JP2001050902A - Method and device for evaluating state of object to be measured - Google Patents

Abstract

PROBLEM TO BE SOLVED: To determine the state of an object to be measured by calculating a main fluctuation coefficient corresponding to a specific image size, based on the brightness value of each section being divided into specific regions and calculating the correlation coefficient between a plurality image sizes and a plurality of main fluctuation coefficients. SOLUTION: An evaluation device 1 consists of an optical measurement means for measuring brightness information of the prescribed region of a sheet-shaped object 3, a computer 11, a display 5, and the like. With this configuration, light is applied from a light source 7 to the sheet-shaped object 3 in a production line, and the transmission light is received by a CCD camera 9 for accumulating brightness information in a prescribed region at the computer 11. Then, data for the specific region obtained by an operation part 13 is divided equally into same image sizes. Then, the brightness value of each section is calculated for each divided pattern to obtain a group of brightness values. After that, an average of the brightness is obtained for each group of brightness values. Then, main measurement result coordinates with the image size as X coordinates and the main fluctuation coefficient as Y coordinates is subjected to regression into a primary straight line by the least square method, thus calculating the main correlation coefficient.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method and an apparatus for evaluating the state of an object to be measured, such as paper and nonwoven fabric.

[0002]

2. Description of the Related Art It is a well-known fact that a sheet-like material composed of fibers causes an appearance defect due to uneven distribution of the constituent fibers. However, the uneven distribution of the constituent fibers is not limited only to the quality of appearance, for example, the elasticity of the patch base material,
It greatly affects the functions in use, such as short-circuit resistance, of an insulating substrate used as an insulating substrate by thermocompression bonding of a battery substrate (separator) or a nonwoven fabric. Therefore, in order to eliminate the uneven distribution of the constituent fibers, not only the production technique itself of the sheet-like material itself is improved, but also the uneven distribution evaluation technique serving as an index thereof is increasing in importance.

As a technique for evaluating the uneven distribution (formation) of such fibers, a sheet-like material having several levels of unevenness prepared in advance is compared with an object to be measured, and the uneven distribution state (formation) of these fibers is determined. Conventionally, subjective evaluation, such as simple visual comparison, has been performed. However, due to the recent development of electronic devices, evaluation of the uneven distribution state of fibers has been replaced by objective evaluation using electronic devices.

Various techniques for evaluating the uneven distribution of fibers using such electronic devices have been proposed.
Many of them irradiate light to a sheet-like object to be measured, and reflect or transmit the reflected light or transmitted light to, for example, 256 gradations (8
A method has been adopted in which a solid-state imaging device (CCD) or the like that can be distinguished by shading of t) quantifies it as luminance information, and this numerical value is processed.

[0005] As a measurement technique using such a CCD, a "1996 Nonwovens Conference" Proceedings P23
9-244 ("CHARACTERIZING NONWOVEN WEB STRUCTUR
E USING IMAGE ANALYSIS TECHNIQUES '', RRBresee
Et al., Held in the United States on March 11-13, 1996)
There have been reports of the results of various arithmetic processings on luminance information obtained from target sheets. Especially in Fig. 9,
Brightness information (256 gradations) obtained at various resolutions by changing the measurement area when scanning the nonwoven fabric to be measured
Coefficient of variation CV (%) obtained by dividing the standard deviation σ of
Are obtained, and the measurement results are shown in which the variation coefficient CV is plotted against the image size (mm) corresponding to the dimension of one side when the measurement area is regarded as a square. By examining the graph showing the measurement results and comparing the CV values,
It is possible to determine which of the nonwoven fabrics to be compared has better uniformity.

[0006]

However, in the above-described conventional method for evaluating the uneven distribution state (formation) of fibers, it is possible to judge the uniformity of the nonwoven fabric to be compared, but the degree of uniformity is not so high. Was not able to be expressed as a specific numerical value, so that it was insufficient as a means for evaluating the uneven distribution state of the fiber.

[0007] The same problem arises when evaluating the surface condition of a special metal foil or when evaluating the printing condition of a printed sheet.

[0008] Therefore, the present invention is to apply the measurement technique,
An object of the present invention is to provide a state evaluation method and a state evaluation device capable of quantifying the state of an object to be measured by expressing the evaluation of the state of the object to be measured as specific numerical values.

[0009]

Means for Solving the Problems As a result of intensive studies to achieve the above object, the present inventors have found that small structural features are physically uniformized as the measurement area increases, so that various features are obtained. The correlation between the measured dimension of the sample and the CV value was taken, and it was found that the state of the object to be measured could be evaluated by the correlation coefficient, and the present invention was completed.

That is, the method for evaluating the state of an object to be measured according to the present invention comprises the steps of irradiating a predetermined area of the object with light, receiving reflected light or transmitted light from the predetermined area, and acquiring luminance information; A predetermined area of the device under test is divided by a predetermined image size, a luminance value of each divided section is calculated based on luminance information, and a main value corresponding to the predetermined image size is calculated based on the luminance value of each section. Calculating the variation coefficient, repeating the calculation of the main variation coefficient while changing the size of the predetermined image size, based on the plurality of image sizes and the plurality of main variation coefficients, the image size and the main variation coefficient, And calculating a main correlation coefficient indicating the correlation between the two.

In addition, the device for evaluating the state of an object to be measured according to the present invention comprises:
A light source that irradiates light to the device under test; light receiving means for receiving reflected light or transmitted light reflected or transmitted in a predetermined region of the device to obtain luminance information; The area is divided by a predetermined image size, a luminance value of each divided section is calculated based on the luminance information, and a main variation coefficient corresponding to the predetermined image size is calculated based on the luminance value of each section. First calculating means, changing means for changing the size of a predetermined image size, and a correlation between the image size and the main variation coefficient based on the plurality of image sizes and the plurality of main variation coefficients. And a second calculating means for calculating a main correlation coefficient indicating

With this configuration, of the light emitted from the light source to the object to be measured, reflected or transmitted light reflected or transmitted in a predetermined area of the object to be measured is received by the light receiving means, and the luminance information is received. Is obtained. Next, the predetermined area of the device under test is divided by the predetermined image size by the first calculating means, and the luminance value of each divided section is calculated based on the luminance information, and based on the luminance value of each section. Thus, the main variation coefficient corresponding to the predetermined image size is calculated. The calculation of the main variation coefficient is repeated while the size of the predetermined image size is changed by the changing unit. Thereafter, the second calculating means calculates a main correlation coefficient indicating a correlation between the image size and the main variation coefficient based on the plurality of image sizes and the plurality of main variation coefficients. In this way, the main correlation coefficient is obtained as a specific numerical value, and it is possible to objectively evaluate the state of the device under test based on the numerical value.

