JP2019020580A - Microscope data processing unit, microscope system and microscope data processing program - Google Patents

Abstract

A microscope data processing apparatus capable of easily measuring the vacancy state of a sample is provided.
A control / processing device as a microscope data processing device includes a sample surface height data acquisition unit 300 that generates and acquires a group of sample surface height data based on sample surface image data output from a laser microscope. A hole data extraction unit 302 for extracting the sample surface height data of the hole region from the group of sample surface height data, and the number of data of the group of sample surface height data and the sample surface height data of the hole region A void ratio calculation unit 303 that calculates a void state in the sample based on the number of data.
[Selection] Figure 2

Description

  The present invention relates to a microscope data processing apparatus, a microscope system, and a microscope data processing program.

  CFRP (carbon fiber reinforced plastic) is used in various product structures. One of the CFRP molding methods is a press molding method, which is characterized by a relatively fast molding cycle and mass production. Structural microscopic parameters in the quality evaluation of thermoplastic CFRP samples produced by the press molding method include cracks (resin cracks), voids (cavities), and carbon fiber distribution. The Archimedes method is known as one of the methods for evaluating the porosity, which is the ratio of cracks and voids in the sample (hereinafter collectively referred to as vacancies) (for example, patent literature). 1).

Japanese Patent Laying-Open No. 2015-187296

  The Archimedes method is a method that uses the Archimedes principle, and measures the porosity from the weight in water, saturated water, and dry weight of a sample. For this reason, there is a problem that the measurement takes time and the saturated water weight is likely to fluctuate depending on how the water is wiped off when the sample is taken out of the water, thereby causing a measurement error.

A microscope data processing apparatus according to a preferred embodiment of the present invention includes an acquisition unit that generates and acquires a group of sample surface height data based on sample surface image data output from a laser microscope, and the group of sample surface height data. An extraction unit for extracting the sample surface height data of the pore region, and the number of data of the group of sample surface height data and the number of data of the sample surface height data of the pore region A computing unit that calculates a state.
In a further preferred aspect, the apparatus further comprises a filter processing unit that removes the influence of the waviness of the sample surface from the group of sample surface height data, and the extraction unit is configured to filter the group of sample surface heights filtered by the filter processing unit. The sample surface height data of the pore region is extracted from the height data.
In a further preferred aspect, the filter processing unit passes a lower wavelength region than the lower limit of the undulation wavelength to be removed with respect to the sample surface height data in an arbitrary cross section of the group of sample surface height data. Filter by filter.
In a further preferred aspect, the calculation unit calculates the porosity based on the number of data of the group of sample surface height data and the number of data of the sample surface height data of the pore region as the vacancy state. To do.
In a further preferred aspect, the calculation unit calculates a hole distribution in the sample based on the number of sample surface height data in the hole region as the hole state.
The microscope system by the preferable aspect of this invention is equipped with the laser microscope which outputs sample surface image data, and the microscope data processing apparatus as described in any one of the aspect mentioned above.
A microscope data processing program according to a preferred embodiment of the present invention generates and acquires a group of sample surface height data on a computer based on sample surface image data output from a laser microscope, and the group of sample surface heights. The sample surface height data of the void region is extracted from the data, and the number of data of the group of sample surface height data and the number of data of the sample surface height data of the void region are determined. And calculating a hole state.

  According to the present invention, the vacancy state of a sample can be easily measured.

FIG. 1 is a block diagram showing the configuration of the laser microscope apparatus. FIG. 2 is a functional block diagram of the CPU. FIG. 3 is a diagram showing the relationship between the height of the sample surface and the photodetector output. FIG. 4 is a schematic view showing a part of a cross section (polished surface) of a thermoplastic CFRP sample produced by a press molding method. FIG. 5 is a histogram of unevenness height data. FIG. 6 is a flowchart showing a processing procedure for calculating the porosity. FIG. 7 is a diagram illustrating an example of a monitor image. FIG. 8 is a diagram for explaining the second modification. FIG. 9 is a diagram showing a display screen for manual threshold setting. FIG. 10 is a diagram for explaining the porosity of the entire sample. FIG. 11 is a diagram showing a cross-sectional curve, a waviness curve, and a roughness curve. FIG. 12 is a diagram illustrating filter characteristics. FIG. 13 is a flowchart illustrating a processing procedure of porosity calculation in the second embodiment.

Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings.
-First embodiment-
FIG. 1 is a block diagram illustrating a configuration of a microscope system including a scanning confocal laser microscope. The laser microscope system 1 includes a scanning confocal laser microscope (hereinafter referred to as a laser microscope) 2, a control / processing device 3, a monitor 4, an input operation unit 5, and a recording medium reading device 6.

  The laser microscope 2 includes a laser light source 18, a mirror 7, a dichroic mirror 8, a two-dimensional scanning unit 9, a revolver 10, an objective lens 11, a stage 12 on which a sample S is placed, a lens 13, a pinhole plate 14, and an amplification unit 15. The z-axis movement control unit 16 and the photodetector 17 are provided.

  The laser light source 18 generates laser light 19 as spot light that scans the surface of the sample S. Laser light 19 from the laser light source 18 is reflected by the mirror 7 and guided to the two-dimensional scanning unit 9 through the dichroic mirror 8. As shown in FIG. 1, when the x-axis is defined in the right direction on the paper surface, the y-axis is defined in the back surface direction of the paper surface, and the z-axis is defined in the upward direction on the paper surface, the two-dimensional scanning unit 9 is based on a control signal from the control / processing device 3. Then, the laser beam 19 from the laser light source 18 reflected by the mirror 7 is two-dimensionally scanned on the sample S. For example, the two-dimensional scanning unit 9 includes a galvanometer mirror for scanning in the x-axis direction and a galvanometer mirror for scanning in the y-axis direction, and swings these galvanometer mirrors in the x-axis direction and the y-axis direction so as to The optical path of the spot light is scanned in the x direction and the y direction.

  The revolver 10 holds a plurality of objective lenses 11 having different magnifications. By switching the revolver 10, the objective lens 11 having a desired magnification among the plurality of objective lenses 11 can be selectively inserted into the observation optical path. The spot light that is two-dimensionally scanned by the two-dimensional scanning unit 9 is applied to the sample S on the stage 12 through the objective lens 11. The stage 12 can be moved in the optical axis direction (z direction) by the z-axis movement control unit 16.

  The reflected light from the sample S returns to the two-dimensional scanning unit 9 through the objective lens 11, returns to the dichroic mirror 8 through the two-dimensional scanning unit 9, and is reflected by the dichroic mirror 8 toward the lens 13.

  The optical system of the laser microscope 2 is a confocal optical system, and irradiates light emitted from a laser light source 18 that is a point light source so as to be focused on one point of the sample S by an objective lens. In the confocal optical system, a pinhole plate 14 having a circular opening (pinhole) is disposed at a position (image position) conjugate with the focal position of the objective lens 11. The reflected light 20 from the sample S is collected on the pinhole. In the confocal optical system, most of the reflected light from other than the focal point is cut by the pinhole plate 14, and only the light from the focal position is detected by the photodetector 17.

  The photodetector 17 converts the light obtained through the pinhole of the pinhole plate 14 into an electric signal corresponding to the amount of light. The electrical signal obtained by the photodetector 17 is amplified by the amplification unit 15 and then output to the control / processing device 3 as image information.

  The control / processing device 3 includes a CPU 30 and a memory 32. The CPU 30 controls the laser microscope 2 and performs various processes based on image information input from the laser microscope 2. The CPU 30 controls the laser microscope 2 according to a control program stored in the ROM 31 or the memory 32. For example, the two-dimensional image information is generated from the electrical signal photoelectrically converted by the photodetector 17 and the scanning timing signal from the two-dimensional scanning unit 9 and transferred to the memory 32, and an image based on the two-dimensional image information is displayed. A surface image of the sample S is displayed on the monitor 4.

