WO2022202198A1 - Evaluation method and evaluation device for surface roughening of metal surface - Google Patents

Evaluation method and evaluation device for surface roughening of metal surface Download PDF

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Publication number
WO2022202198A1
WO2022202198A1 PCT/JP2022/009211 JP2022009211W WO2022202198A1 WO 2022202198 A1 WO2022202198 A1 WO 2022202198A1 JP 2022009211 W JP2022009211 W JP 2022009211W WO 2022202198 A1 WO2022202198 A1 WO 2022202198A1
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Prior art keywords
roughening
image data
ndsi
evaluation
light
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PCT/JP2022/009211
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French (fr)
Japanese (ja)
Inventor
紀昭 篠原
右京 樋口
慎剛 中原
和弘 木村
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ジャパンマリンユナイテッド株式会社
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Priority to CN202280024447.5A priority Critical patent/CN117098972A/en
Priority to KR1020237026676A priority patent/KR20230127343A/en
Publication of WO2022202198A1 publication Critical patent/WO2022202198A1/en

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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00Measuring arrangements characterised by the use of optical techniques
    • G01B11/30Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/47Scattering, i.e. diffuse reflection
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84Systems specially adapted for particular applications
    • G01N21/88Investigating the presence of flaws or contamination
    • G01N21/8806Specially adapted optical and illumination features
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84Systems specially adapted for particular applications
    • G01N21/88Investigating the presence of flaws or contamination
    • G01N21/8851Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84Systems specially adapted for particular applications
    • G01N21/88Investigating the presence of flaws or contamination
    • G01N21/8806Specially adapted optical and illumination features
    • G01N2021/8845Multiple wavelengths of illumination or detection
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84Systems specially adapted for particular applications
    • G01N21/88Investigating the presence of flaws or contamination
    • G01N21/8851Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8887Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques

Definitions

  • the present disclosure relates to a method for evaluating surface roughening applied to the surface of metal such as steel, and an evaluation apparatus capable of executing this.
  • Patent Documents 1 and 2 when the techniques described in Patent Documents 1 and 2 are used, even if the surface roughness can be evaluated, the degree of rust removal and cleanliness cannot be evaluated. cannot be substituted.
  • Various other optical techniques and methods have been developed as techniques for evaluating the roughening of metal surfaces, but they all have weaknesses, such as the extremely narrow range that can be evaluated at once. Therefore, it cannot be said that they are practically sufficient as evaluation techniques for surface roughening treatment.
  • the present disclosure relates to acquiring image data of a roughened surface of an object to be inspected, and based on said image data, for light of two preselected wavelengths, the NDSI value at each pixel of said image data and a step of evaluating the roughening of an object to be inspected based on the NDSI value.
  • the wavelength of light used for calculating the NDSI value can be selected based on the following conditions.
  • Condition 1) The magnitude of reflectance is positively correlated with the magnitude of surface roughness.
  • Condition 2) In addition to satisfying condition 1, one of the two wavelengths of reflected light should have as little variation in reflectance as possible due to the surface roughness of the object to be inspected, and the other should have as large a variation as possible.
  • the average value of the NDSI values of the target pixels in the acquired image data is calculated, and the surface roughness is evaluated based on the average value. can.
  • the NDSI value of each target pixel in the acquired image data can be referred to as a preset threshold to evaluate rusting.
  • a range to be evaluated can be selected in the acquired image data, and evaluation of surface roughening can be performed within the selected range.
  • the present disclosure includes an image creation unit that creates image data based on at least the two wavelengths of light selected in advance, and an analysis unit that performs NDSI analysis based on the image data.
  • the present invention relates to an evaluation apparatus for roughening of a metal surface, which is configured to be capable of executing an evaluation method for surface treatment.
  • FIG. 1 is a block diagram showing an example of the configuration of a metal surface roughening evaluation apparatus according to an embodiment of the present disclosure
  • 4 is a graph showing the relationship between the wavelength of light and the reflectance on the surface of a steel material subjected to surface-roughening treatment.
  • 3 is a graph showing each reflectance at each wavelength in FIG. 2 normalized with respect to the reflectance at a specific wavelength
  • 5 is a graph showing an example of the relationship between calculated NDSI values and surface roughness
  • 4 is a flow chart illustrating an example of a procedure of a method for evaluating roughening of a metal surface according to an embodiment of the present disclosure
  • FIG. 1 is a block diagram showing an example of the configuration of a metal surface roughening evaluation apparatus according to an embodiment of the present disclosure
  • 4 is a graph showing the relationship between the wavelength of light and the reflectance on the surface of a steel material subjected to surface-roughening treatment.
  • 3 is a graph showing each reflectance at each wavelength in FIG. 2 normal
  • FIG. 4 is a diagram showing an example of a screen displayed on a display unit in an embodiment of the present disclosure, showing a state in which an image of a measurement target using visible light and a selection range thereof are displayed;
  • FIG. 10 is a diagram showing another example of a screen displayed on the display unit in the embodiment of the present disclosure, showing a state in which an image in which the selection range is color-coded according to the NDSI value is displayed.
  • FIG. 10 is a diagram illustrating another example of a screen displayed on the display unit in the embodiment of the present disclosure, and illustrates a state in which an image in which the selection range is binarized according to the NDSI value is displayed;
  • FIG. 1 shows an example of the configuration of a metal surface roughening evaluation apparatus according to an embodiment of the present disclosure.
  • the evaluation device 1 includes an irradiation unit 2 that irradiates light for inspection, an imaging unit 3 that acquires image data of an object to be inspected, a display unit 4 that displays various visual information, the irradiation unit 2 and the imaging unit 3. , and a display unit 4, and a power supply unit 6 for supplying power to these units.
  • the irradiation unit 2 is, for example, an LED lighting device, and is designed to irradiate the inspection object with light for inspection.
  • the light emitted by the irradiation unit 2 needs to include at least light of wavelengths corresponding to the two wavelengths of reflected light described later.
  • "light of a wavelength corresponding to reflected light of a certain wavelength ( ⁇ nm)” refers to "light of a wavelength that, when the light is incident on an object to be inspected, gives reflected light of a wavelength of ⁇ nm". If the object to be inspected is illuminated by another light source, and the image acquisition and inspection procedures, which will be described later, can be executed without hindrance, the irradiation unit 2 as a component of the evaluation apparatus 1 is not necessarily required. .
