plate and its fluctuation was theoretically analyzed by simulation, and the validity of the measurement method of the present invention was confirmed.

That is, the method of the present invention is a method for measuring the surface properties of a rough object, which comprises projecting a reference pattern onto the surface of a rough object having a surface that causes regular reflection to form fluctuations in the reflected image. And the fluctuation of the reflected image is detected by a CCD.
Calculating the luminance distribution of the fluctuation of the reflected image and the magnitude of the fluctuation of the reflected image by performing image processing on a video signal of the CCD camera, and obtaining the surface properties of the rough object from the values. It is characterized by.

An apparatus for practicing the present invention captures a reference pattern provided at an angle θ on the surface of a rough object, a light source for illuminating the reference pattern, and a fluctuation of the reflected image. And a computer for performing image processing on a video signal of the CCD camera.

[0023]

According to the measuring method based on the regular reflection of light of the present invention, the surface property of a rough object on which a reflection image of a reference pattern (graphic) is projected is first captured by an image pickup device, thereby obtaining the same as visual observation. It is possible to obtain the magnitude of the fluctuation of the reflected image (in this embodiment, the standard deviation of the luminance distribution of the reflected image) by performing image processing on the statistics of the luminance distribution from these image sensors. From this value, not only the functional surface properties of the above-mentioned rough object surface, that is, not only the roughness of the surface unevenness, but also the directionality of the surface unevenness, the surface reflectivity, etc. can be measured in a non-contact manner, quantitatively, with high accuracy and easily. Can be measured.

Further, according to the apparatus of the present invention, a small volume and portable apparatus can be obtained by comprising a reference pattern, a light source, a CCD camera, a computer and the like.

[0025]

DESCRIPTION OF THE PREFERRED EMBODIMENTS As shown in FIG. 14 (B), a rough surface object 1 to which the present invention can be applied has a long wavelength component 12 of irregularities which are extremely smooth locally and cause specular reflection (specular reflection). Those with a large surface, for example, stainless steel plate,
Suitable are various metal plates, plastic molded products, ceramic products (such as tiles), glass products, painted products, plated products, and the like. In addition, an object having a surface that mainly causes regular reflection, for example, a plate, a cylinder, a sphere, or the like having a flat surface, a curved surface, a spherical surface, or the like can be given. Further, the present invention can be applied to a fluctuation phenomenon of a liquid surface.

The reference pattern 2 used in the present invention may be any pattern in which the fluctuation of the reflected image 4 can be confirmed. For example, a straight line, a curve, a circle, an ellipse, a triangle, a trefoil, a quadrangle, a rhombus, a hexagon, a star Arbitrary figures and shapes obtained from shapes, irregularities, combinations thereof, and the like can be used. The reference pattern 2 is shown in FIG.
As shown in (1), the surface of the rough object 1 is set at an angle θ with the surface so that the fluctuation of the reflection image 4 is reflected on the surface.
The angle θ can be set in a wider range depending on the shooting direction of the CCD camera 5. The reference pattern 2 is shown in FIG.
As shown in the figure, when there is a linear streak 11 on the surface of the rough object 1 such as, for example, a stainless steel hairline finished surface, the streak 11 and the graphic of the reference pattern 2 are orthogonal or parallel. (FIG. 4). These reference patterns 2 can be manufactured by processing or printing on the surface of a rigid plate material having a smooth outer surface without distortion.

The light source 3 used in the present invention may be any illuminator that indirectly provides appropriate illumination to the fluctuation of the reflected image 4 of the reference pattern 2, and may be a general incandescent bulb such as a tungsten bulb or a halogen bulb. , Fluorescent lamps such as white fluorescent lamps, color rendering improved type (white) and three-wavelength emission type (neutral white), and large discharge lamps such as fluorescent mercury lamps, high-pressure mercury lamps, metal hydride lamps, and high-pressure sodium lamps. . The light source 3 illuminates the reference pattern 2 from the horizontal direction as shown in FIG. 1 and plays a role of giving sufficient brightness to the fluctuation of the reflected image 4 reflected on the surface of the rough object 1.

