JPH0224458B2 - - Google Patents

Description

[Detailed description of the invention]

[Industrial Application Field] The present invention relates to a method for determining the glossiness of an object surface,
In particular, a method for determining the glossiness of an object's surface that classifies and grades the glossiness based on the visual sensation based on the light reflection intensity distribution on the object's surface, which is suitable only for measuring and managing the surface quality of steel plates. Regarding the improvement of

[Conventional technology]

As a method for determining the glossiness of an object's surface, various methods using light reflection measurements have been proposed in the past.A typical method is based on specular glossiness, which measures the specular reflection intensity of a white beam projected at a fixed angle. method, a contrast gloss method that uses the ratio of specular reflection intensity and diffuse reflection intensity of white light projected at a certain angle, and a clear gloss method that reflects another object on the surface and observes the blurring of the reflected image with the naked eye. There is.

[Problems to be solved by the invention]

However, the method based on specular gloss,
Although it is widely used industrially, it has the disadvantage that it does not match reality for specular objects with small surface roughness. In addition, the method using the comparative glossiness,
Although it has the characteristic of giving a gloss level close to visual perception even to objects of different colors, it also tends to have low determination accuracy for objects that are close to mirror surfaces.

[Problems to be solved by the invention]

However, the method based on specular gloss,
Although it is widely used industrially, it has the disadvantage that it does not match reality for specular objects with small surface roughness. In addition, the method using the comparative glossiness,
Although it has the characteristic of giving a gloss level close to visual perception even to objects of different colors, the determination accuracy also tends to be low for objects that are close to mirror surfaces. Furthermore, the method using the sharp glossiness has a problem in that a quantitative display cannot be obtained.

[Purpose of the invention]

The present invention was made to solve the above-mentioned conventional problems, and has the same color (brightness may be different).
The purpose of the present invention is to provide a method for determining the glossiness of the surface of an object that closely matches the visual glossiness and that can quantitatively determine the glossiness over a wide roughness range from specular to rough surfaces. shall be.

[Means to solve the problem]

The present invention uses the light reflection intensity distribution on the object surface to
In a method for determining glossiness of an object's surface that classifies and ranks glossiness based on visual perception, as shown in Figure 1, the variance σ of the height distribution of the surface profile to be measured is expressed by the following equation {( 4πσ/λ ₁ )・cosθ ₁ } ² ≦1 …(1) {(4πσ/λ ₂ )・cosθ ₂ } ² ≧4 …(2) Wavelengths λ ₁ , λ ₂ (λ ₁ = λ ₂ ) are projected at incident angles θ ₁ and θ ₂ respectively, and the specular reflection intensities I ₁ and I ₂ and total reflection intensities S ₁ and S ₂ are _detected . /S ₁ , I ₂ /S ₂ ), plot the number of samples that statistically sufficiently represent each visual gloss level, and calculate the difference between each adjacent gloss level group for multiple gloss levels existing on a two-dimensional plane. The above object is achieved by determining a boundary line Z, which is a discriminant function that minimizes the overlap, and using the boundary line Z to classify the glossiness of any object to be measured. Here, the specular reflection intensity I means the intensity of the luminous flux in a minute area in the optical specular reflection direction (α=0) with respect to the incident angle θ of the incident light, as shown in Fig. 6 and the following equation. do. I=∫ ⁺ 〓 _- 〓i(θ)dθ i(θ): Distribution of reflected light flux α: Receiving angle (direction of regular reflection α=0) Also, the total reflection intensity S is shown in Fig. 6 and the following formula , it means the total intensity integrated over all directions of the optically reflected light beam with respect to the incident light. S=∫〓〓 _- 〓〓i(θ)dθ

[Effect]