In the method of evaluating the state of an object to be measured according to the present invention, in the step of calculating the main variation coefficient, the average brightness and the standard deviation of the entire predetermined area are calculated based on the brightness value of each section. The main variation coefficient may be calculated based on the standard deviation. In the device for evaluating the state of an object to be measured according to the present invention, the first calculating means calculates a luminance average and a standard deviation of the entire predetermined area based on the luminance value of each section, and calculates the luminance average and the standard deviation based on the luminance average and the standard deviation. And calculating the main variation coefficient.

According to this configuration, in the first calculating means,
A luminance average and a standard deviation of the entire predetermined area are calculated based on the luminance value of each section, and a main variation coefficient is calculated based on the luminance average and the standard deviation.

In the method for evaluating the state of an object to be measured according to the present invention, in the step of calculating the main variation coefficient, the first and second areas intersecting each other in a predetermined area based on the luminance value of each section.
The first and second variation coefficients of the direction may be calculated, and the main variation coefficient may be calculated based on the first and second variation coefficients. Further, in the device for evaluating the state of an object to be measured according to the present invention, the first calculating means calculates the first and second variation coefficients in the first and second directions intersecting each other with respect to the predetermined area based on the brightness value of each section. Then, the main variation coefficient may be calculated based on the first and second variation coefficients.

With this configuration, the first calculating means calculates the first and second variation coefficients in the first and second directions intersecting each other with respect to the predetermined area based on the brightness value of each section. The main variation coefficient is calculated based on the second variation coefficient.

Further, in the method for evaluating the state of an object to be measured according to the present invention, a first correlation indicating a correlation between an image size and a first variation coefficient based on a plurality of image sizes and a plurality of first variation coefficients.
The method may further include a step of calculating a correlation coefficient. In the device for evaluating the state of a device under test according to the present invention, a first correlation coefficient indicating a correlation between an image size and a first variation coefficient is calculated based on a plurality of image sizes and a plurality of first variation coefficients. It may be characterized by further comprising a third calculating means.

According to this configuration, the third calculating means indicates the correlation between the image size and the first variation coefficient based on the plurality of image sizes and the plurality of first variation coefficients.
A correlation coefficient is calculated. Then, more specific evaluation of the state of the device under test can be performed using the first correlation coefficient and the main correlation coefficient.

In the method and the apparatus for evaluating the state of a device under test according to the present invention, the main correlation coefficient is a group of main measurement results obtained based on a plurality of logarithms of image sizes and a plurality of main variation coefficients. It may be characterized in that the coordinates are obtained as an inclination when regressed to a linear line.

In this way, the main correlation coefficient is obtained as a gradient when the main measurement result group coordinates obtained based on the logarithms of a plurality of image sizes and the plurality of main variation coefficients are regressed to a linear line. Can be

In the method and the apparatus for evaluating the state of an object to be measured according to the present invention, regression to a linear line may be performed by a least square method. In this way, the regression to the linear line is performed by the least square method.

Further, the method for evaluating the state of an object to be measured according to the present invention further comprises a step of calculating a ratio of the main correlation coefficient to a previously obtained main correlation coefficient for another object to be measured. It may be characterized. The device for evaluating the state of a device under test according to the present invention may further include a fourth calculating unit that calculates a ratio between the main correlation coefficient and the main correlation coefficient obtained for another device under test. It may be characterized.

With this configuration, the fourth calculating means calculates the measured value of the measured object based on the ratio of the main correlation coefficient of the measured object to the previously obtained main correlation coefficient of another measured object. It allows relative evaluation of the state of an object. In particular, when another DUT is a reference sample, the degree of superiority of the state with respect to the reference can be obtained as an objective numerical value.

In the method and the apparatus for evaluating the state of an object to be measured according to the present invention, the luminance information is obtained by dividing the reflected light or the transmitted light into a plurality of light components and obtaining the luminance for each light component. It may be characterized by including information. With this configuration, it is possible to evaluate the state of the device under test in more detail using the luminance information for each light component, that is, the luminance information for each color.

In the method and apparatus for evaluating the state of an object to be measured according to the present invention, the object to be measured may be a sheet made of fibers. As described above, the state evaluation method and the state evaluation apparatus of the object to be measured according to the present invention can be suitably used for evaluating the formation of a sheet-like material made of fibers such as paper and nonwoven fabric.

[0026]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Preferred embodiments of the method and apparatus for evaluating the state of a device under test according to the present invention will be described below with reference to the accompanying drawings. Note that the same components are denoted by the same reference numerals, and redundant description will be omitted. Here, in this specification, the object to be measured mainly means a sheet-like material such as paper, nonwoven fabric, special metal foil, or a printed sheet, and the state of the object to be measured refers to the state of the entire object to be measured or the state of the object to be measured. It means the state of the surface of the measured object. Specifically, it means, for example, the uneven distribution state (formation) of fibers of a sheet-like material made of fibers such as paper and nonwoven fabric, the surface state of a special metal foil, the printed state of a printed sheet, and the like. In the following embodiment, a case will be described in which the formation of a sheet-like material composed of fibers such as paper and nonwoven fabric is evaluated.

FIG. 1 is a perspective view showing a first embodiment of a device for evaluating the state of an object to be measured (hereinafter also referred to as an evaluation device) according to the present invention.

As shown in FIG. 1, a sheet-like material (measurement object) 3 made of fibers such as paper and nonwoven fabric is produced by a conveying means (not shown) in a direction indicated by an arrow 5 (this is a production direction). ).