  Further, the CPU 30 executes various image information processing based on image information obtained from the laser microscope 2 by executing an image information processing program stored in the ROM 31 or the memory 32, for example, porosity calculation processing described later. I do. For example, when the image information processing program is stored in the memory 32, the image information processing program is provided via a recording medium such as a CD-ROM, and the CPU 30 records the program recorded on the recording medium. It is read by the medium reader 6 and stored in the memory 32.

  The input operation unit 5 includes a pointing device such as a mouse in addition to the keyboard, and can input various instructions and parameters to the control / processing device 3 by a user operation. The input parameters are stored in the memory 32.

  In the example shown in FIG. 1, the converging position on the sample S is changed by moving the stage 12 in the optical axis direction (up and down), but the revolver 10 is moved in the optical axis direction. It may be a simple configuration.

  FIG. 2 is a functional block diagram for explaining the porosity calculation processing executed by the CPU 30. Here, a case where the porosity of a CFRP sample is calculated will be described as an example. FIG. 4 schematically shows a part of a cross section (polished surface) of a thermoplastic CFRP sample produced by a press molding method. In the example shown in FIG. 4, the direction of the carbon fiber 100 is the y direction in the a layer and the c layer, and the direction of the carbon fiber 100 is the z direction in the b layer and the d layer. In the CFRP sample, the 0 ° layer and the 90 ° layer are alternately laminated in this way. Structural elements that affect the mechanical strength of CFRP include cracks 102, pores 103, and distribution of carbon fibers 100 in the portion of resin 101 filled between carbon fibers 100.

  In the present embodiment, based on the image information acquired by the laser microscope 2, the holes 103 in the region of the CFRP sample that is perpendicular to the fiber direction, that is, in the cross section of the b layer and the d layer in FIG. The porosity, which is the ratio of the cracks 102, is calculated.

(Sample surface height data acquisition unit 300)
The sample surface height data acquisition unit 300 in FIG. 2 controls the laser microscope 2 to acquire sample surface height data that is the height data of the surface of the sample S. Hereinafter, the sample surface height data is simply referred to as height data. As described above, the focusing position of the objective lens 11 is at a position conjugate with the pinhole of the pinhole plate 14. Therefore, when the surface of the sample S is at the condensing position of the objective lens 11, the reflected light from the sample surface is condensed on the pinhole plate 14 and passes through the pinhole. On the other hand, when the sample surface is shifted up and down (in the optical axis direction) from the focusing position of the objective lens 11, the reflected light from the sample S is not condensed on the pinhole plate 14, but passes through the pinhole. The amount of light to be reduced is significantly reduced. FIG. 3 is a diagram showing the relationship between the height of the sample surface and the output of the photodetector 17. When the sample surface is at the condensing position of the objective lens 11, the output of the photodetector 17 becomes maximum, and as the sample surface moves away from the condensing position of the objective lens 11, the output of the photodetector 17 rapidly decreases. .

  With such characteristics, if the two-dimensional scanning unit 9 two-dimensionally scans the focal point in the x and y directions and images the output of the photodetector 17 in synchronization with the scanning of the two-dimensional scanning unit 9, Only a certain height of the surface is imaged, and an image (confocal image) obtained by optically slicing the sample S (slicing in a plane perpendicular to the optical axis) is obtained. Further, the stage 12 is moved discretely in the optical axis direction, the two-dimensional scanning unit 9 is scanned at each discrete position to acquire a confocal image, and the output of the photodetector 17 is output at each point on the sample surface. By measuring the maximum stage position, the height information of the sample surface can be obtained. Further, by displaying the maximum value of the output of the photodetector 17 at each point on the sample surface in an overlapping manner, it is possible to obtain an image (extended image) in which all surfaces are in focus.

  The sample surface height data acquisition unit 300 performs the above-described control on the laser microscope 2 to obtain image data regarding a predetermined region (hereinafter referred to as a measurement region) of the sample S. And stored in the memory 32 (see FIG. 1). The measurement area is set in advance by the user operating the input operation unit 5 and stored in the memory 32. Then, the sample surface height data acquisition unit 300 generates a group of height data related to the height of the sample surface from the acquired image data.