As the CCD camera 5 used in the present invention, the fluctuations of the reflected image 4 of the reference pattern 2 given the appropriate illumination conditions are condensed on the image pickup device surface by a lens system, and this is photoelectrically converted to an electric signal. Any signal can be extracted as a signal (video signal 6), and a pixel having a high number of pixels is preferable from the viewpoint of resolution for clearly capturing the fluctuation of the reflected image. For example, a commercially available CCD camera having a large number of pixels such as 1.3 million pixels or 2 million pixels can be used as appropriate. Further, a liquid crystal display can be used instead of the reference image pattern 2. However, in this case, the light source 3 becomes unnecessary. The CCD camera 5 is adjusted to a position where the rough object 1 enters the field of view so that the virtual image 4 of the reference pattern 2 formed at the target position behind the surface of the rough object 1 can be focused and photographed. Is done. Optical information from the virtual image of the rough object 1 is formed on the image pickup device by the lens of the CCD camera 5, and a video signal 6 of a level corresponding to the brightness (brightness) of the location is provided for each pixel by the computer 8. It is taken in.

The computer 8 used in the present invention can output a target image pattern and a quantitative amount derived from the image pattern by subjecting the video signal from the CCD camera to specific image processing and arithmetic processing. Any commercially available computer or microcomputer can be used as appropriate. A video signal 6 which is a light / dark analog signal from a CCD camera is A / D converted by an interface and converted into a digital signal by a computer 8.
Sent to. The computer 8 converts the intensity of light and dark, that is, the magnitude of the luminance on the vertical axis, into a luminance distribution 8a (FIGS. 1 and 8) indicating the coordinates of the virtual image plane on the horizontal axis. Further, an amplitude of the luminance value is taken as a statistic of the luminance distribution 8a, and a standard deviation of the amplitude amount is calculated. The standard deviation is plotted on the vertical axis, and the rough surface object 1 of the same type measured in advance, for example,
The value of the surface roughness Ra of the stainless steel sheet is plotted on the horizontal axis, and a correlation diagram between the two is drawn.

[0030]

An embodiment of the present invention will be described below in detail with reference to the drawings. FIG. 1 is a diagram showing the measurement principle of the method for measuring the surface texture of a rough object according to the present invention and the configuration of an apparatus for carrying out the method. That is, this measuring device is composed of a reference pattern 2, a light source 3, a CCD camera 5 and a computer 8, and a measuring method using the same is based on a method in which a reference pattern is mainly applied to the surface of a rough object 1 having a surface that causes regular reflection. 2
Is reflected, and the fluctuation of the reflection angle due to the unevenness of the reflecting surface is converted into the fluctuation of the virtual image pattern on the surface of the virtual image 4. This virtual image pattern is photographed by the CCD camera 5, and the video signal 6 is image-processed by the computer 8. First, a luminance distribution 8a of the virtual image pattern 4 is obtained, then a standard deviation of the luminance distribution 8a is obtained, and a strong correlation diagram 8b is obtained from the standard deviation and the surface roughness Ra of the rough object. Therefore, if the standard deviation of the luminance distribution 8a of another rough surface object 1 of the same kind is measured by the method of the present invention, the surface roughness Ra can be directly read from the diagram 8b.

The measuring method of the present invention, as shown in FIG.
First, the reference pattern 2 is irradiated by the light source 3 to indirectly illuminate the reflection image 4 (virtual image) of the reference pattern 2 reflected on the surface of the rough object 1. Then, the reflected image 4 is photographed by focusing on the virtual image 4 using the CCD camera 5.

Next, a reference pattern 2 provided at an angle θ to the object is projected onto the surface of a rough object 1 having a surface which mainly causes regular reflection, which is a measurement object, and the reference pattern 2 is projected at a symmetrical position behind the reference pattern 2. A virtual image 4 due to reflection is formed. The virtual image 4 of the reference pattern 2 is closely related to the surface fine property unique to the rough surface object 1, and if the surface is smooth, the reference pattern 2
As the surface becomes rougher, that is, as the roughness becomes rougher, blurring of the reference pattern 2 progresses due to variations in the reflection angle, and an image with an unclear outline, that is, fluctuation of the virtual image 4 (FIG. 5) is obtained. .