  • the imaging unit 3 includes a light receiving unit 7, an image creating unit 8, and an analyzing unit 9.
  • the light receiving unit 7 receives reflected light from the surface of the inspection object, and the image creation unit 8 creates image data of the surface of the inspection object based on the light received by the light receiving unit 7 .
  • the analysis unit 9 performs analysis, which will be described later, based on the image data created by the image creation unit 8 .
  • the light receiving unit 7 must be able to detect at least two wavelengths of reflected light, which will be described later.
  • the light receiving section 7 can detect visible light, and it is particularly preferable that the three primary colors of RGB can be detected.
  • a hyperspectral camera can be used as the imaging unit 3 having such a light receiving unit 7.
  • the imaging unit 3 is a device capable of detecting light including the above two wavelengths, it can be used for the analysis and inspection described later.
  • the device may be sufficient and detectable in a narrower wavelength range of light than a typical hyperspectral camera.
  • the display unit 4 is a display that displays visual information such as images acquired by the imaging unit 3, images processed by the analysis unit 9, and character information indicating the analysis results of the analysis unit 9.
  • the operation unit 5 is an input device for a user to input operations to each unit such as the irradiation unit 2, the imaging unit 3, and the display unit 4. For example, buttons provided on the main body of the imaging unit 3, or an imaging unit. It is a touch panel display or the like connected to the main body of the unit 3 . When the operation unit 5 is configured as a touch panel display, the operation unit 5 can also function as the display unit 4 .
  • the power supply unit 6 is, for example, a battery box that houses a rechargeable battery, and supplies power to the irradiation unit 2, the imaging unit 3, the display unit 4, and the operation unit 5.
  • the devices corresponding to the irradiation unit 2, the display unit 4, etc. are each provided with a power supply device such as a rechargeable battery, it is not necessary to supply power from the power supply unit 6 to these devices (for example, the display unit 4 and the display unit 4).
  • the operation unit 5 is configured as a touch panel type display, the touch panel type display usually comes with a power supply device as standard equipment).
  • NDSI Normalized Difference Spectral Index
  • the NDSI analysis is a method of detecting light of two specific wavelengths out of the light obtained from the surface of the inspection target and grasping the properties of the surface of the inspection target from the difference in intensity thereof. It is known that the reflectance of light on a metal surface varies depending on the surface roughness, and the degree of change in reflectance due to the surface roughness also varies depending on the wavelength of the reflected light.
  • the surface roughness can be grasped from the magnitude thereof.
  • the surface of the object to be inspected is irradiated with light, reflected light with two wavelengths ⁇ 1 and ⁇ 2 is detected from the reflected light, and the respective reflection intensities are calculated. Then, the difference between the two is used as a relative value and the size is evaluated according to the following formula.
  • R ⁇ 1 is the reflectance of light with wavelength ⁇ 1
  • R ⁇ 2 is the reflectance of light with wavelength ⁇ 2.
  • FIG. 2 is a graph showing the wavelength of reflected light in a steel material and the reflectance of the reflected light at that wavelength.
  • the five curves shown in the figure represent the measurement results of the reflectance of steel materials having different surface roughnesses.
  • the surface roughness of the steel materials corresponding to each curve shown in the figure is the largest for steel material A, and decreases in order of steel material B, steel material C, steel material D, and steel material E.
  • FIG. 1 is a graph showing the wavelength of reflected light in a steel material and the reflectance of the reflected light at that wavelength.
  • the five curves shown in the figure represent the measurement results of the reflectance of steel materials having different surface roughnesses.
  • the surface roughness of the steel materials corresponding to each curve shown in the figure is the largest for steel material A, and decreases in order of steel material B, steel material C, steel material D, and steel material E.
  • the intensity of the reflected light differs for each wavelength.
  • the rate of change in the intensity of reflected light due to wavelength is not uniform regardless of the surface roughness. intensity varies greatly.
  • the reflected light of two wavelengths ( ⁇ 1, ⁇ 2) to be used for inspection is selected.
  • the following two conditions are important.
  • Condition 1) The magnitude of reflectance is positively correlated with the magnitude of surface roughness.
  • Condition 2) In addition to satisfying condition 1, one of the two wavelengths of reflected light should have as little variation in reflectance as possible due to the surface roughness of the object to be inspected, and the other should have as large a variation as possible.
  • Condition 1 is a condition to ensure the basic accuracy of the inspection.
  • the intensity of reflected light at wavelengths p and q is correlated with surface roughness (i.e., the lower the surface roughness, the lower the reflectance, and the higher the surface roughness, the higher the reflectance). high), but for the reflected light of wavelength r, the magnitude of the reflectance is reversed in some regions of surface roughness (focusing on steel materials D and E, the reflectance of reflected light on steel material E with low surface roughness is is higher than the reflectance in steel D, which has a higher surface roughness). Reflected light with a wavelength that causes such a phenomenon does not meet condition 1 and is not suitable for inspection.
  • Condition 2 is a condition for improving the accuracy of inspection.
  • the larger the difference in reflectance between the two wavelengths the higher the detection sensitivity, which is suitable for evaluating the surface roughness.
  • the amplitude is as small as possible and “the amplitude is as large as possible” means that the reflectance due to the surface roughness is "largest” or "smallest” among the wavelengths that meet Condition 1. don't mean Of course, the wavelength at which the reflectance due to the surface roughness is "most” or “least” may be selected here, but is not necessarily limited to those wavelengths.
  • the two wavelengths of reflected light one is selected so that the fluctuation range of the reflectance due to the surface roughness of the object to be inspected is as small as possible, and the other is selected as large as possible.” It refers to selecting two wavelengths so that the difference in amplitude due to surface roughness is large to the extent that it does not hinder the NDSI analysis of .
  • the light of each wavelength is arranged in descending order of the amplitude of the reflectance due to the surface roughness (the difference between the reflectance at the surface roughness with the highest reflectance and the reflectance at the surface roughness with the lowest reflectance).
  • light having a wavelength whose reflectance amplitude is located within about the lower one-third is selected as light having a wavelength ⁇ 2
  • wavelengths having a reflectance amplitude greater than or equal to ⁇ 2 are selected. You may select by the method of selecting from light.