(Threshold setting unit 301)
The threshold setting unit 301 sets a threshold for determining whether or not the acquired height data is the height data of the hole region (the region of the crack 102 or the hole 103). Various threshold value setting methods are conceivable. Here, a case will be described in which the threshold value is automatically set based on the acquired height data. Even when the crack 102 and the void 103 are not formed in the cross sections of the b layer and the d layer in FIG. 4, the cross section has minute unevenness, and the histogram of the unevenness height data is as shown in FIG. Normal distribution. In FIG. 5, the vertical axis represents the number of data, and the horizontal axis represents the deviation from the average value. On the other hand, since the height of the hole area is lower than the surface of the sample, the height data of the hole area is an area where the standard deviation in the normal distribution is greatly deviated at least in the minus direction (herein referred to as the hole data area). Is considered to be included in the data. For example, the area on the left side of the deviation −2σ indicated by the symbol A in FIG. 5 can be set as the hole data area. By setting −2σ as a threshold value in this way, height data that hardly includes height data of the uneven portion of the cross section (polished surface) is extracted as hole height data. Here, −2σ is set as the threshold, but the threshold is not limited to this.

  In addition to the method of setting the threshold value based on the distribution of height data in this way, for example, for a plurality of samples, a threshold value that matches the porosity measured by the Archimedes method is obtained, and the value is obtained as pore data. The threshold value for extraction may be set in advance. In that case, the threshold value is automatically selected by the threshold value setting unit 301.

(Hole Data Extraction Unit 302)
The hole data extraction unit 302 obtains height data having a height lower than the threshold set by the threshold setting unit 301 from the data group of the height data acquired by the sample surface height data acquisition unit 300. Are extracted as height data (hereinafter referred to as hole data). The number of data of the hole portion data is used as the number of data in the entire measurement region for obtaining the porosity of the entire measurement region. The hole data extraction unit 302 also obtains the number of data for each partial area when the measurement area is divided into a plurality of partial areas, in addition to the number of data in the entire measurement area. The number of data for each partial region is used to represent the distribution of holes.

(Hole state calculator 303)
The hole state calculation unit 303 extracts the number of height data in the entire measurement region acquired by the sample surface height data acquisition unit 300 (herein referred to as the total number of data) and the hole data extraction unit 302. The porosity (%) is calculated as shown in the following equation (1) from the number of data of the hole portion data in the entire measurement region. Here, the number of data of the hole portion data corresponds to the cross-sectional area of the hole portion, and the total number of data of the height data corresponds to the cross-sectional area of the measurement region.
(Porosity) = {(Number of data of hole portion data) / (Total number of data)} × 100 (1)

  In addition, the hole state calculation unit 303 calculates the distribution of holes based on the number of data for each partial region described above. As a method of expressing the distribution of vacancies, as shown in the distribution diagram of FIG. 7 to be described later, the number of vacancy data in each partial area may be indicated, or the porosity of each partial area may be indicated respectively. You may make it show. For the porosity of each partial area, replace (number of data of hole data) and (total number of data) in equation (1) with (number of data of hole data) and (total number of data) in the partial area. Is calculated by

(Monitor image generation unit 304)
The monitor image generation unit 304 generates a monitor image for displaying the porosity calculation result on the monitor 4. The operator can confirm the porosity calculation result by looking at the monitor image displayed on the monitor 4. FIG. 7 shows an example of a monitor image. The image shown on the upper right side of the screen shows a grayscale image representing the surface of the observation region C in FIG.

  For example, in the histogram shown in FIG. 5, when the height data of −2σ or less is expressed in black, the height data of −2σ to 1σ is expressed in gray, and the height data of 1σ or more is expressed in white, black (B), gray ( A sample surface image of a grayscale image (reflection luminance image) represented by the hatched area G) and white (W) is obtained. In the observation area C of FIG. 4, the grayscale image of FIG. 7 includes the height data of the carbon fiber 100 portion included in the height data of 1σ or higher, and the height data of the resin 101 portion of −2σ to 1σ high. It is schematically shown that the height data of the crack 102 and the hole 103 is included in the height data of 1σ or more.