Subsequently, the video signal 6 from the CCD camera 5
The (video signal) is taken into the computer 8 via the interface 7. As shown in FIGS. 1 and 8A and FIG. 8, the fluctuation of the reflected image 4 is reduced by performing image processing on the intensity of the light (video signal 6) received by the image sensor that forms the fluctuation of the reflected image 4 by the computer 8. The calculated luminance distribution 8a is calculated and drawn.

Further, as a statistic of the luminance distribution 8a obtained by the image processing, the difference between the maximum value and the minimum value of the amplitude value of the luminance value shown in FIG. 8 is obtained, and the standard deviation is calculated from them. In this case, the standard deviation is obtained by inputting and calculating each luminance value in the X-axis direction.

When the standard deviation obtained in this manner is plotted on the vertical axis, and the value of the surface roughness Ra (center line average roughness) of the rough object 1 of the same kind measured in advance is plotted on the horizontal axis, image processing is performed. As shown in FIG. 9 and FIG. 9, a diagram 8b showing a strong correlation between the two is obtained. The approximate straight line in this case is
It is easily obtained by regression analysis.

In the above case, the standard deviation of the amplitude of the luminance value is used as the fluctuation of the reflection image 4, that is, the statistical value of the luminance distribution, but the standard method for quantifying the magnitude of this fluctuation is the standard. Various evaluation functions other than the deviation are considered,
You can use this.

EXAMPLE 1 A roughened object mainly having a surface that causes regular reflection is made of a surface-finished stainless steel plate (Nisshin Steel Products, trade name: Moon Star Stainless Steel, AISI No. SUS304 / SUS43).
0, sample size 80 × 50 × 0.49 mm). 8 Finish / BA Finish (S
US430) ・ No2B finish (SUS430) ・ N
o. No. 7 finish, BA finish, HL (hairline) finish, fine color finish, No. 4 finish with straight (polished) streaks and strong directivity; Ten kinds of 2DR-2 finish and starlight emboss were used. First, the surface roughness Ra (center line average roughness) of each of the above stainless steel plates was measured using a stylus type roughness meter (SURFCOM570A, manufactured by Tokyo Seimitsu). For a steel plate having linear streaks, the surface roughness Ra is determined in a direction perpendicular to the straight line, and a cross-sectional shape (enlarged view) having a locally smooth surface as shown in FIG. Was done. Next, the stainless steel plate was placed on a horizontal base (not shown), and a line pattern (size 80 × 60 × 3 mm) shown in FIG.
It was installed in. Then, the line pattern was made to appear orthogonal or parallel to the linear streaks of the steel sheet. This line pattern has a line width of 0.35, 0.70, 1.05, 1.40,
1.75 and 2.10 mm (0.35 mm increments) 6
The line spacing was twice the line width. This line pattern was produced by pasting paper on which the pattern of FIG. 2 was printed on the surface of an acrylic plate (thickness: 3 mm). Subsequently, three krypton lamps (5.2 V × 0.3 A) are illuminated to the line pattern from the horizontal direction to make the fluctuation of the reflection image of the line pattern reflected on the steel plate surface sufficiently bright, and then the CCD
Images were taken with a camera (KCC-310ND manufactured by KOCOM), and the reflected image fluctuated (clearness of the image or blurred image) depending on the difference in surface roughness (Ra value) (FIG. 5) and the direction of the streaks (FIG. 7). (Unclearness caused by the above) were obtained. Further, the video signal was taken into a computer, and the luminance intensity was plotted on the vertical axis and the position on the image plane was plotted on the horizontal axis as image processing to obtain a luminance distribution (FIG. 8). In addition, the amplitude of the luminance value of this luminance distribution was taken and its standard deviation was calculated. The standard deviation is normalized by dividing the standard deviation by the average of the luminance values with the value of the surface roughness Ra of the steel sheet measured in advance on the horizontal axis, and the surface roughness Ra value is expressed in logarithm and drawn. A logarithmic regression line was obtained by regression analysis of the correlation diagram (dotted line).