  • the reflected light of wavelength q that satisfies condition 1 and has the smallest possible fluctuation of reflectance due to surface roughness is selected as one reflected light (reflected light of wavelength ⁇ 2) used for inspection.
  • the reflectance of light of wavelength ⁇ 2 in each inspection object is used as a reference, and the reflectance of light of other wavelengths is normalized. If the graph of FIG. 2 is redrawn based on this normalized reflectance, it will become like FIG. In the graph of FIG. 3, the other wavelength (wavelength ⁇ 1) that meets the conditions 1 and 2 is selected.
  • the condition that the magnitude of the surface roughness and the magnitude of the reflectance are positively correlated and that the fluctuation range of the reflectance due to the surface roughness is as large as possible corresponds to, for example, the reflected light of the wavelength p.
  • the light is selected as the other reflected light (reflected light with wavelength ⁇ 1) used for inspection.
  • the object to be inspected is steel, it is particularly suitable for inspection to select light with a wavelength of about 620 nm or more and 700 nm or less as the light with the wavelength ⁇ 1 and light with a wavelength of about 450 nm or more and 520 nm or less as the light with the wavelength ⁇ 2. , these wavelengths well meet the above conditions 1 and 2).
  • this figure can of course vary depending on the type of metal that constitutes the object to be inspected.
  • light of two wavelengths (wavelengths ⁇ 1 and ⁇ 2) used for inspection may be specified by the same technique as described above.
  • the wavelengths of light suitable for the light of wavelengths ⁇ 1 and ⁇ 2 may differ from the above numerical values depending on the test method and the like. It should be noted that the numerical values illustrated above are only examples.
  • the image data is created by the image creating section 8 from the light received by the light receiving section 7 .
  • the image data acquired here is, for example, an image of the surface of the object to be inspected photographed in a range of several cm ⁇ several cm to 1 m ⁇ 1 m.
  • the analysis unit 9 selects an appropriate range of the image data (a part of the obtained image may be selected as an inspection target, or the entire image data may be selected).
  • Fig. 4 shows an example of the actual relationship between the NDSI value thus calculated and the surface roughness of the steel material.
  • the horizontal axis is the surface roughness measured using a roughness meter for various steel materials subjected to different degrees of surface roughening
  • the vertical axis is the NDSI value calculated by the above method for each steel material.
  • the same NDSI value can be used to evaluate not only surface roughness but also rust removal.
  • the NDSI value based on the reflected light on the metal surface fluctuates according to the surface roughness as described above, but it is also affected by the degree of rust removal. This has been clarified by the research of the inventor of the present application.
  • the NDSI value when calculating the NDSI value by the above formula (1) based on the light of the wavelength determined by the above method (620 nm ⁇ ⁇ 1 ⁇ 700 nm, 450 nm ⁇ ⁇ 2 ⁇ 520 nm), the area with rust (rusted part) , the NDSI value shows a generally constant value (a specific value varies depending on the measurement environment and the like, but is about 60, for example). Therefore, if the NDSI value is 60 or more, it can be determined that rust exists in that portion. That is, for example, if the image data obtained by the evaluation device 1 includes an area having an NDSI value of 60 or more, it can be determined that the area is a rusted portion. Then, the ratio of pixels whose NDSI value is less than 60 can be grasped as the degree of rust removal.
  • the inspection procedure using the evaluation device 1 can be represented, for example, by the flowchart shown in FIG.
  • each value (R ⁇ 1 and R ⁇ 2 ) used for calculating the NDSI value represented by the above formula (1) is a reflectance, that is, a relative value. I use it. That is, in a certain pixel of an image acquired in a later step, the value obtained by dividing the intensity of light of a certain wavelength by the intensity of light of the same wavelength in the white board data acquired in step S1 is the value of that wavelength at that pixel. is the reflectance of light. It should be noted that it is sufficient to perform this step S1 only once for each site unless the optical conditions differ greatly.
  • image data of the surface of the object to be inspected is acquired (step S2).
  • image data is created for light of at least the two wavelengths, but in addition to this, image data may be created for light of other wavelengths, for example, wavelengths corresponding to RGB.
  • the brightness of the acquired image data is corrected (step S3), and the light intensity data of each wavelength acquired for each pixel is smoothed using a Gaussian filter or the like (step S4).
  • the image data is displayed on the display unit 4 (step S5).
  • step S5 When the image data of the light of the wavelength corresponding to RGB is created in step S2, in this step S5, as shown in FIG.
  • the user of the evaluation device 1 selects an area to be subjected to evaluation of the roughening process from the image displayed on the display unit 4 (step S6).
  • An example of the selection range at this time is indicated by a rectangle in FIG.
  • the portion of the displayed image that captures the appearance of the surface that can be used for inspection is the central region, so this region is selected.
  • the subsequent step of evaluating the surface roughening treatment is performed within the range selected here.
  • this step S6 is a process that is executed, for example, when there is a portion that should not be used for inspection, such as a foreign substance, in the image acquired in step S2, and may be omitted if not necessary. Further, when selecting the region in step S6, the selection may be automatically performed by the evaluation device 1 without depending on the user's operation. In that case, for example, a certain area to be selected from the image displayed on the display unit 4 may be stored in advance, and the stored area may be set to be selected as an evaluation target for each image. . Alternatively, it may be set so that the entire area of the displayed image is automatically selected as the evaluation target.
  • the reflectance of light of the above two wavelengths is calculated, and the NDSI value (see formula (1) above) is calculated (step S7).
  • Steps S8 and S9 are steps for obtaining the surface roughness and the blast rate
  • steps S10 and S11 are steps for obtaining the area of the rusted portion and the degree of rust removal.
  • step S8 the average value of the NDSI values of each pixel obtained in step S7 is calculated. Based on this average value, the surface roughness and the blast rate are calculated from the relationship between the NDSI value and the surface roughness (see FIG. 4) previously obtained by experiment (step S9).
  • the blast rate is the ratio of the area in which the appropriate anchor pattern is formed on the target surface by surface roughening, and correlates with the surface roughness.
  • the surface roughness can be obtained from FIG. 4 based on the NDSI value, but since the surface roughness and the blast rate are correlated, the blast rate can also be obtained based on the surface roughness obtained from FIG.
  • the NDSI value of each target pixel in the acquired image is referred to as a preset threshold to evaluate rusting.
  • the image data is binarized based on the NDSI value of each pixel obtained in step S7.