  Further, the image shown on the upper left side of the screen in FIG. 7 represents the hole distribution, and represents the distribution of the hole data in the observation region C by numbers. Here, the observation area C is divided into 8 × 16 = 104 partial areas, and the number of holes in the divided areas is displayed. Thereby, it is possible to visually and quantitatively recognize the distribution of holes in the cross section of the sample. As described above, the porosity of each partial region may be indicated instead of indicating the number of data of the hole portion data.

  Furthermore, the table at the bottom of the screen displays the porosity based on the data of the entire observation region C as a percentage.

  FIG. 6 is a flowchart showing a series of processing procedures relating to porosity calculation executed by the CPU 30. In step S10, the laser microscope 2 is controlled to acquire sample surface height data. In step S20, a threshold setting process in the threshold setting unit 301 is performed. In step S30, using the threshold value set in step S20, the hole area height data (hole part data) is extracted from the acquired height data. In step S40, the monitor image generation unit 304 generates a monitor image indicating the processing result as shown in FIG. 7, and the monitor image is displayed on the monitor 4 in step S50.

(Modification 1)
In the above-described embodiment, the height data of each point on the sample surface is obtained by obtaining the confocal image obtained by optically slicing the sample S by discretely changing the position of the condensing point in the optical axis direction. . On the other hand, in the first modification, height data is obtained based on an image (reflection luminance image) obtained by performing two-dimensional scanning in the xy direction while maintaining the position of the condensing point in the optical axis direction constant.

  As shown in FIG. 3, when the position of the condensing point in the optical axis direction is kept constant, the output of the photodetector 17 varies depending on the height of the sample surface. The output value is the largest when the sample surface height matches the light collection position, and the output value decreases as the relative position between the sample surface and the light collection position increases. Therefore, if the light condensing position is matched with the highest position on the sample surface (for example, the cross-sectional position of the carbon fiber 100 in the case of the d layer in FIG. 4), the output value decreases as the height decreases. Therefore, height data can be obtained by associating the output value with the height.

  That is, height data similar to that in the above-described embodiment can be obtained based on the magnitude of the output value of the photodetector 17. The sample surface height data acquisition unit 300 shown in FIG. 2 generates sample surface height data from the output value of the photodetector 17 and the height-output correlation shown in FIG. The subsequent processing is the same as in the above-described embodiment.

  Also in the case of the first modification, in the histogram illustrated in FIG. 5, when the height data of −2σ or less is expressed in black, the height data of −2σ to 1σ is expressed in gray, and the height data of 1σ or more is expressed in white, black ( The grayscale image (reflection luminance image) represented by B), gray (G), and white (W) is the same as the grayscale image shown in FIG.

(Modification 2)
FIG. 8 is a flowchart for explaining a second modification of the above-described embodiment, and is a flowchart showing a processing procedure of porosity calculation executed by the CPU 30. In the porosity calculation processing shown in FIG. 6, the threshold value is automatically set. In the second modification, the operator can select automatic setting or manual setting for the threshold setting. In FIG. 8, steps S100 to S120 are processes newly added to FIG. 6, and other steps are the same as those shown in FIG.

  If the laser microscope 2 is controlled in step S10 to obtain the sample surface height data, then the process of step S100 is executed. In step S100, a display screen for selecting automatic setting or manual setting is displayed on the monitor 4, and an input operation by the operator is awaited. When the operator operates the input operation unit 5 (see FIG. 1) and selects automatic setting, it is determined in step S110 that the automatic setting is selected, and the process proceeds to step S20, and a series of steps from step S20 to step S60 is performed. Processing is executed.

  On the other hand, when the manual setting is selected by the operator, the process proceeds from step S110 to step S120, and the manual setting process is performed. As an example of the manual setting process, for example, a display screen for manual setting as shown in FIG. 9 is displayed on the monitor 4 to prompt the operator to input. A screen 40 for selecting the type of sample is displayed on the left side of the screen, and a screen 41 for inputting a threshold value (corresponding to the hole depth) is displayed on the right side of the screen.