At this time, in order to evaluate the uneven distribution of the fibers of the sheet-like material 3, that is, the so-called formation, the evaluation device 1 uses the sheet-like material 3.
Optical measuring means capable of measuring the luminance information of the predetermined area. The optical measuring means includes a light source, for example, a fluorescent lamp 7 disposed below the sheet-shaped material 3, and a light-receiving means disposed above the sheet-shaped material 3 and receiving light transmitted through the sheet-shaped material 3.
For example, a CCD camera 9 is provided. The CCD camera 9 may be configured to generate the luminance information by directly receiving the transmitted light without dispersing the transmitted light, or to separate the transmitted light into red (R), green (G), and blue (B) light components. Alternatively, a configuration may be adopted in which these light components are received to generate luminance information for each light component.

The evaluation device 1 also includes a computer 11 for processing the transmitted video signal from the CCD camera 9 and a display 15 for displaying the processing result. The CCD camera 9 and the computer 11 are electrically connected, and the transmitted video signal from the CCD camera 9 is transmitted to the computer 11 and stored as luminance information in a predetermined area. The computer 11 has an operation unit 13 for performing various operations inside. The luminance information in a predetermined area is processed by the operation unit 13 using image processing software, and as a result, the formation evaluation is displayed on the display 15. Is displayed.

In the evaluation apparatus 1 of this embodiment, the fluorescent lamp 7 and the CCD camera 9 are arranged on the same side of the sheet 3, and the CCD camera 9 reflects the light reflected on the sheet 3. It may be configured to detect light. Further, a configuration may be adopted in which luminance information in a predetermined area of the sheet-like material 3 is read by a page scanner.

As shown in FIG. 2, the calculation unit 13 of the computer 11 includes a main variation coefficient calculation unit (first calculation unit) 1
7, an image size changing unit (changing unit) 19, a main correlation coefficient calculating unit (second calculating unit) 21, and a ratio calculating unit (fourth calculating unit) 23.

The main variation coefficient calculator 17 is provided with the CCD camera 9
Sheet-like object 3 based on the luminance information transmitted from
Is divided by a predetermined image size to calculate a luminance value of each section, and a main variation coefficient corresponding to the predetermined image size is calculated based on the luminance value of each section.

The image size changing section 19 is connected to the main variation coefficient calculating section 17 and transmits to the main variation coefficient calculating section 17 a signal for changing an image size for dividing a predetermined area of the sheet 3. .

The main correlation coefficient calculating section 21 is connected to the main variation coefficient calculating section 17, and includes a plurality of image sizes obtained by changing the image size and a plurality of image sizes calculated corresponding thereto. A main correlation coefficient indicating a correlation between the image size and the main variation coefficient is calculated based on the main variation coefficient.

The ratio calculating section 23 is connected to the main correlation coefficient calculating section 21, and the main correlation coefficient calculated by the main correlation coefficient calculating section 21 and another sheet stored in the storage means 25. The ratio with respect to the main correlation coefficient of the object (other measured object) is calculated.

Storage means 2 constituted by this RAM or the like
Reference numeral 5 is connected to the operation unit 13 and stores various values calculated by the operation unit 13 and supplies data stored in advance to the operation unit 13.

Next, a method of evaluating the formation of the sheet-like material 3 using the evaluation apparatus 1 of the first embodiment having the above-described configuration will be described with reference to the flowchart of FIG.

First, light is emitted from the light source 7 to the sheet material 3 in the production line, the transmitted light is received by the CCD camera 9, and luminance information in a predetermined area is stored in the computer 11 (S1). In this case, the resolution can be set arbitrarily, but analysis is usually performed with an accuracy of about 400 dpi. Numerical values constituting the luminance of each pixel are 0 to 8 bits.
It is represented by 255 digitized gradations. As the luminance information, luminance information generated by directly receiving the transmitted light without dispersing the transmitted light may be used, or the transmitted light may be converted into red (R), green (G), and blue (B) light components. It is also possible to use the luminance information for each light component generated by spectrally separating and receiving these light components. However, if the luminance information for each light component, that is, the luminance information for each color, is used, the formation of the sheet 3 can be evaluated in more detail. For example,
It is possible to evaluate the distribution state of colored fibers.

Next, in the calculation unit 13 of the computer 11, more specifically, in the main variation coefficient calculation unit 17, the bitmap data of the predetermined area obtained by the above method is converted into a predetermined same image using image processing software. It is equally divided into sizes (S2). In this case, it is preferably equally divided into at least two or more square sections, and more preferably four or more sections. Then, a signal for changing the image size is sent from the image size changing unit 19 to the main variation coefficient calculating unit 17 to divide the predetermined area into at least two or more types of image sizes _Sn.
To obtain a plurality of division patterns. The number of image size S _n (division pattern), although evaluation of the texture if at least two is possible, since the reliability of the formation index P, which will be described later As the number of image size S _n increases , it is preferable to perform split operation for the image size S _n of 3 or more. Further, if the predetermined area is divided so that the sections do not overlap each other, the variation coefficient CV can be significantly obtained, and as a result, the reliability of the formation index P described later is further improved. Also, the luminance information of each divided section does not necessarily need to be used in the following processing. Further, the predetermined area may be equally divided into a non-square shape. For example, it may be equally divided into a rectangular shape and a circular shape.

Next, likewise the main variation coefficient calculation unit 17, for each of the divided pattern of the n pieces of divided patterns corresponding to n image size S ₁ to S _n, the luminance of each section of the equally divided squares It calculates a value to obtain the luminance value group G ₁ ~G _n (S3).