FIG. 5 is a photograph showing a fluctuation state of a line pattern reflection image projected on two types of stainless steel plates having different surface roughnesses Ra. FIG. 6 is an enlarged view of the measured surface irregularities and minute portions of the steel plates. From FIG. 5, a steel plate having a large surface roughness (Ra = 0.233 μm (HL finish)) is small [Ra = 0.113 μm (No.
8 finish)], the image is blurred and unclear due to scattering, diffraction, interference, and the like of the reflected light shown in FIG. 14A, that is, the reflected image has optical fluctuations 4a. It is observed that In particular, as shown in FIG. 7, in the case of a steel plate having linear streaks, if a line pattern is arranged so as to be parallel to the direction in which the linear streaks are present [FIG. It is too large and becomes completely unclear (FIG. 5D). In this way, various characteristics such as the shape, arrangement, and arrangement of fine irregularities on the surface of a rough object are regarded as fluctuations of a specular reflection image (virtual image). To
This is a basic requirement of the present invention to be extracted in more detail and specifically.

FIG. 8 shows the luminance distribution of the fluctuation of the reflection image of the line pattern projected on the surfaces of the two stainless steel plates having different surface roughnesses shown in FIG. That is, the reflected image fluctuation 4a
The intensity of the reflected light corresponding to the brightness coming from each position of the line (dark stripes) and the white background (bright stripes) that composes is captured by a CCD camera, which is evaluated and converted into a luminance value, and the luminance is calculated. This is represented by a distribution graph. Referring to the clear cases [(a) and (b)] of the reflection image in FIG. 5 and the unclear and streak cases [(c) and (d)], FIG. 8 shows (1).
As shown in [(a) and (b)], the luminance distribution on the surface where the reflected image is clear has a remarkable gradient from a high luminance value to a low luminance value [FIG. 8 (a)]. When the difference in luminance from the stripe is large, the glossiness is strong, and conversely, [(c),
(D)], when the reflected image is unclear, the gradient is gentle [FIG. 8 (b)], and when the difference in luminance is small, the glossiness is weakly observed. A small steel plate has a large amplitude of the luminance value (FIG. 8A), and a steel plate with a large Ra value has a small amplitude of the luminance value (FIG. 8B).
(3) The brightness distribution of a steel sheet having a streak direction on the steel sheet surface differs depending on the direction in which the line pattern is projected. The amplitude of the brightness value is large when the steel sheet is orthogonal, but significantly small when the steel sheet is parallel. Is observed, and the directionality with the roughness can be detected. FIG. 9 shows that there is a strong correlation between the Ra value with various steel plates and the standard deviation of the luminance amplitude width. That is, it indicates that it is possible to manufacture a direct-reading surface roughness measuring device having a Ra value of about 0.01 to 5 μm by measuring the surface texture based on the regular reflection information of the present invention. . As described above, the luminance distribution is obtained by converting the qualitative information of the fluctuation of the reflected image that can be sensed by the naked eye to the quantitative information of the luminance, which is a reference of the brightness. In other words, this luminance distribution does not explicitly indicate the specific surface microscopic properties, but numerically (quantitatively) represents a large amount of reflected light information governed by the surface properties.
It provides an important clue to know the specific surface properties. While the conventional method has focused on grasping the geometric properties of the surface with high accuracy, the industry has two-dimensional (plane) unevenness (heterogeneity) in addition to this geometric property. And functional surface properties, i.e., color, orientation, gloss,
It is required to comprehensively determine characteristics such as luminance. The CCD camera essentially has the function of measuring and evaluating the functional properties such as color tone, gloss and brightness, and the only solution is the geometric property evaluation related to surface roughness. Was the problem. The present invention solves this problem and suggests the possibility of comprehensive judgment of the surface properties desired by the industry.

Reference Example Hereinafter, an experiment by simulation of the method of the present invention will be described in detail with reference to the drawings.
FIG. 10 to FIG. 12 are diagrams showing analysis models of the simulation of the method of the present invention. In the same figure, the device model was provided with a reference pattern provided at an angle of 45 ° with respect to the surface of the stainless steel plate, as in the example, and configured with a light source (not shown) and a CCD camera. The stainless steel surface was assumed to be composed of a group of micro mirrors having different inclinations and to have a sinusoidal irregularity. As the reference pattern, first, a point light source was considered as a minute portion on the pattern surface illuminated by the light source, and then a line pattern was adopted. Calculations for coordinates and the like were based on geometry.