  Representative sample names are displayed on the samples # 1 to # 8 on the screen 40, and when these are selected, a threshold corresponding to the sample name is set. This threshold value represents a deviation in the minus direction from the average value of the height data. The value of the standard deviation σ of the normal distribution shown in FIG. 5 varies depending on the type of sample, and the threshold value is set smaller for a sample with a smaller standard deviation σ, that is, for a sample with less unevenness in a non-hole portion. On the other hand, when the unevenness is relatively large, the threshold is set larger so that the unevenness on the surface is not erroneously determined as a hole.

  If the operator has knowledge about the unevenness of the sample, a threshold value based on the knowledge may be manually input on the screen 41.

  When the manual setting process in step S120 ends, the process proceeds to step S30. In step S30, the hole area height data based on the threshold value set by the manual setting process is extracted. Subsequent processing is the same as in the case of automatic setting, and description thereof is omitted.

  By the way, in the above-described calculation of the porosity, the calculation is performed as shown in Expression (1) based on the microscopic image of the surface (polishing surface) of the sample S. In this case, the porosity is calculated by dividing the porosity region. It represents the area ratio between the area and the cross-sectional area of the measurement region. Here, the relationship between the porosity obtained as the area ratio and the porosity for the entire sample will be described by taking a rectangular parallelepiped sample as shown in FIG. 10 as an example.

(About the porosity of the entire sample)
In FIG. 10, a rectangular parallelepiped sample is divided into four partial regions from the first region to the fourth region in the z direction, and the porosity is considered. For the sake of simplicity, it is assumed that the first region has a structure in which rectangular parallelepiped material portions (hatched portions) and hole portions (outlined portions) are alternately arranged. In this case, in any cross section parallel to the xy plane in the first region, the porosity represented by the area ratio is 50%. Also, the porosity of the entire first region is 50%, which is the same as the porosity represented by the area ratio.

  In any region from the second region to the fourth region, the rectangular parallelepiped material portion and the void portion are arranged in the same manner as the first region, and the porosity of the entire region of the second to fourth regions. It is assumed that the material part and the hole part are provided so that the order is 30%, 20%, and 40%. Therefore, in any of the second to fourth regions, the porosity expressed by the area ratio in the cross section parallel to the xy plane is the same as the porosity of the entire region of each region. That is, the porosity in the xy cross section of the second region is 30%, the porosity in the xy cross section of the third region is 20%, and the porosity in the xy cross section of the fourth region is 40%.

  The total porosity of the rectangular parallelepiped sample is represented by an average value from the first region to the fourth region, and is (50 + 30 + 20 + 40) / 4 = 35%. On the other hand, the average porosity in the xy section from the first region to the fourth region is also 35%. That is, in the case of the structure as shown in FIG. 10, the average porosity in the xy cross section from the first region to the fourth region is the same value as the porosity of the entire sample.

  In an actual sample, the porosity in the xy cross section in each region often differs depending on the position of the region in the z direction. In that case, the average of the porosity in the xy cross section does not completely match the porosity of the entire sample, but it can be considered to be almost the same. That is, the porosity of the entire sample can be obtained by taking the average value of the porosity calculated for a plurality of cross sections.

  For example, in the case of a CFRP sample as shown in FIG. 4, the overall porosity of the b layer and the d layer can be calculated by taking the average of the porosity of a plurality of cross sections in the z direction. The average porosity of the a layer and the c layer can be calculated by taking the average of the porosity. Furthermore, the porosity of the whole sample shown in FIG. 4 can be calculated by taking the average of the porosity of the a layer, b layer, c layer, and d layer.

  Regarding the distribution of holes, the distribution diagram shown in FIG. 7 shows the distribution of holes in one cross section, but the distribution of holes in a three-dimensional sample can be recognized by showing each distribution of a plurality of cross sections. can do.