  • the threshold value used for binarization is an NDSI value that is suitable for determining a rusted portion and is obtained in advance through experiments.
  • a pixel with an NDSI value equal to or greater than a threshold corresponds to a rusted portion, and the area of the rusted portion and the degree of rust removal can be calculated based on the ratio of pixels with an NDSI value greater than or equal to the threshold (step S11).
  • the display unit 4 can appropriately display the image of the object, various numerical values, and the like. For example, after calculating the NDSI value for each pixel in step S7, an image in which each pixel is color-coded according to the magnitude of the NDSI value can be displayed as shown in FIG. Further, the image in which the pixels are color-coded in step S10 can be displayed as an image showing the rusted portion as shown in FIG. The user compares these images with the image shown in FIG. 6, for example, and determines which region of the surface to be inspected shown in the image of FIG. 6 has high (or low) surface roughness and blast rate. Alternatively, it is possible to grasp which region corresponds to the rusted portion.
  • the display unit 4 displays character information such as various values (for example, the average value of the NDSI values in the selected area and the NDSI values used for detecting rusted portions). Threshold value, surface roughness, blast rate, degree of rust removal calculated based on these values, etc.) can also be displayed as appropriate. Further, when the display unit 4 is a touch panel type display and also functions as the operation unit 5, it is possible to display operation buttons and the like.
  • the quality of the surface roughening treatment is evaluated from the surface roughness or blast rate obtained in step S9 and the degree of rust removal obtained in step S10 (step S12).
  • the evaluation here is determined in consideration of consistency with various evaluation standards depending on the inspection object, field, site, and the like. In the quality evaluation of sweep blasting of steel materials for ships, for example, if the blast rate is 30% or more and the degree of rust removal is 90% or more, it is considered acceptable (these figures are only examples, and specific The criteria may differ depending on the object or site), and the evaluation is performed based on the blasting rate according to the surface roughness calculated from the NDSI value and the rust removal degree calculated by binarization.
  • step S12 is based on pre-inputted criteria (reference values regarding blast rate, rust removal, etc., set in advance according to the environment in which the device is operated, such as the office and ship owner supervision). This may be performed by the analysis unit 9 of the imaging unit 3, or may be performed by a person based on the results of steps S9 and S11.
  • the results displayed on the display unit 4 (part or all of the surface roughness, blasting rate, rusted area, degree of rust removal, quality of surface roughening, or other information) are recorded or not shown. It is output as appropriate, such as by printing with a printing machine (step S13), and the inspection ends.
  • the reflectance of light of two wavelengths previously specified as wavelengths suitable for inspection is used, and the surface roughness and the degree of rust are evaluated by NDSI analysis. .
  • Various techniques for evaluating either surface roughness or rusting have been proposed so far. No analogy. In evaluating the roughening treatment of the metal surface, it is necessary to evaluate both the surface roughness and the degree of rust formation. Visual inspection by an inspector has, of course, satisfied this requirement, but the mechanical evaluation techniques that have been developed to date provide devices or methods for evaluating either surface roughness or rust formation. It was not possible to evaluate both at the same time. According to the present embodiment, it is possible to evaluate both indexes by simple calculation, and to output the evaluation of surface roughening based on them.
  • the evaluation apparatus 1 it is possible to inspect a range of up to about 1 m x 1 m on the surface of the inspection object at once. This range is equivalent to the range visually evaluated by inspectors.
  • conventional devices developed for evaluating the quality of surface roughening there are devices that can inspect only a very narrow range of the surface to be inspected at one time. If so, a sufficiently wide range can be inspected in a single operation.
  • evaluation of surface roughness and rust removal can be done with very simple arithmetic processing. It takes only a short time (several seconds at most). Therefore, if the image is acquired, the evaluation of the surface roughening of the inspection object can be confirmed on the spot.
  • the evaluation items, the range of evaluation, and the time required for evaluation can fully replace the conventional visual inspection by an inspector.
  • the evaluation apparatus 1 as shown in FIG. 1 can be manufactured at low cost.
  • the imaging unit 3 and the irradiation unit 2 are operated by a battery-powered power supply unit 6 and do not require a power cable or the like, they can be easily brought into an inspection site such as the inside of a ship's hull structure. , a simple inspection is possible.
  • the imaging unit 3 can be configured as a device having the same size as a general camera device, and the display unit 4 and the operation unit 5 can be configured as devices such as a touch panel display, even one person can carry the evaluation device 1 to the site. and can be evaluated with a simple operation.
  • the evaluation method and evaluation apparatus for the roughening treatment of the metal surface of this embodiment can be used as a technology for performing quantitative evaluation instead of the current visual evaluation, for example, in inspections after blasting work prior to painting in shipbuilding. can do.
  • surface roughening it can be used as a method of presenting an objective standard when the evaluation of pass or fail differs depending on the person.
  • it can be assumed to be used as a tool for training and education for beginners of painting work. At training and education sites, it is sometimes difficult to prepare inspectors or personnel with equivalent knowledge and experience on a case-by-case basis. It can be used for education.
  • the configuration of the evaluation device 1 and the procedure of evaluation described above are only examples, and the configuration of the device and the procedure can be changed as appropriate as long as the evaluation can be suitably performed on the same principle.
  • image creation unit 8 and the analysis unit 9 that constitute the evaluation device 1 the case where an image is created from the light received by the light receiving unit 2 provided in the imaging unit 3 and analyzed has been described above.
  • image data used for inspection may be acquired by the image creating unit 8 from an external device and analyzed by the analysis unit 9 .
  • the evaluation process was described above assuming that the evaluation procedure for the surface roughness and the evaluation for the degree of rusting were performed in parallel. good.
  • an objective evaluation can be performed in place of the conventional visual inspection by an inspector.
  • the wavelength of light used for calculating the NDSI value can be selected based on the following conditions. In this way, accurate and highly accurate evaluation can be performed regarding the roughening treatment of the metal surface.
  • Condition 1) The magnitude of reflectance is positively correlated with the magnitude of surface roughness.
  • Condition 2) In addition to satisfying condition 1, one of the two wavelengths of reflected light should have as little variation in reflectance as possible due to the surface roughness of the object to be inspected, and the other should have as large a variation as possible.
  • the average value of the NDSI values of the target pixels in the acquired image data can be calculated, and the surface roughness can be evaluated based on the average value.