The present invention was made based on the fact that the visual gloss of the surface of an object, such as a steel plate, depends on two surface roughness parameters: the average roughness and the average peak interval, and cannot be evaluated based on the average roughness alone. . That is, surface roughness is the main factor that determines the gloss of objects of substantially the same color, and it is basically considered that the degree of gloss can be evaluated by accurately grasping information on the surface roughness. Information on surface roughness can be roughly expressed by the variance σ of the height distribution of the surface profile and the autocorrelation distance T (distance at which the autocorrelation function is 1/e), and these quantities and the light reflection intensity The distribution includes e.g.
Published by Pergamon Press, P. Beckmann
and “The Scattering of
Electromagnetic Waves from Rough
There is a certain relationship as shown in ``Surfaces''.Furthermore, the results of detailed examination of these relationships by Yuichiro Asano et al. Accordingly, by satisfying each range of equations (1) and (2) above, the specular reflection intensities I ₁ and I ₂ under each condition have a relationship with the roughness parameters σ and T as shown in the following equation. I ₁ =f ₁ (σ) ...(3) I ₂ =f ₂ (σ, T) ...(4) However, the incident light intensity is assumed to be a unit intensity and the total reflectance is 1. Here, if the total reflectance is taken into account, the above (3),
The left sides of equation (4) are I ₁ /S ₁ and I ₂ /S ₂ (S ₁ and S ₂ are
(1) and (2) (total reflection intensity under each condition), and the information on the roughness parameters σ and T is I ₁ /
It is definitely included in both S ₁ and I ₂ /S ₂ information. Therefore, the glossiness is determined by both information of I ₁ /S ₁ and I ₂ /S ₂ and can be quantified. On the other hand, if we consider many samples of the same type of material but with different visual gloss levels, we can
When plotted on a dimensional plane (I ₁ /S ₁ , I ₂ /S ₂ ), these samples are divided into groups on the two-dimensional plane according to their glossiness, as shown in Figure 2, for example. Separately distributed. In FIG. 2, ◯ indicates a sample with visual gloss level 1, ▲ indicates a sample with visual gloss level 2, and □ indicates a sample with visual gloss level 3. The glossiness of these samples was determined by (I ₁ /S ₁ , I ₂ /
When classifying on the two-dimensional plane of S ₂ ), it is appropriate to define the boundary line Z and perform the classification so that the overlap between adjacent glossiness groups is statistically minimized.
The boundary line Z that minimizes the statistical overlap between two adjacent groups is derived using a discriminant function.
When this two-dimensional distribution is projected onto the Zv axis, it can be determined so that the overlap there will be minimized. Using this method, the boundary line Z ₁₂ between glossiness 1 and glossiness 2 and the boundary line Z ₂₃ between glossiness 2 and glossiness 3 in the glossiness group shown in FIG. 2 are obtained, and the classification is shown in FIG. For example, the boundary line _Z23 between glossiness 3 and glossiness 2 in the example of FIG. 4 is determined as follows. That is, when data as shown in Table 1 is obtained for each gloss level, the following statistics are calculated from these data using the following formula.

【table】

[Table] ⁽¹⁾ = _n 〓 ^a=1 Xai ⁽¹⁾ /n …(3) ⁽²⁾ = _n 〓 ^b=1 Xbi ⁽²⁾ /m …(4) Xi=( ⁽¹⁾ + ^{(2 )} )/2 …(5) di= ⁽¹⁾ − ⁽²⁾ (i=1,2,…p) …(6) Sij= _n 〓 ^a=1 (Xai ⁽¹⁾ − ⁽¹⁾ ) (Xaj ⁽¹⁾ − ⁽¹⁾ )+ _n 〓 ^b=1 (Xbi ⁽²⁾ − ⁽²⁾ ) (Xbj ⁽²⁾ − ⁽²⁾ ) (i, j=1,
2,...p)...(7) Vij=Sij/(n+m-2)...(8) Here, equations (3) and (4) are the average, and equation (7) is the within-group sum of squares.
The sum of products, Equation (8), calculates the within-group variance and covariance, respectively. From the above statistics, the boundary line Z, which is a discriminant function, can be determined using the following equation. Z= _P 〓 ⁱ⁼¹ ai (Xi−Xi) …(9) ai= _P 〓 ⁱ⁼¹ Vij・dj …(10) ∴a=V ^-1 d …(11) In addition, in the above explanation, 2 Although the method for determining the discriminant function of variables has been described, this method of determining the discriminant function can also be used to similarly determine the discriminant functions of two or more variables.