Here, for the sake of simplicity, a case where n = 2, that is, a case where a predetermined area is equally divided by two kinds of image sizes to obtain two luminance value groups will be described with reference to FIG. FIG. 4A shows a case where a sheet 3 of 15 cm square is scanned by a page scanner and divided into four identical image sizes of 7.5 cm square as an image size S ₁ (division pattern 1). 4 (b) is a 15 cm square sheet 3
Is defined as an image size S ₂ (divided pattern 2) of 9
It shows a case where the image is divided into the same image size. For example, the accuracy of the scanner is 400 dpi, the image size is considered the case of S _1, the luminance value g ₁₁ to g ₁₄ of each compartment,
Approximately 1180x1180 ($ 400 / 25.4x
75｝ ² ) pixels, represented by the average value of the luminance,
The luminance value group G ₁ = (g ₁₁ , g ₁₂ , g ₁₃ , g ₁₄ ) corresponding to the image size S ₁ (divided pattern 1) is obtained. Also,
When the image size is considered the case of S _2, the luminance value g of each compartment
₂₁ to g _{2 9} are each about 787 × 787 ({400 ÷ 2
A luminance value group G ₂ = (g ₂₁ , g ₂₂ ,..., G) represented by an average value of luminance in 5.4 × 50 ² pixels corresponding to an image size S ₂ (divided pattern 2). ₂₈ , g ₂₉ ) are obtained.

Next, average brightnesses X _{1 to} X _n are calculated for each of the brightness value groups G _{1 to} G _n . (S4) This is simply obtained as an arithmetic average of luminance values. For example, when the image size of the above Consider the case of S _1, the average brightness X ₁ can be determined as _{X 1 = (g 11 + g} 12 + g 13 + g 14) / 4.

Next, standard deviations σ _{1 to} σ _n are calculated for each of the luminance value groups G _{1 to} G _n (S5). For example, when the above-mentioned image size is S ₁ , the standard deviation σ ₁ is

(Equation 1) Can be obtained as

Next, the standard deviations σ _{1 to} σ _n are converted to the luminance averages X ₁ to
The main variation coefficient divided by _{X n CV 1 ~CV n (CV} n = σ n /
X _n ) is calculated (S6). For example, when the image size of the above Consider the case of S _1, the main coefficient of variation CV ₁ is determined as _{CV 1 = σ 1 / X 1} . Although the main coefficient of variation CV _n is generally determine a percentage, in the present embodiment, since taking the ratio of the slope k _M and k _R as formation index as described below, as the main coefficient of variation CV _n The same formation index can be obtained simply by using a value obtained by dividing the standard deviation σ _n by the average luminance X _n .

Next, the main correlation coefficient x coordinate logarithmic image size S ₁ to S _n in the arithmetic unit 21, the main coefficient of variation CV ₁ -C
Main measurement result group coordinates と_した (Log _a S ₁ , CV
₁ ),..., (Log _{a Sn} , CV _n )} (where a is 1
Are regressed to a linear line by the least squares method, and the slope k _M (main correlation coefficient) is calculated (S7). In addition,
Since the logarithm of the image size is used as the x coordinate, the area of the reading area can be used instead of the image size.

Finally, in the ratio calculator 23, the main phase relation
The slope k calculated by the numerical operation unit 21_MAnd the storage means 25
Tilt of reference sample (other DUT) stored in advance
K _RAnd calculate it as the formation index P
(S8). That is, P is P = k_M/ K_R It is expressed as

As described above, in the present embodiment, the image size S
_n logarithmic main variation coefficient primary measurement result group coordinates obtained by the _{CV n {(Log a S 1} , CV 1), ····, (Log a S n,
By regressing CV _n )｝ to a linear line, the degree of averaging of the main variation coefficient CV _n is quantified in the form of the gradient of the linear line, so that the formation of the sheet-like material 3 is a specific numerical value. Can be evaluated objectively. For example, if the uniformity of the sheet 3 is high, the inclination k _M is reflected as a result close to 0. Also, with this slope k _M ,
By taking the ratio with the slope k _R obtained in advance for the reference sample and calculating this ratio as the formation index P, objective formation evaluation with respect to the predetermined reference can be realized with high reproducibility.

In this embodiment, the sheet 3 continuously flowing in the production line is scanned at regular intervals, and the slope k _M as a main correlation coefficient is calculated at regular intervals. Alternatively, a change in the quality of the sheet 3 may be monitored. Also, the formation index P may be used not only for evaluation of formation with respect to a predetermined reference, but also for relative evaluation of the formation state of sheet materials different from each other.

Next, a second embodiment of the device for evaluating the state of an object to be measured according to the present invention will be described.

The evaluation device 1 according to the present embodiment is similar to the evaluation device shown in FIGS.
Is different from the evaluation device of the first embodiment described above.

That is, in the calculation unit 13 of the evaluation device 1 of the present embodiment, the main variation coefficient calculation unit 17 converts a predetermined area of the sheet 3 into a predetermined image based on the luminance information transmitted from the CCD camera 9. The luminance value of each section is calculated by dividing by the size. Then, based on the luminance value of each section, the production direction variation coefficient (first variation coefficient or second variation coefficient) in the production direction 5 (first direction or second direction) of the sheet-like material 3 and the production direction 5 Is calculated in the width direction 27 (the second direction or the first direction) in the width direction 27 (the second direction or the first direction) which is orthogonal to. Then, the main variation coefficient is calculated by averaging the production direction variation coefficient and the width direction variation coefficient.

The image size changing section 19 transmits a signal for changing the image size for dividing a predetermined area of the sheet 3 to the main variation coefficient calculating section 17.

Then, the main correlation coefficient calculator 21 (the second calculator and the third calculator) calculates a plurality of image sizes obtained by changing the image sizes and the corresponding image sizes. The main correlation coefficient indicating the correlation between the image size and the main fluctuation coefficient is calculated based on the plurality of main fluctuation coefficients. Further, the main correlation coefficient calculation unit 21 determines the image size and the production direction based on the plurality of image sizes obtained by changing the image size and the plurality of production direction variation coefficients calculated so as to correspond thereto. The production direction correlation coefficient indicating the correlation with the variation coefficient is calculated. Alternatively, a plurality of image sizes obtained by changing the image size,
A width-direction correlation coefficient indicating a correlation between the image size and the width-direction variation coefficient is calculated based on the plurality of width-direction variation coefficients calculated so as to correspond thereto. Note that the main correlation coefficient calculator 21 may calculate both the production direction correlation coefficient and the width direction correlation coefficient.

As described above, in the present embodiment, not only the main correlation coefficient is calculated in the main correlation coefficient calculation unit 21 but also the production direction correlation coefficient or the width direction correlation coefficient is calculated. Reference numeral 13 may include an operation unit for calculating the production direction correlation coefficient or the width direction correlation coefficient, separately from the main correlation coefficient operation unit 21.