  • rusting can be evaluated by referring to the NDSI value of each target pixel in the acquired image data as a preset threshold value.
  • a range to be evaluated can be selected in the acquired image data, and evaluation of surface roughening can be performed within the selected range.
  • the apparatus 1 for evaluating rough surface treatment of a metal surface of the above embodiment includes an image creating unit 8 for creating image data based on light of at least the two wavelengths selected in advance, and an NDSI analysis based on the image data. and an analysis unit 9 for performing the above-described method for evaluating the roughening of the metal surface.
  • the roughening treatment of the metal surface can be easily and favorably evaluated.
  • evaluation device 2 irradiation unit 3 imaging unit 4 display unit 5 operation unit 6 power supply unit 7 light receiving unit 8 image creation unit 9 analysis unit

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Abstract

The present invention executes: a step S2 for acquiring image data of a surface of a testing sample which has been subjected to surface roughening; a step S7 for calculating an NDSI value of each pixel of the image data with respect to light of two wavelengths pre-selected on the basis of the image data; and steps S8-S12 for performing evaluation with respect to the surface roughening of the testing sample on the basis of the NDSI values.

Description

金属表面の粗面処理の評価方法および評価装置Evaluation method and evaluation device for roughening of metal surface
 本開示は、鋼材等の金属の表面に施された粗面処理に関する評価を行うための方法およびこれを実行し得る評価装置に関する。 The present disclosure relates to a method for evaluating surface roughening applied to the surface of metal such as steel, and an evaluation apparatus capable of executing this.
 鋼材等の金属の表面に対しては、錆を除去したり、塗料の食付きを良くするといった目的で、ショットブラスト等の粗面処理が行われる場合がある。特に船舶においては、船体を構成する鋼材について、対象の箇所に応じて粗面処理の実施が義務付けられている。例えば、防錆塗料の塗膜状態が健全な個所に対してはスイープブラストと呼ばれる軽めの粗面処理が行われるし、健全でない箇所に関しては、より強い度合いの粗面処理が求められる。そして、こうした処理を施された鋼材表面が、粗度や除錆度、清浄度といった所定の要件を満たしているか否かについて、検査官による立会検査が行われるようになっている。ただし、このような立会検査は、検査官が目視により主観的に評価を行う方式がほとんどである。したがって、評価は検査官の技量や経験に依存し、結果にばらつきが発生しやすい。 For the surface of metals such as steel materials, rough surface treatment such as shot blasting is sometimes performed for the purpose of removing rust and improving the bite of paint. In ships, in particular, it is obligatory to roughen the surface of the steel materials that make up the hull, depending on the target location. For example, a light surface roughening process called sweep blasting is applied to areas where the antirust paint film is in good condition, and a stronger surface roughening process is required for areas where the coating is not sound. An inspector conducts an on-site inspection to determine whether or not the surface of the steel material subjected to such treatment satisfies predetermined requirements such as roughness, degree of rust removal, and degree of cleanliness. However, most of such witnessed inspections are subjectively evaluated by inspectors visually. Therefore, the evaluation depends on the skill and experience of the inspector, and the results are likely to vary.
 こうした評価方法に起因する評価のばらつきを抑制するため、程度の異なる粗面処理を施した金属表面の写真を基準として準備し、それらと実物と比較対照することで評価を行う方法等も場合によっては採用されている。しかしながら、検査の現場における光学的な条件はまちまちであるうえ、検査対象である金属に経年による退色等が見られる場合もあり、写真を用いたとしても再現性の高い安定した評価を行うことは困難である。 In order to suppress the variation in evaluation due to such evaluation methods, there are methods such as preparing photographs of metal surfaces with different levels of roughening treatment as a reference and comparing them with the actual object for evaluation. has been adopted. However, the optical conditions at the inspection sites vary, and the metal subject to inspection may show discoloration over time. Have difficulty.
 そこで、金属表面における粗面処理の程度を客観的に測定するための装置や方法が種々創案され、実用化されている(例えば、下記特許文献1、2参照)。 Therefore, various devices and methods for objectively measuring the degree of roughening treatment on a metal surface have been invented and put into practical use (for example, see Patent Documents 1 and 2 below).
特開2019-158820号公報JP 2019-158820 A 特開2019-168353号公報JP 2019-168353 A
 しかしながら、上記特許文献1、2に記載の如き技術を用いた場合、表面粗度は評価できても、除錆度や清浄度は評価できず、検査官の目視による評価をこれらの技術のみで代替することはできない。金属の粗面処理を評価するための技術としては、その他にも種々の光学的な技術や方法が開発されているが、例えば一度に評価可能な範囲が著しく狭いなど、いずれも弱点を抱えており、それらも粗面処理の評価技術として実用上、必ずしも十分であるとは言えなかった。 However, when the techniques described in Patent Documents 1 and 2 are used, even if the surface roughness can be evaluated, the degree of rust removal and cleanliness cannot be evaluated. cannot be substituted. Various other optical techniques and methods have been developed as techniques for evaluating the roughening of metal surfaces, but they all have weaknesses, such as the extremely narrow range that can be evaluated at once. Therefore, it cannot be said that they are practically sufficient as evaluation techniques for surface roughening treatment.
 そこで、本開示においては、斯かる実情に鑑み、金属表面の粗面処理を簡便且つ好適に評価し得る金属表面の粗面処理の評価方法および評価装置を説明する。 Therefore, in the present disclosure, in view of such circumstances, an evaluation method and evaluation apparatus for metal surface roughening that can easily and suitably evaluate metal surface roughening will be described.
 本開示は、粗面処理を施された検査対象の表面の画像データを取得するステップと、前記画像データに基づき、予め選定された2つの波長の光に関し、前記画像データの各ピクセルにおけるNDSI値を算出するステップと、前記NDSI値に基づき、検査対象の粗面処理に関する評価を行うステップとを実行する、金属表面の粗面処理の評価方法にかかるものである。 The present disclosure relates to acquiring image data of a roughened surface of an object to be inspected, and based on said image data, for light of two preselected wavelengths, the NDSI value at each pixel of said image data and a step of evaluating the roughening of an object to be inspected based on the NDSI value.