First, as shown in FIG. 10, when light from a certain point light source (Px, Py) is projected on the surface of a micro mirror inclined by an angle θ, the light is reflected and the symmetrical position behind the light is reflected. A virtual image is formed on (fx, fy). The coordinates (fx, fy) of the virtual image are expressed by the formula (I) of a straight line on the surface of the micro mirror,
Equation (II) perpendicular to it and their orthogonal midpoint (Z
x, Zy) Is required. Then, as shown in FIG. 11, if the pattern surface is set at an angle of 45 ° with respect to the stainless steel surface and the micro mirror is set on the stainless steel surface at an angle θ, the coordinates of the micro mirror become (Mx, O). , And that of the point light source is [Px, Px (= Py)]. Furthermore, θ
Assuming ≪1, Therefore, the coordinates (fx, fy) of the virtual image are Obtained as

The brightness of the virtual image, that is, the light intensity of the virtual image of the point light source is equal to the intensity of the light reflected by the minute mirror by the point light source, and is equal to the solid length φ formed by the minute length dl and the point light source. Proportional. Let L be the distance from the point light source (Px, Px) to the center (Mx, O) of the micromirror (FIG. 1).
2) Assuming that dl is sufficiently small, φ also becomes sufficiently small, so that the following equation is established. therefore Therefore, the intensity Ip of the light reflected at the minute length dl is Is obtained as However, the light I (light intensity of the virtual image) actually entering the lens of the CCD camera is not only the light intensity Ip for the minute length dl by the point light source, but also the light from the countless point light sources over the entire pattern is stainless steel. It can be considered as an aggregate of entangled light reflected on the surface of the group of micromirrors constituting the surface. That is, the intensity I of the pattern reflection image is obtained as a value obtained by integrating the light intensity Ip of the point light source for the minute length dl with respect to the entire area of the pattern and the entire surface area of stainless steel. Although a detailed calculation procedure is omitted, an example of a result obtained by numerically calculating the above integral is shown in the figure. However, the roughness of the stainless steel surface used was that obtained by approximating the roughness of the material shown in FIG. 8 by a sin curve.

As is clear from FIG. 19 (b), when the stainless steel surface becomes rough such as in HL finishing, the surface is qualitatively regarded as a sine waveform by a micro mirror, but the brightness value amplitude of the reflected image is obtained. The tendency of the decay to decrease as the distance from the pattern surface increases is shown in the experimental results (FIG. 8B).
Is very similar to This proves that the concept of the present invention based on regular reflection of light is basically correct.

[0044]

As described above, according to the present invention, an image (qualitative) obtained by a CCD camera having a surface texture of a surface of a stainless steel plate, such as a stainless steel plate, is mainly used for statistical distribution of luminance. Converting to a quantity (quantitative value) and obtaining not only one of the surface properties called roughness Ra from the statistics, but also obtaining the amplitude and directionality of the unevenness and the unevenness of the roughness on the two-dimensional surface. And suggested the possibility of measurement of color tone, uneven color tone, gloss, brightness, and the like. In addition, the apparatus of the present invention has a reference pattern, a light source, a CCD camera,
Since the portable device is constituted by a microcomputer or the like, various economical, simple, lightweight, and portable effects such as low cost, small volume, and small occupied area can be obtained.

[Brief description of the drawings]

FIG. 1 is a diagram showing the principle of a method for measuring the surface properties of a rough object according to the present invention and the configuration of an apparatus.

FIG. 2 is a plan view showing a line pattern.

FIG. 3 is a line pattern, a stainless steel plate, a virtual image, a reflection image,
It is a partially expanded perspective view which shows the positional relationship of fluctuation.

FIG. 4A is a perspective view showing a state in which linear streaks and a line pattern of a stainless steel plate are arranged orthogonally. (B) A case where a linear streak and a line pattern are arranged in parallel.

FIG. 5 is a photograph of a fluctuation of a reflection image when a surface of a stainless steel plate having two types of rough surface roughness Ra values is orthogonal or parallel.