Next, a method of evaluating the formation of the sheet-like material 3 using the evaluation apparatus 1 of the second embodiment having the above-described configuration will be described.
A description will be given along a flowchart showing the data processing procedure of FIG.

First, similarly to the first embodiment, light is applied to the sheet 3 from the light source 7 in the production line, the transmitted light is received by the CCD camera 9, and luminance information in a predetermined area is stored in the computer 11. (S11). In this case, the resolution can be set arbitrarily, but usually 400 dpi
Analyze with a degree of accuracy. The numerical value constituting the luminance of each pixel is represented by a digitized gradation of 0 to 255 in the case of 8 bits. In addition, as the luminance information, the first
As in the embodiment, the luminance information generated by directly receiving the transmitted light without dispersing the transmitted light may be used, or the transmitted light may be separated into red (R), green (G), and blue (B) light components. Alternatively, luminance information for each light component generated by receiving these light components may be used.

Next, in the calculation unit 13 of the computer 11, more specifically, in the main variation coefficient calculation unit 17, the bitmap data of the predetermined area obtained by the above method is converted into a predetermined same image using image processing software. It is equally divided into sizes (S12). In this case, it is preferably equally divided into at least two or more square sections, and more preferably four or more sections. Then, a signal for changing the image size is sent from the image size changing unit 19 to the main variation coefficient calculating unit 17 to divide the predetermined area into at least two or more types of image sizes _Sn.
To obtain a plurality of division patterns. The number of image size S _n (division pattern), although evaluation of the texture if at least two is possible, since the reliability of the formation index P, which will be described later As the number of image size S _n increases , it is preferable to perform split operation for the image size S _n of 3 or more. Further, if the predetermined area is divided so that the sections do not overlap each other, the variation coefficient CV can be significantly obtained, and as a result, the reliability of the formation index P described later is further improved. Also, the luminance information of each divided section does not necessarily need to be used in the following processing. Further, the predetermined area may be equally divided into a non-square shape. For example, it may be equally divided into a rectangular shape and a circular shape.

Next, likewise the main in variation coefficient calculation unit 17, for each of the divided pattern of the n pieces of divided patterns corresponding to n image size S ₁ to S _n, the luminance of each section of the equally divided squares It calculates a value to obtain the luminance value group G ₁ ~G _n (S13).

Here, as a method of calculating the luminance value groups G _{1 to} G _n , the same method as in the first embodiment is used as shown in FIG.

Next, each luminance value group G₁~ G_nUsing each shine
Width variation coefficient CV in degree value group _CDnAnd change of production direction
Dynamic coefficient CV_MDnIs calculated (S14). And the width direction
Coefficient of variation CV_CDnAnd production direction variation coefficient CV_MDnAnd average
By doing so, each luminance value group G₁~ G_nMain variation coefficient CV in
₁~ CV_nIs calculated (S15).

Here, a method of calculating the width direction variation coefficient CV _CDn and the production direction variation coefficient CV _MDn and the main variation coefficient CV _{n for} the division pattern 2 (see FIG. 4B) will be described with reference to FIG. explain.

First, the luminance values g _{21 to} g ₂₉ of each of the nine sections are used, and are used as the luminance value group (g ₂₁ , g ₂₂ ,
g _23), the width direction second stage of the luminance value group (g _24, g _25,
g ₂₆ ), and a luminance value group (g ₂₇ ,
g ₂₈ , g ₂₉ ). Then, the luminance average X _1CD and the standard deviation σ _1CD of the first step in the width direction are calculated. First in width direction
The luminance average X _{1CD at the level} can be obtained as X _1CD = (g ₂₁ + g ₂₂ + g ₂₃ ) / 3.

The standard deviation σ of the first step in the width direction is
_1CD is

(Equation 2) Can be obtained as

Then, using the luminance average X _1CD and the standard deviation σ _1CD of the first step in the width direction, the variation coefficient CV _1CD of the first step in the width direction is obtained as CV _1CD = σ _1CD / X _1CD. Can be.

This operation is also performed on the second and third stages in the width direction, and the variation coefficient CV _2CD and the variation coefficient CV _3CD on the second stage in the width direction are calculated.
_The width direction variation coefficient CV _CDn is calculated by averaging _{1CD to} CV _3CD .

On the other hand, the luminance values g _{21 to} g ₂₉ of each of the nine sections are used, and this is used as the luminance value group (g ₂₁ ,
g _24, g _27), production direction second stage of the luminance value group (g _22, g
_25, g _28), and divided into production direction third stage luminance value group _{(g 23, g 26, g} 29). And production direction 1
The luminance average X _1MD and the standard deviation σ _1MD of the stage are calculated.
The luminance average X _{1MD in} the first stage in the production direction can be obtained as X _1MD = (g ₂₁ + g ₂₄ + g ₂₇ ) / 3.

Also, the standard deviation σ _1MD of the first stage in the production direction
Is

(Equation 3) Is required.

Using the luminance average X _1MD and the standard deviation σ _1MD of the first stage in the production direction, the variation coefficient CV _1MD of the first stage in the production direction is obtained as CV _1MD = σ _1MD / X _1MD. Can be.

This operation is also performed for the second and third stages in the production direction, and the variation coefficient CV of the second stage in the production direction is obtained.
_2MD and third stage of calculating a coefficient of variation CV _3MD, these CV _{1M D} ~CV _3MD average of production direction coefficient of variation CV _MDn
Is calculated.

[0071] Finally, to calculate the main coefficient of variation CV _n by averaging the width direction variation coefficient CV _CDn and production direction variation coefficient CV _MDn.

Next, the main correlation coefficient calculation unit 21, x-coordinate of the logarithm of the image size S ₁ to S _n, the main coefficient of variation CV ₁ ~
Main measurement result group coordinates と_した (Log _a S ₁ , C
V ₁ ),..., (Log _{a Sn} , CV _n ) (where a is a positive number excluding 1) is regressed to a linear line by the least squares method,
The slope k _M (main correlation coefficient) is calculated (S16). Since the logarithm of the image size is used as the x coordinate,
The area of the reading area can be used instead of the image size.