 上述の金属表面の粗面処理の評価方法において、NDSI値の算出に用いる光の波長は、次の条件に基づき選定することができる。
条件1)表面粗度の大小に対し、反射率の大小が正に相関していること。
条件2)条件1を満たした上で、2波長の反射光のうち、一方は検査対象の表面粗度による反射率の振れ幅がなるべく小さく、他方はなるべく大きいこと。
In the method for evaluating the roughening treatment of the metal surface described above, the wavelength of light used for calculating the NDSI value can be selected based on the following conditions.
Condition 1) The magnitude of reflectance is positively correlated with the magnitude of surface roughness.
Condition 2) In addition to satisfying condition 1, one of the two wavelengths of reflected light should have as little variation in reflectance as possible due to the surface roughness of the object to be inspected, and the other should have as large a variation as possible.
 上述の金属表面の粗面処理の評価方法においては、取得された画像データにおいて、対象とするピクセルのNDSI値の平均値を算出し、該平均値に基づいて表面粗度に関する評価を行うことができる。 In the method for evaluating the roughening of the metal surface described above, the average value of the NDSI values of the target pixels in the acquired image data is calculated, and the surface roughness is evaluated based on the average value. can.
 上述の金属表面の粗面処理の評価方法においては、取得された画像データにおいて、対象とする各ピクセルのNDSI値を予め設定された閾値と参照し、発錆に関する評価を行うことができる。 In the method for evaluating the roughening of the metal surface described above, the NDSI value of each target pixel in the acquired image data can be referred to as a preset threshold to evaluate rusting.
 上述の金属表面の粗面処理の評価方法においては、取得された画像データにおいて評価の対象とする範囲を選択し、粗面処理に関する評価を選択された前記範囲内で行うことができる。 In the method for evaluating surface roughening of a metal surface described above, a range to be evaluated can be selected in the acquired image data, and evaluation of surface roughening can be performed within the selected range.
 また、本開示は、少なくとも予め選定された前記2つの波長の光に基づき画像データを作成する画像作成部と、前記画像データに基づきNDSI解析を行う解析部とを備え、上述の金属表面の粗面処理の評価方法を実行可能に構成されている、金属表面の粗面処理の評価装置にかかるものである。 Further, the present disclosure includes an image creation unit that creates image data based on at least the two wavelengths of light selected in advance, and an analysis unit that performs NDSI analysis based on the image data. The present invention relates to an evaluation apparatus for roughening of a metal surface, which is configured to be capable of executing an evaluation method for surface treatment.
 本発明の金属表面の粗面処理の評価方法および評価装置によれば、金属表面の粗面処理を簡便且つ好適に評価するという優れた効果を奏し得る。 According to the method and apparatus for evaluating the roughening treatment of a metal surface of the present invention, it is possible to obtain an excellent effect of easily and suitably evaluating the roughening treatment of a metal surface.
本開示の実施例による金属表面の粗面処理の評価装置の構成の一例を示すブロック図である。BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram showing an example of the configuration of a metal surface roughening evaluation apparatus according to an embodiment of the present disclosure; 粗面処理を施した鋼材表面における光の波長と反射率との関係を示すグラフである。4 is a graph showing the relationship between the wavelength of light and the reflectance on the surface of a steel material subjected to surface-roughening treatment. 図2の各波長における各反射率を、特定の波長における反射率に対し正規化して表したグラフである。3 is a graph showing each reflectance at each wavelength in FIG. 2 normalized with respect to the reflectance at a specific wavelength; 算出されたNDSI値と、表面粗度との関係の一例を示すグラフである。5 is a graph showing an example of the relationship between calculated NDSI values and surface roughness; 本開示の実施例による金属表面の粗面処理の評価方法の手順の一例を説明するフローチャートである。4 is a flow chart illustrating an example of a procedure of a method for evaluating roughening of a metal surface according to an embodiment of the present disclosure; 本開示の実施例において、表示部に表示される画面の一例を示す図であり、可視光による測定対象の画像と、その選択範囲を表示した様子を示している。FIG. 4 is a diagram showing an example of a screen displayed on a display unit in an embodiment of the present disclosure, showing a state in which an image of a measurement target using visible light and a selection range thereof are displayed; 本開示の実施例において、表示部に表示される画面の別の一例を示す図であり、選択範囲がNDSI値に応じて色分けされた画像を表示した様子を示している。FIG. 10 is a diagram showing another example of a screen displayed on the display unit in the embodiment of the present disclosure, showing a state in which an image in which the selection range is color-coded according to the NDSI value is displayed. 本開示の実施例において、表示部に表示される画面のさらに一例を示す図であり、選択範囲がNDSI値に応じて二値化された画像を表示した様子を示している。FIG. 10 is a diagram illustrating another example of a screen displayed on the display unit in the embodiment of the present disclosure, and illustrates a state in which an image in which the selection range is binarized according to the NDSI value is displayed;
 以下、本開示における実施例の形態を添付図面を参照して説明する。 Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings.
 図1は本開示の実施例による金属表面の粗面処理の評価装置の構成の一例を示している。評価装置1は、検査のための光を照射する照射部2と、検査対象の画像データを取得する撮像部3と、各種の視覚情報を表示する表示部4と、照射部2や撮像部3、表示部4といった各部への操作を入力する操作部5と、これら各部に電力を供給する電源部6とを備えた簡便な構成の装置である。 FIG. 1 shows an example of the configuration of a metal surface roughening evaluation apparatus according to an embodiment of the present disclosure. The evaluation device 1 includes an irradiation unit 2 that irradiates light for inspection, an imaging unit 3 that acquires image data of an object to be inspected, a display unit 4 that displays various visual information, the irradiation unit 2 and the imaging unit 3. , and a display unit 4, and a power supply unit 6 for supplying power to these units.
 照射部2は、例えばLED照明装置であり、検査対象に対し検査のための光を照射するようになっている。照射部2の照射する光は、少なくとも後述する2波長の反射光に対応する波長の光を含む必要がある。ここで、「ある波長(λnm)の反射光に対応する波長の光」とは、「その光が検査対象に入射した場合に、λnmの波長の反射光が得られる波長の光」を指す。尚、検査対象が他の光源によって照らされており、それによって後述する画像の取得や検査の手順を支障なく実行できる場合には、評価装置1の構成要素としての照射部2は必ずしも必要ではない。 The irradiation unit 2 is, for example, an LED lighting device, and is designed to irradiate the inspection object with light for inspection. The light emitted by the irradiation unit 2 needs to include at least light of wavelengths corresponding to the two wavelengths of reflected light described later. Here, "light of a wavelength corresponding to reflected light of a certain wavelength (λ nm)" refers to "light of a wavelength that, when the light is incident on an object to be inspected, gives reflected light of a wavelength of λ nm". If the object to be inspected is illuminated by another light source, and the image acquisition and inspection procedures, which will be described later, can be executed without hindrance, the irradiation unit 2 as a component of the evaluation apparatus 1 is not necessarily required. .