FIG. 6 (a) No. It is a figure of the surface unevenness of a 8 finish stainless steel plate, and a microscopic part enlarged. (B) It is a figure of the surface unevenness of a HL finish stainless steel sheet, and a minute part expansion.

FIG. 7 is a schematic view of a vertical linear streak and a horizontal cross-sectional shape of a stainless steel plate surface unevenness.

FIG. 8 is a graph in which the fluctuations of the reflection images on the surfaces of two types of stainless steel sheets having different surface roughnesses are converted into luminance distribution and displayed.

FIG. 9 is a logarithmic regression line showing the relationship between the standard deviation of the luminance value and the surface roughness of ten stainless steel sheets obtained by the method of the present invention.

FIG. 10 is a diagram of a simulation analysis model showing a positional relationship between a point light source and a virtual image formed by a micromirror.

FIG. 11 is a diagram of a simulation analysis model showing settings of a pattern surface and a stainless steel surface.

FIG. 12 (a) No. It is a graph of the intensity distribution of the reflection image by simulation of an 8 finish stainless steel plate. (B) It is a graph of intensity distribution by the simulation in case of HL finish stainless steel sheet.

FIG. 13A is a vertical schematic diagram showing a state of scattering by light on a surface having fine irregularities. FIG. 4B is a vertical schematic diagram in the case of regular reflection (mirror reflection) of light on an uneven surface having a locally smooth surface.

FIG. 14 shows a light scattering method (A) for obtaining surface roughness from an angular distribution.
It is a principle diagram of (RS method).

FIG. 15 is a principle diagram of a light scattering method (TIS method) for obtaining a root mean square roughness from total scattered light.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Rough surface object 11 Straight line of stainless steel plate 1s Stainless steel plate 2 Reference pattern 2a Line pattern 3 Light source 3a Laser light 3b Incident light 4 Reflected image (virtual image) 4a Fluctuation 5 CCD camera 5a Lens 6 Video signal 7 Interface 8 Computer 8a Brightness Distribution 8b Correlation diagram 9 Specularly reflected light 10 Scattered light 11 Scattered light pattern 12 Irregular wavelength component 13 Gaussian angle distribution d Interline width d1 Micromirror minute length fx, fy Coordinate of virtual image h From centerline to surface Height w Line width x Coordinates in the vertical direction of the surface z Coordinates in the height direction of the surface A Aperture D1, D2 Detector I (θ) Scattered light intensity I Light intensity Ip Light intensity per minute length L From point light source Distance to minute mirror M Rotating mirror Mx, My Center coordinates of minute mirror Px, Py Coordinates of point light source Ra Core line average roughness Rrms, R'rms Root mean square roughness Ry Maximum height roughness S Integrating sphere α, θ angle φ Solid angle I Micromirror straight line formula II I formula and perpendicular straight formula

[Procedure amendment]

[Submission date] December 24, 1999 (1999.12.
24)

[Procedure amendment 2]

[Document name to be amended] Statement

[Correction target item name] Brief description of drawings

[Correction method] Change

[Correction contents]

[Brief description of the drawings]

FIG. 1 is a diagram showing the principle of a method for measuring the surface properties of a rough object according to the present invention and the configuration of an apparatus.

FIG. 2 is a plan view showing a line pattern.

Fig. 3 Line pattern, stainless steel plate, virtual image (reflection image)
FIG. 3 is a partially enlarged perspective view showing the positional relationship of FIG.

FIG. 4A is a perspective view showing a state in which linear streaks and a line pattern of a stainless steel plate are arranged orthogonally. (B) A case where a linear streak and a line pattern are arranged in parallel.

FIG. 5 is a fluctuation photograph of a reflection image of two types of stainless steel plates having different surface roughnesses and having different Ra values when the surfaces are orthogonal or parallel.

FIG. 6 (a) No. It is a figure of the surface unevenness of a 8 finish stainless steel plate, and a microscopic part enlarged. (B) It is a figure of the surface unevenness of a HL finish stainless steel sheet, and a minute part expansion.

FIG. 7 is a schematic diagram of a linear linear streak and a horizontal undulating shape of a surface unevenness of a stainless steel plate.

FIG. 8 is a graph in which the fluctuations of the reflection images on the surfaces of two types of stainless steel sheets having different surface roughnesses are converted into luminance distribution and displayed.