Finally, in the ratio calculator 23, the main phase relation
The slope k calculated by the numerical operation unit 21_MAnd the storage means 25
Tilt of reference sample (other DUT) stored in advance
K _RAnd calculate it as the formation index P
(S17). That is, P is P = k_M/ K_R It is expressed as

As described above, in the present embodiment, the image size S
_n logarithmic main variation coefficient primary measurement result group coordinates obtained by the _{CV n {(Log a S 1} , CV 1), ····, (Log a S n,
By regressing CV _n )｝ to a linear line, the degree of averaging of the main variation coefficient CV _n is quantified in the form of the gradient of the linear line, so that the formation of the sheet-like material 3 is a specific numerical value. Can be evaluated objectively. For example, if the uniformity of the sheet 3 is high, the inclination k _M is reflected as a result close to 0. Also, with this slope k _M ,
By taking the ratio with the slope k _R obtained in advance for the reference sample and calculating this ratio as the formation index P, objective formation evaluation with respect to the predetermined reference can be realized with high reproducibility.

[0075] In the second embodiment also, the sheet 3 come flowing continuously in the production line scans at predetermined intervals, calculates an inclination k _M as a main correlation coefficient for each predetermined time Thus, a change in the quality of the sheet material 3 may be monitored. Also, the formation index P may be used not only for evaluation of formation with respect to a predetermined reference, but also for relative evaluation of the formation state of sheet materials different from each other.

In the present embodiment, the main correlation coefficient calculating section 2
In 1, the image size S ₁ to S _n logarithm x-coordinate, width measurements group coordinates the widthwise variation coefficient CV _CD1 ~CV _CDn and y coordinates of _{{(Log a S 1, CV} CD1), ···・, (Log _a
S _n , CV _CDn )｝ (where a is a positive number excluding 1) is regressed to a linear line by the least squares method, and its slope k _CD (width direction correlation coefficient) is calculated (S 18). Or, each luminance value group G
Production direction measurement result group coordinates と_{し た} (Log _a S ₁ , CV _MD1 ) _where the logarithm of image sizes S _{1 to} Sn corresponding to _{1 to} G _n is the x coordinate and the production direction variation coefficients CV _{MD1 to} CV _MDn are the y coordinate. , ...,
_{(Log a S n, CV MDn} )} ( where, a is a positive number other than 1) to return to a linear line by the least square method to calculate the slope k _MD (production direction correlation coefficient) (S18). Since the logarithm of the image size is used as the x coordinate, the area of the reading area can be used instead of the image size.

[0077] Then, the ratio ratio Q _CD main correlation coefficient k widthwise correlation coefficients for _M k _CD or production direction correlation coefficient k _MD in the arithmetic unit _{23 (Q CD = k CD /} k M) or Q _MD ( Q _MD
= K _{M D} / k _M ) (S19), it is possible to evaluate whether or not there is a streak in the sheet-like material 3, and evaluate the condition of the streak. That is, as the sheet-like material 3, for example, depending on the technology for producing the nonwoven fabric, streaks (stripes) in a specific direction (particularly, the production direction or the width direction) of the nonwoven fabric to be produced.
May occur. Since this streak sometimes becomes a defect as a product, it is necessary to adjust production conditions for the purpose of eliminating the streak. In some cases, these streaks are positively incorporated into the sheet-like material 3 as a design effect (for example, Japanese Patent Application Laid-Open No. 57-39268 discloses that the web is entangled by a high-pressure water flow to thereby increase the production direction. A technique for forming a striped pattern along the line is disclosed). Therefore,
A technique for evaluating whether or not the sheet-like material 3 has a streak and a condition of the streak are desired.

In the present embodiment, the ratio Q of the width direction correlation coefficient k _CD or the production direction correlation coefficient k _{MD to} the main correlation coefficient k _{M is}
By calculating the _CD or Q _MD, whether the sheet 3 is muscle, and can evaluate the condition of the muscle. For example, when there is no streak in the sheet-like material 3, the fluctuations in the width direction correlation coefficient k _CD and the production direction correlation coefficient k _MD with respect to the main correlation coefficient k _M are extremely small. In contrast, the variation in the width direction correlation coefficient k _CD and production direction correlation coefficient k _MD with respect to the main correlation coefficient k _M If the sheet 3 is muscle becomes extremely large.

Therefore, by calculating the ratio Q _CD or Q _MD of the width direction correlation coefficient k _CD or the production direction correlation coefficient k _{MD to} the main correlation coefficient k _M , if the sheet 3 has no streak, The values of Q _CD and Q _MD are very close to 1, while the values of the ratios Q _CD and Q _MD are 1 if the sheet 3 has streaks.
Keep away from

By calculating the ratio Q _CD or Q _MD in this manner, it is possible to determine whether or not there is a streak in the sheet-like material 3 and to evaluate the condition of the streak.

Next, the state evaluation method using the apparatus for evaluating the state of an object to be measured according to the present invention will be described in more detail with reference to examples.

[0082]

EXAMPLES (1) Example 1 As shown in Table 1, two nonwoven fabrics having different formations, which were entangled with each other as sheets, were used as measurement samples A and B.

[Table 1]

In sample A, the average fineness of the constituent fibers was 0.3.
In Sample B, the average fineness of the constituent fibers is 2.8d (3d and 1.2d are mixed at a ratio of 9: 1), and the average fineness of the constituent fibers is different. As a result, as can be seen from FIGS. 7 and 8 showing the states of Samples A and B, Sample A, which has a smaller average fineness, is visually superior to Sample B.

Each of these two samples was cut into a 15 cm square, and was set on a commercially available page scanner.
And brightness information was obtained and calculated in five divided patterns having an image size of 3 mm square to 48 mm square. In the calculation at this time, luminance information was sent from the page scanner to the personal computer, and the information was processed by Microsoft Excel.

FIG. 9 shows the logarithm of the image size as the x coordinate.
It is the graph which plotted the main measurement result group coordinate obtained as a result of calculation when the main variation coefficient was made into y coordinate.