 撮像部3は、受光部7と、画像作成部8と、解析部9を備えている。受光部7は、検査対象の表面の反射光を受光し、画像作成部8は、受光部7が受光した光に基づいて検査対象の表面の画像データを作成する。解析部9は、画像作成部8の作成した画像データに基づき、後述する解析を行う。 The imaging unit 3 includes a light receiving unit 7, an image creating unit 8, and an analyzing unit 9. The light receiving unit 7 receives reflected light from the surface of the inspection object, and the image creation unit 8 creates image data of the surface of the inspection object based on the light received by the light receiving unit 7 . The analysis unit 9 performs analysis, which will be described later, based on the image data created by the image creation unit 8 .
 受光部7は、少なくとも後述する2波長の反射光を検出できる必要がある。また、受光部7は、これに加えて可視光を検出できることが好ましく、特にRGBの三原色を検出できるようになっていることが好ましい。このような受光部7を備えた撮像部3としては、例えばハイパースペクトルカメラを用いることができるが、撮像部3は上記2波長を含む光を検出できる装置であれば後述する解析および検査には十分であり、検出可能な光の波長域が一般的なハイパースペクトルカメラよりは狭い装置であってもよい。 The light receiving unit 7 must be able to detect at least two wavelengths of reflected light, which will be described later. In addition, it is preferable that the light receiving section 7 can detect visible light, and it is particularly preferable that the three primary colors of RGB can be detected. For example, a hyperspectral camera can be used as the imaging unit 3 having such a light receiving unit 7. However, if the imaging unit 3 is a device capable of detecting light including the above two wavelengths, it can be used for the analysis and inspection described later. The device may be sufficient and detectable in a narrower wavelength range of light than a typical hyperspectral camera.
 表示部4は、撮像部3で取得された画像や、解析部9による処理を経た画像、また解析部9による解析の結果を示す文字情報などの視覚情報を表示するディスプレイである。 The display unit 4 is a display that displays visual information such as images acquired by the imaging unit 3, images processed by the analysis unit 9, and character information indicating the analysis results of the analysis unit 9.
 操作部5は、照射部2、撮像部3、表示部4といった各部に対し、使用者が操作を入力するための入力装置であり、例えば撮像部3の本体に備えられたボタン類、あるいは撮像部3の本体に接続されたタッチパネル式のディスプレイ等である。尚、操作部5をタッチパネル式のディスプレイとして構成する場合、操作部5は表示部4の機能を兼ねることもできる。 The operation unit 5 is an input device for a user to input operations to each unit such as the irradiation unit 2, the imaging unit 3, and the display unit 4. For example, buttons provided on the main body of the imaging unit 3, or an imaging unit. It is a touch panel display or the like connected to the main body of the unit 3 . When the operation unit 5 is configured as a touch panel display, the operation unit 5 can also function as the display unit 4 .
 電源部6は、例えば充電式の電池が収容される電池ボックスであり、照射部2、撮像部3、表示部4および操作部5へ電力を供給するようになっている。尚、照射部2や表示部4等にあたる装置が各々充電式電池等の電源装置を備えている場合には、これらへの電源部6からの電力供給は不要である(例えば、表示部4と操作部5がタッチパネル式ディスプレイとして構成される場合、該タッチパネル式ディスプレイには通常、電源装置が標準装備として付属している)。 The power supply unit 6 is, for example, a battery box that houses a rechargeable battery, and supplies power to the irradiation unit 2, the imaging unit 3, the display unit 4, and the operation unit 5. In addition, when the devices corresponding to the irradiation unit 2, the display unit 4, etc. are each provided with a power supply device such as a rechargeable battery, it is not necessary to supply power from the power supply unit 6 to these devices (for example, the display unit 4 and the display unit 4). When the operation unit 5 is configured as a touch panel type display, the touch panel type display usually comes with a power supply device as standard equipment).
 上記評価装置1を用いた検査の仕組みについて説明する。検査には、2波長の反射光によるNDSI(Normalized Difference Spectral Index)解析や傾き解析等と呼ばれる手法を用いる。NDSI解析とは、検査対象の表面から得た光のうち、特定の2波長の光を検出し、それらの強度の差によって検査対象の表面の性質等を把握する手法である。金属の表面における光の反射率は表面粗度によって異なるが、その表面粗度による反射率の変化の度合いは、さらに反射光の波長によって異なることが知られている。したがって、検査対象の表面の反射光から特定の2波長の光を検出し、それらの反射率を比較すると、その大小によって表面粗度を把握することができる。具体的には、検査対象の表面に光を照射し、反射光のうち、λ1とλ2という2波長の反射光を検出し、それぞれの反射強度を算出する。そして、下記の式により両者の差を相対値として大小を評価する。尚、下記式(1)において、Rλ1は波長λ1の光の反射率、Rλ2は波長λ2の光の反射率である。
(Rλ1-Rλ2)/(Rλ1+Rλ2) ……(1)
A mechanism of inspection using the evaluation apparatus 1 will be described. For inspection, a technique called NDSI (Normalized Difference Spectral Index) analysis using reflected light of two wavelengths, tilt analysis, or the like is used. The NDSI analysis is a method of detecting light of two specific wavelengths out of the light obtained from the surface of the inspection target and grasping the properties of the surface of the inspection target from the difference in intensity thereof. It is known that the reflectance of light on a metal surface varies depending on the surface roughness, and the degree of change in reflectance due to the surface roughness also varies depending on the wavelength of the reflected light. Therefore, by detecting two specific wavelengths of light from the reflected light from the surface of the inspection object and comparing their reflectances, the surface roughness can be grasped from the magnitude thereof. Specifically, the surface of the object to be inspected is irradiated with light, reflected light with two wavelengths λ1 and λ2 is detected from the reflected light, and the respective reflection intensities are calculated. Then, the difference between the two is used as a relative value and the size is evaluated according to the following formula. In the following formula (1), R λ1 is the reflectance of light with wavelength λ1, and R λ2 is the reflectance of light with wavelength λ2.