-Second Embodiment-
In the second embodiment, a porosity calculation process that takes into account the undulation of the sample surface (polishing surface) that is the sample observation region will be described. 11 and 12 are diagrams for explaining the concept of undulation removal. FIG. 11A is a diagram showing a cross-sectional curve L1 in the y direction of the observation region C in FIG. 4, for example. The cross-sectional curve L1 includes the undulation of the sample surface caused by vibration between the tool and the workpiece. FIG. 11B is a diagram showing a waviness curve L2 representing a waviness component included in the cross-sectional curve L1. The cross-sectional curve L1 is also indicated by a broken line. Further, FIG. 11C shows a roughness curve L3. The roughness curve L3 is a curve after removing the undulation component represented by the undulation curve L2 from the cross-sectional curve L1. The surface shape indicated by the roughness curve L3 is generated by a trace of cutting by a tool or an impression of grinding / polishing.

  As described above, the height data of the sample surface acquired by the detection information of the laser microscope 2 includes not only the depth due to the holes but also the swell component of FIG. 11B and the roughness component of FIG. 11C. include. Therefore, as for the height data of the portion where the sample surface is depressed by the undulation as in the region D of FIG. 11B, the detected height is lowered by the amount of depression, and may be erroneously determined as a hole. There is. Therefore, in order to accurately extract the height data of the hole region, it is necessary to remove the undulation component that gradually changes greatly like the undulation curve L2 from the height data.

  In order to extract the waviness curve L2 from the cross-sectional curve L1, the height data is filtered with a waviness extraction filter having the characteristics shown by the curve L10 in FIG. The horizontal axis in FIG. 12 represents the wavelength, and the vertical axis represents the amplitude transmission rate. As the waviness extraction filter, a band pass filter having a pass band from the cutoff value λc to the cutoff value λf is used. The cut-off value λc is set to about 0.25 mm to 2.5 mm, for example, and the cut-off value λf is set to about 8 mm to 12.5 mm, for example. That is, a case where the uneven state of the sample surface changes in a wavelength range from the cutoff value λc to the cutoff value λf is called undulation.

  Further, in order to extract the roughness curve L3 from the cross-sectional curve L1, the height data is filtered with a roughness extraction filter having characteristics as shown by the curve L11 in FIG. A high-pass filter having a cutoff value λc is used as the roughness extraction filter. In addition, the cross-sectional curve L1 shown to Fig.11 (a) represents the shape after removing the uneven | corrugated shape below several micrometers called microroughness. In order to remove the microroughness, a low-pass filter having a cutoff value λs (for example, about λs = 2.5 μm to 8 μm) is used. Therefore, in FIG. 12, the curve L11 is described as a band pass filter having a pass band from the cutoff value λs to the cutoff value λc.

  Since the observation region C in FIG. 4 is a two-dimensional region in the x direction and the y direction, the data string arranged in the x direction is filtered by the roughness extraction filter, and the roughness extraction filter is filtered in the data string arranged in the y direction. Will be filtered. Since there are a plurality of data strings arranged in the x direction in the y direction and a plurality of data strings arranged in the y direction in the x direction, filtering is performed on each of the plurality of data strings. Such filtering for the height data is performed by the sample surface height data acquisition unit 300 of FIG.

  FIG. 13 is a flowchart illustrating a processing procedure of porosity calculation executed by the CPU 30 in the second embodiment. The flowchart of FIG. 13 is obtained by adding the process of step S200 to the flowchart of FIG. 6, and the processes of other steps are the same as those in FIG.

  In step S10, as described in the first embodiment, the laser microscope 2 is controlled to obtain the height data of the sample surface. In step S200, in order to remove the waviness component from the height data and obtain the roughness component height data as shown in FIG. Note that a band pass filter having characteristics as shown by a curve L11 in FIG. 12 may be used. The sample surface height data acquisition unit 300 shown in FIG. 2 performs such filtering to generate height data in which the swell component is removed from the acquired height data. Since the processing from step S20 to step S60 is the same as that described in the first embodiment, description thereof is omitted here.