The equation of the straight line L1 when the main measurement result group coordinates (indicated by triangles in the figure) of the sample A are regressed to the linear line by the least square method is obtained as y = −0.192x + 1.224. Therefore, the main correlation coefficient k _M is -0.192
Is required. The equation of the straight line L2 when the main measurement result group coordinates of the reference sample B (indicated by white circles in the figure) are regressed to a linear line by the least squares method is obtained as y = −0.588x + 3.804. Therefore, the main correlation coefficient k _R is −0.588.
Is required. As a result, the formation index P (= k _M / k _R ) was about 0.327, and a high correlation was obtained with the visual comparison of FIGS. 7 and 8. (2) Example 2 As shown in FIG. 10, a nonwoven fabric having no streak as a sheet material was used as sample C, and a nonwoven fabric having streaks in the production direction was used as a measurement sample D as shown in FIG. 11.

These two samples were cut to a size of 15 cm square, and set on a commercially available page scanner.
, And luminance information was obtained and calculated in four divided patterns having an image size of 3 mm square to 24 mm square. In the calculation at this time, luminance information was sent from the page scanner to the personal computer, and the information was processed by Microsoft Excel.

FIG. 12 shows the measurement result group coordinates obtained as a result of calculation when the logarithm of the image size for sample C is x-coordinate and the main variation coefficient / width-direction variation coefficient / production-direction variation coefficient is y-coordinate. Is a graph in which is plotted.

The equation of the straight line L1 when the main measurement result group coordinates of the sample C (indicated by white circles in the figure) are regressed to a linear line by the least square method is obtained as y = −0.5735x + 2.7636. Therefore, the main correlation coefficient k _M is -0.573
5 is required. The equation of the straight line L2 when the production direction measurement result group coordinates (indicated by white squares in the figure) are regressed to a linear line by the least squares method is obtained as y = −0.5696x + 2.7728. Therefore, the production direction correlation coefficient k _MD is −0.
5696 is required. The equation of the straight line L3 when the width direction measurement result group coordinates (indicated by white triangles in the figure) are regressed to a primary straight line by the least square method is obtained as y = −0.5775x + 2.7554. Therefore, the width direction correlation coefficient k _CD is −0.5
775. As described above, in the sample C having no streaks as the nonwoven fabric, k _MD and k _CD fluctuate in the order of three decimal places around k _M , and the fluctuation is extremely small.

Note that the ratio Q _CD of the width direction correlation coefficient k _{CD to} the main correlation coefficient k _M is Q _CD = 1.00697. Also, the ratio Q _MD of the production direction correlation coefficient k _{MD to} the main correlation coefficient k _M is Q _MD = 0.9932.

FIG. 13 shows the measurement result group coordinates obtained as a result of calculation when the logarithm of the image size for sample D is x-coordinate and the main variation coefficient / width-direction variation coefficient / production-direction variation coefficient is y-coordinate. Is a graph in which is plotted.

The main measurement result group coordinates of sample D (open circles in the figure)
) Is regressed to a linear line by the least squares method.
The equation of the straight line L1 is obtained as y = −0.3772x + 2.139. Therefore, the main correlation coefficient k_MIs -0.377
2 is required. In addition, the production direction measurement result group coordinates (in the figure,
(Represented by white squares) was regressed to a linear line using the least squares method.
The equation of the straight line L2 in this case is obtained as y = −0.4054x + 2.096. Therefore, the production direction correlation coefficient k_MDIs -0.
4054. Also, the width direction measurement result group coordinates
(Indicated by white triangles in the figure) to a linear line by the least squares method.
The equation of the straight line L3 when it is returned is obtained as y = −0.349x + 2.1821. Therefore, the width direction correlation coefficient k_CDIs -0.3
49 is required. Thus, the production direction as non-woven fabric
In sample D, which has a streak,_MDAnd k_CDIs k _MIn
It fluctuates in the order of the second decimal place as a heart,
The variation is larger than that of the sample C having no streak. Soshi
And the production direction correlation coefficient k_MDIs the main correlation coefficient k_M
Is larger than the absolute value of
Number k_CDIs the main correlation coefficient k_MSmaller than the absolute value of
It's getting cheaper.

The ratio Q _CD of the width direction correlation coefficient k _{CD to} the main correlation coefficient k _M is Q _CD = 0.9252. Further, the ratio Q _MD of the production direction correlation coefficient k _{MD to} the main correlation coefficient k _M is Q _MD = 1.0748.

The ratio Q of the sample D_CDOr Q_MDThe value of
Ratio Q of sample C_CDOr Q_MDOne greater than the value of
Is fluctuating. Therefore, based on sample C
Then, it can be determined that the sample D has a streak.
Wear. Also, the ratio Q_CDOr Q _MDBy observing the value of
For example, it is possible to evaluate the condition of muscles based on rules of thumb
Become.

[0095] In this manner, by calculating the ratio Q _CD or Q _MD of the main correlation coefficient k _M in the width direction correlation coefficient k _CD or production direction correlation coefficient k _{M D,} streaks sheet is You can evaluate whether there is, and the condition of the muscle.

[0096]

According to the present invention, a state evaluation method and a state evaluation apparatus capable of quantifying the state of an object to be measured can be obtained by expressing the state evaluation of the object to be measured as specific numerical values. . Therefore, a more objective index can be obtained as compared to the subjective evaluation by visual observation, and the state evaluation of a large number of objects to be measured can be performed with high reliability using the electronic device.

[Brief description of the drawings]

FIG. 1 is a perspective view schematically showing a configuration of a device for evaluating a state of an object to be measured according to first and second embodiments of the present invention.

FIG. 2 is a block diagram schematically illustrating a configuration of a calculation unit of the computer.

FIG. 3 is a flowchart illustrating a data processing procedure when evaluating formation in the first embodiment.

FIG. 4A is an explanatory diagram illustrating a division example in which a predetermined area is equally divided into four sections. FIG. 4B is an explanatory diagram showing a division example in which a predetermined area is equally divided into nine sections.

FIG. 5 is a flowchart showing a data processing procedure when evaluating formation in the second embodiment.