FIG. 9 is a logarithmic regression line showing the relationship between the standard deviation of luminance values obtained by the method of the present invention and the surface roughness of ten stainless steel sheets.

FIG. 10 is a diagram of a simulation analysis model showing a positional relationship between a point light source and a virtual image formed by a micromirror.

FIG. 11 is a diagram of a simulation analysis model showing settings of a pattern surface and a stainless steel surface.

FIG. 12 is a model diagram of a simulation analysis of the intensity of light impinging on a micromirror from a point light source.

FIG. 13 (a) No. It is a graph of the intensity distribution of the reflection image by simulation of an 8 finish stainless steel plate. (B) It is a graph of intensity distribution by the simulation in case of HL finish stainless steel sheet.

FIG. 14A is a vertical schematic diagram showing a state of scattering by light on a surface having fine irregularities. FIG. 4B is a vertical schematic diagram in the case of regular reflection (mirror reflection) of light on an uneven surface having a locally smooth surface.

FIG. 15A is a vertical schematic diagram illustrating the principle of a light scattering method (ARS method) for obtaining surface roughness from a relatively smooth surface reflection angle distribution. (B) is a vertical schematic diagram showing the principle of the light scattering method in the case of a relatively rough surface.

FIG. 16 is a principle diagram of a light scattering method (TIS method) for obtaining a root mean square roughness from total scattered light.

[Description of Signs] 1 Rough surface object 11 Straight line of stainless steel plate 1s Stainless steel plate 2 Reference pattern 2a Line pattern 3 Light source 3a Laser light 3b Incident light 4 Reflected image (virtual image) 4a Fluctuation 5 CCD camera 5a Lens 6 Video signal 7 Interface 8 Computer 8a Luminance distribution 8b Correlation diagram 9 Specular reflection light 10 Scattered light 11 Scattered light pattern 12 Irregular wavelength component 13 Gaussian angle distribution d Line width dl Length of minute mirror fx, fy Coordinate of virtual image h From center line Height to surface w Line width x Vertical coordinate of surface z Vertical coordinate of surface A Aperture D1, D2 Detector I (θ) Scattered light intensity L Distance from point light source to micromirror M Rotating mirror Mx , My Center coordinates of micro mirror Px, Py Coordinates of point light source Ra Center line average roughness Rrms Square roughness S integrating sphere Zx, Zy formula (I), the intersection coordinates alpha, theta angle φ formula perpendicular straight line of the formula II I of the straight solid angle I micro mirror surface of (II)

Continued on front page F-term (reference) 2F065 AA49 AA50 BB26 CC06 FF42 FF61 FF63 GG03 HH06 HH12 HH17 JJ03 JJ08 JJ26 LL41 QQ03 QQ17 QQ41 QQ42 2G051 AA37 AB07 AB20 BA01 BA20 CA03 CA02 EC02 BA03 EC02 DB09 DC23 DC30 DC33

Claims (5)

[Claims] In a method for measuring the surface properties of a rough object, a reference pattern is projected onto a surface of a rough object having a surface which mainly causes regular reflection, and a fluctuation of a reflection image of the reference pattern is formed. The fluctuation of the reflected image is photographed with a CCD camera, and the image signal of the CCD camera is subjected to image processing to calculate the luminance distribution of the fluctuation of the reflected image and the magnitude of the fluctuation of the reflected image. A method for measuring the surface properties of a rough object, comprising determining the surface properties of the object. 2. The method according to claim 1, wherein the magnitude of the fluctuation of the reflected image is a standard deviation of the amplitude of the luminance value. 3. The rough surface object is a stainless steel plate.
The method for measuring the surface texture of a rough object according to claim 2 or 3. 4. A reference pattern provided at an angle .theta. For reflecting a fluctuation of a reflected image on a surface of a rough object having a surface which mainly causes regular reflection, a light source for illuminating the reference pattern, A surface property of a rough object, comprising: a CCD camera for photographing a fluctuation of a reflection image reflected on the surface of the rough object; and a computer for image processing a video signal from the CCD camera. measuring device. 5. The rough surface object is a stainless steel plate.
The surface texture measuring device for a rough object according to the above.