According to the embodiment and the modification described above, the following operational effects can be obtained.
(C1) The control / processing device 3 as a microscope data processing device is a group of sample surface heights based on sample surface image data (for example, a plurality of confocal images or one reflection luminance image) output from the laser microscope 2. Sample surface height data acquisition unit 300 for generating and acquiring height data, and the sample surface height in the void region (for example, the region of the crack 102 and the hole 103 in FIG. 4) from the group of sample surface height data A hole data extraction unit 302 that extracts data, and a hole that calculates a hole state in a sample based on the number of data of a group of sample surface height data and the number of data of sample surface height data of a hole region A state calculation unit 303. As a result, the vacancy state of the sample can be easily measured based on the sample surface image data output from the laser microscope 2.

  Note that the calculated vacancy state includes a porosity calculated based on the number of data of the group surface height data and the number of data of the sample surface height data of the vacancy region, and the group of sample surfaces. There is a hole distribution in the sample calculated based on the number of data of the height data and the number of data of the sample surface height data of the hole region. As a result, the porosity and hole distribution can be easily obtained. Moreover, the distribution of vacancies, which cannot be evaluated by the conventional Archimedes method, can be calculated.

  (C2) In addition, the sample surface height data acquisition unit 300 performs a filtering process to remove the influence of the undulation of the sample surface from the group of sample surface height data, so that the hole data extraction unit 302 as a filter processing unit is performed. The sample surface height data of the hole area extracted in step (2) does not include the influence of waviness, and the hole state in the sample can be calculated with higher accuracy. For example, the hole data extraction unit 302 uses the lower limit of the undulation wavelength to be removed (cut-off value λc in FIG. 12) for the sample surface height data in an arbitrary cross section of the group of sample surface height data. Is also filtered by a filter that passes through a low wavelength region.

  Although various embodiments and modifications have been described above, the present invention is not limited to these contents. Other embodiments conceivable within the scope of the technical idea of the present invention are also included in the scope of the present invention. In the above-described embodiment, the case where the sample is CFRP has been described as an example. However, the calculation of the porosity and the hole distribution described above can be applied to samples other than CFRP.

  DESCRIPTION OF SYMBOLS 1 ... Laser microscope system, 2 ... Laser microscope, 3 ... Control and processing apparatus, 102 ... Crack, 103 ... Hole, 300 ... Sample surface height data acquisition part, 301 ... Threshold setting part, 302 ... Hole data extraction part , 303: Hole state calculation unit, 304: Monitor image generation unit, S: Sample

Claims (7)

An acquisition unit that generates and acquires a group of sample surface height data based on the sample surface image data output from the laser microscope;
An extraction unit for extracting the sample surface height data of the pore region from the group of sample surface height data;
A microscope data processing apparatus comprising: an arithmetic unit that calculates a hole state in a sample based on the number of data of the group of sample surface height data and the number of data of the sample surface height data of the hole region. In the microscope data processing device according to claim 1,
A filter processing unit for removing the influence of the waviness of the sample surface from the group of sample surface height data;
The microscope data processing apparatus, wherein the extraction unit extracts sample surface height data of the pore region from the group of sample surface height data filtered by the filter processing unit. In the microscope data processing apparatus according to claim 2,
The filter processing unit filters the sample surface height data in an arbitrary cross-section of the group of sample surface height data with a filter that passes a lower wavelength region than the lower limit of the undulation wavelength to be removed. Microscope data processing device. In the microscope data processing device according to any one of claims 1 to 3,
The calculation unit calculates the porosity as the vacancy state based on the number of data of the group of sample surface height data and the number of data of the sample surface height data of the vacancy region. apparatus. In the microscope data processing device according to any one of claims 1 to 3,
The said calculation part is a microscope data processing apparatus which calculates the void | hole distribution in a sample based on the data number of the sample surface height data of the said void | hole area | region as the said void | hole state. A laser microscope that outputs sample surface image data;
A microscope system comprising: the microscope data processing apparatus according to any one of claims 1 to 5. On the computer,
Generating and acquiring a group of sample surface height data based on the sample surface image data output from the laser microscope;
Extracting the sample surface height data of the pore region from the group of sample surface height data;
A microscope data processing program for realizing the calculation of the vacancy state in the sample based on the number of data of the group of sample surface height data and the number of data of the sample surface height data of the vacancy region .

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