【Example】

EXAMPLES Hereinafter, an example in which the glossiness of a cold rolled steel sheet was determined according to the present invention will be described in detail. This embodiment aims to replace the conventional visual determination of glossiness (4 levels of glossiness 1 to 4) with automatic determination by measuring the light reflection intensities I ₁ and I ₂ . This was done to test performance. Surface roughness parameter σ of cold rolled steel sheet treated here
is 0.1 to 0.5 μm, and if a He-Ne laser beam with a wavelength λ = 0.633 μm is used as the luminous flux, the above equation (1) can be satisfied at an incident angle θ = 75°,
Furthermore, the above equation (2) can be satisfied when the incident angle θ=10°. In addition, in the case of the cold-rolled steel sheet treated here, the total reflectance is almost constant, and the two-dimensional plane (I ₁ /S ₁ , I ₂ /S ₂ ) used for gloss evaluation is the same as the two-dimensional plane (I ₁ /I ₂ )
is equivalent to FIG. 5 shows the results of determination according to this example. Each sample was visually judged by a plurality of skilled judges in comparison with a standard sample, and was classified into four levels of glossiness, 1 to 4. In Figure 5,
〇, ▲, □, ● are gloss levels 1, 2, 3, and 3, respectively.
4 samples are shown. On the other hand, for these samples, the specular reflection intensities I ₁ and I ₂ are measured, and for the samples belonging to each gloss level, discrimination is made between each gloss level group on the (I ₁ , I ₂ ) two-dimensional plane. Boundary lines Z ₃₄ , Z ₂₃ which are functions
and Z ₁₂ were derived. Derived boundaries Z ₃₄ , Z ₂₃
and Z ₁₂ were expressed by the following formula. Z ₃₄ =0.0043(I ₂ −1278) +0.0029(I ₁ −2269) …(12) Z ₂₃ =0.0219(I ₂ −1017) −0.0035(I ₁ −2113) …(13) Z ₁₂ =0.03( I ₂ −642) +0.0007 (I ₁ −2011) …(14) The boundary lines Z ₃₄ , Z ₂₃ and
As a result of using Z ₁₂ to judge the brightness of a large number of cold-rolled steel sheet samples, the judgment was made correctly for about 90% of the samples, confirming that it has sufficient judgment ability. In addition, although the present invention is applied to the determination of the glossiness of a cold-rolled steel plate in the above example, the scope of application of the present invention is not limited thereto, and can be similarly applied to determination of the glossiness of the surface of a general object. is clear.

【Effect of the invention】

As explained above, according to the present invention, for objects of the same color (brightness may differ), the visual glossiness closely matches the visual glossiness and can be quantitatively measured over a wide roughness range from specular to rough surfaces. It becomes possible to determine the gloss level. Therefore, it is possible to accurately measure and manage the surface quality online, which has excellent practical effects such as prevention of defects.

[Brief explanation of drawings]

FIG. 1 is a flowchart showing the gist of the method for determining the glossiness of _an object _surface according to the present invention, and _{FIG .} FIG. 3 is a diagram showing an example of the distribution of samples on a two-dimensional plane; FIG. 3 is a diagram showing an example of how to classify each gloss group; FIG. Fig. 5 is a diagram showing the judgment results of an example in which the present invention was applied to judge the glossiness of cold-rolled steel sheets. FIG. 3 is a diagram for explaining reflection intensity. σ...Dispersion, _λ1 , _λ2 ...Wavelength, _θ1 , _θ2 ...Incident angle, _I1 , _I2 ...Specular reflection intensity, _S1 , _S2 ...Total reflection intensity, Z, Z ₁₂ , Z ₂₃ , Z ₃₄ ... Boundary line.

Claims (1)

[Claims] 1. In a method for determining the glossiness of an object surface, which classifies and ranks the glossiness based on the visual perception based on the light reflection intensity distribution on the surface of the object, the dispersion σ of the height distribution of the surface profile to be measured is ^The wavelengths λ ₁ ^and _{λ 2} ( _{λ 1 = λ 2 also} ) are projected at incident angles θ ₁ and θ ₂ , respectively, and the specular reflection intensities I ₁ and I ₂ and total reflection intensities S ₁ and S ₂ are respectively
The number of samples that statistically sufficiently represent each visual gloss level is plotted in advance on a two-dimensional plane (I ₁ /S ₁ , I ₂ /S ₂ ), and multiple gloss levels existing on the two-dimensional plane are plotted. A boundary line Z, which is a discriminant function that minimizes the overlap between adjacent glossiness groups, is determined for each, and the glossiness of an arbitrary object to be measured is classified by the boundary line Z. A method for determining the glossiness of the surface of an object.