FIG. 6 shows a width direction variation coefficient when a predetermined area is equally divided into nine sections to obtain a luminance value group in the second embodiment.
It is an explanatory view for explaining how to calculate a production direction variation coefficient and a main variation coefficient.

FIG. 7 is a photograph showing an image of the state of sample A in Example 1.

FIG. 8 is a photograph showing an image of a state of sample B in Example 1.

FIG. 9 is a graph in which the main measurement result group coordinates (Log _{a Sn} , CV _n ) of both samples obtained by the arithmetic processing in Example 1 are plotted.

FIG. 10 is a photograph showing an image of a state of sample C in Example 2.

11 is a photograph showing an image of the state of sample D in Example 2. FIG.

[12] The main measurement result group coordinates of sample C obtained by processing in Example _{2 (Log a S n, CV} n), the width direction measurement unit coordinates _{(Log a S n, CV CDn} ) and production direction measurement unit coordinates are _{(Log a S n, CV MDn} ) graph plotting.

[13] The main measurement result group coordinates of sample D obtained by processing in Example _{2 (Log a S n, CV} n), the width direction measurement unit coordinates _{(Log a S n, CV CDn} ) and production direction measurement unit coordinates are _{(Log a S n, CV MDn} ) graph plotting.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 ... Evaluation apparatus of a to-be-measured object, 3 ... Sheet-like object, 7 ... Light source, 9 ... CCD camera, 11 ... Computer, 13 ... Calculation part, 15 ... Display, 17 ... Main variation coefficient calculation part,
19: image size changing unit, 21: main correlation coefficient calculating unit, 2
3. Ratio operation unit, 25 storage unit.

Claims (18)

[Claims] A step of irradiating a predetermined region of the device under test with light and receiving reflected light or transmitted light from the predetermined region to obtain luminance information; and obtaining a predetermined image of the predetermined region of the device under test. Dividing by size, calculating a luminance value of each divided section based on the luminance information, and calculating a main variation coefficient corresponding to the predetermined image size based on the luminance value of each section; Repeating the calculation of the main variation coefficient while changing the size of the predetermined image size; and a correlation between the image size and the main variation coefficient based on the plurality of image sizes and the plurality of main variation coefficients. Calculating a main correlation coefficient indicating the state of the DUT. 2. In the step of calculating the main variation coefficient, a brightness average and a standard deviation of the entire predetermined area are calculated based on the brightness value of each section, and a main variation is calculated based on the brightness average and the standard deviation. The method according to claim 1, wherein the coefficient is calculated. 3. The step of calculating the main variation coefficient includes calculating first and second variation coefficients in first and second directions intersecting each other with respect to the predetermined area based on a luminance value of each section, The method according to claim 1, wherein the main coefficient of variation is calculated based on the first and second coefficient of variation. 4. A plurality of said image sizes and a plurality of said first images.
The state evaluation of the device under test according to claim 3, further comprising a step of calculating a first correlation coefficient indicating a correlation between the image size and the first variation coefficient based on the variation coefficient. Method. 5. The method according to claim 1, wherein the main correlation coefficient is obtained as a slope when a main measurement result group coordinate obtained based on a plurality of logarithms of the image size and the plurality of main variation coefficients is regressed to a linear line. The method for evaluating the state of an object to be measured according to any one of claims 1 to 4, characterized in that: 6. The method according to claim 5, wherein the regression to the linear line is performed by a least square method. 7. The method according to claim 1, further comprising a step of calculating a ratio between the main correlation coefficient and a previously obtained main correlation coefficient for another device under test. 3. The method for evaluating a state of an object to be measured according to item 1. 8. The object according to claim 1, wherein the luminance information includes luminance information for each light component obtained by dispersing the reflected light or the transmitted light into a plurality of light components. Method for evaluating the state of the measured object. 9. The method for evaluating the state of an object according to claim 1, wherein the object to be measured is a sheet-like object made of fibers. 10. A light source for irradiating light to an object to be measured, and a light receiving unit for receiving reflected light or transmitted light reflected or transmitted in a predetermined region of the object to obtain luminance information. Dividing the predetermined area of the device under test by a predetermined image size, calculating a luminance value of each divided section based on the luminance information, and calculating the predetermined image size based on the luminance value of each section. A first calculating means for calculating a main variation coefficient corresponding to, and a changing means for changing the size of the predetermined image size, based on a plurality of the image sizes and a plurality of the main variation coefficients, And a second calculating means for calculating a main correlation coefficient indicating a correlation between the image size and the main variation coefficient. 11. The first calculating means calculates a luminance average and a standard deviation of the entire predetermined area based on the luminance value of each section, and calculates a main variation coefficient based on the luminance average and the standard deviation. The apparatus for evaluating the state of a device under test according to claim 10, wherein the state is calculated. 12. The first calculating means calculates first and second variation coefficients in first and second directions intersecting each other for the predetermined area based on the luminance value of each section, and The device for evaluating the state of a device under test according to claim 10, wherein a main variation coefficient is calculated based on the second variation coefficient. 13. A third calculating means for calculating a first correlation coefficient indicating a correlation between an image size and a first variation coefficient based on the plurality of image sizes and the plurality of first variation coefficients. The apparatus for evaluating a state of a device under test according to claim 12, further comprising: 14. The main correlation coefficient is obtained as a gradient when a main measurement result group coordinate obtained based on a plurality of logarithms of the image size and a plurality of the main variation coefficients is regressed to a linear line, The device for evaluating a state of an object to be measured according to any one of claims 10 to 13, characterized in that: 15. The apparatus according to claim 14, wherein the regression to the linear line is performed by a least square method. 16. The apparatus according to claim 10, further comprising: fourth calculating means for calculating a ratio between the main correlation coefficient and a previously obtained main correlation coefficient for another device under test. ~
15. The device for evaluating a state of an object to be measured according to any one of 15. 17. The object according to claim 10, wherein the luminance information includes luminance information for each light component obtained by dispersing the reflected light or the transmitted light into a plurality of light components. A device for evaluating the state of a measured object. 18. The device for evaluating the state of an object to be measured according to claim 10, wherein the object to be measured is a sheet-like object made of fibers.