(R λ1 −R λ2 )/(R λ1 +R λ2 ) (1)
 このようなNDSI解析の原理自体は既に広く知られているが、本願発明者は特に金属の表面粗度を解析するにあたって最適な反射光の波長を特定する手法を開発し、さらに、粗面処理の評価における表面粗度以外の指標をも併せて評価し得る技術を発明するに至った。 The principle of such NDSI analysis itself is already widely known, but the inventors of the present application have developed a technique for specifying the optimum reflected light wavelength for analyzing the surface roughness of metals, and have further developed a method for surface roughening. In the evaluation of , we have invented a technique that can also evaluate indices other than surface roughness.
 まず、表面粗度の解析に適した反射光の波長の特定について説明する。図2は、鋼材における反射光の波長と、その波長の反射光の反射率を示すグラフである。図中に示された5本の曲線は、各々表面粗度の互いに異なる鋼材における反射率の測定結果を示している。尚、図中に示す各曲線に対応する鋼材の表面粗度は、鋼材Aで最も大きく、鋼材B、鋼材C、鋼材D、鋼材Eの順に小さくなる。 First, we will explain how to identify the wavelength of reflected light that is suitable for surface roughness analysis. FIG. 2 is a graph showing the wavelength of reflected light in a steel material and the reflectance of the reflected light at that wavelength. The five curves shown in the figure represent the measurement results of the reflectance of steel materials having different surface roughnesses. The surface roughness of the steel materials corresponding to each curve shown in the figure is the largest for steel material A, and decreases in order of steel material B, steel material C, steel material D, and steel material E. FIG.
 ここに示すように、同一の検査対象であっても、反射光の強度は波長毎に異なる。また、波長による反射光の強度の変化率は表面粗度にかかわらず一様というわけではなく、例えば図中における波長pの反射光は、波長qの反射光と比較して、表面粗度によって強度が大きく変化している。 As shown here, even for the same inspection object, the intensity of the reflected light differs for each wavelength. In addition, the rate of change in the intensity of reflected light due to wavelength is not uniform regardless of the surface roughness. intensity varies greatly.
 これを踏まえ、検査に用いる2波長(λ1、λ2)の反射光を選定する。波長の選定にあたっては、以下の2条件が重要である。
条件1)表面粗度の大小に対し、反射率の大小が正に相関していること。
条件2)条件1を満たした上で、2波長の反射光のうち、一方は検査対象の表面粗度による反射率の振れ幅がなるべく小さく、他方はなるべく大きいこと。
Based on this, the reflected light of two wavelengths (λ1, λ2) to be used for inspection is selected. In selecting the wavelength, the following two conditions are important.
Condition 1) The magnitude of reflectance is positively correlated with the magnitude of surface roughness.
Condition 2) In addition to satisfying condition 1, one of the two wavelengths of reflected light should have as little variation in reflectance as possible due to the surface roughness of the object to be inspected, and the other should have as large a variation as possible.
 条件1は、検査の基本的な正確さを担保するための条件である。例えば図2に示すグラフでは、波長pおよび波長qの反射光の強度は表面粗度と相関している(すなわち、表面粗度が小さいほど反射率が低く、表面粗度が大きいほど反射率が高い)が、波長rの反射光については、表面粗度の一部領域において反射率の大小が入れ替わっている(鋼材D、Eに着目すると、表面粗度の低い鋼材Eにおける反射光の反射率が、より表面粗度の高い鋼材Dにおける反射率よりも高い)。このような現象の見られる波長の反射光は、条件1に合致せず、検査を行うにあたって適切でない。 Condition 1 is a condition to ensure the basic accuracy of the inspection. For example, in the graph shown in FIG. 2, the intensity of reflected light at wavelengths p and q is correlated with surface roughness (i.e., the lower the surface roughness, the lower the reflectance, and the higher the surface roughness, the higher the reflectance). high), but for the reflected light of wavelength r, the magnitude of the reflectance is reversed in some regions of surface roughness (focusing on steel materials D and E, the reflectance of reflected light on steel material E with low surface roughness is is higher than the reflectance in steel D, which has a higher surface roughness). Reflected light with a wavelength that causes such a phenomenon does not meet condition 1 and is not suitable for inspection.
 条件2は、検査の精度を高めるための条件である。上記式(1)を用いるNDSI解析では、両波長の光の反射率の差が大きいほど検出感度が高く、表面粗度の評価に向く。尚、ここでいう「振れ幅がなるべく小さい」「振れ幅がなるべく大きい」とは、条件1に合致する波長の中で、表面粗度による反射率が「最も大きい」あるいは「最も小さい」ことを意味しない。無論、表面粗度による反射率が「最も大きい」あるいは「最も小さい」波長をここで選択してもよいが、必ずしもそれらの波長に限定されない。「2波長の反射光のうち、一方は検査対象の表面粗度による反射率の振れ幅がなるべく小さく、他方はなるべく大きい波長を選定する」とは、これら2波長の光を用いて粗面処理に関するNDSI解析を行うにあたって支障がない程度に、表面粗度による振れ幅の差が大きくなるよう、2波長を選定することを指す。目安としては、例えば表面粗度による反射率の振れ幅(最も反射率の高い表面粗度における反射率と、最も反射率の低い表面粗度における反射率の差)が大きい順に各波長の光を並べた場合に、上位3分の1程度以内に位置する波長から選定された波長をλ1に、下位3分の1以内程度に位置する波長から選定された波長をλ2に、それぞれ設定すれば足りる。あるいは、まず反射率の振れ幅が下位3分の1程度以内に位置する波長の光を波長λ2の光として選定し、波長λ1の光については、反射率の振れ幅がλ2以上である波長の光から選定するといった方法で選定してもよい。 Condition 2 is a condition for improving the accuracy of inspection. In the NDSI analysis using the above formula (1), the larger the difference in reflectance between the two wavelengths, the higher the detection sensitivity, which is suitable for evaluating the surface roughness. Here, "the amplitude is as small as possible" and "the amplitude is as large as possible" means that the reflectance due to the surface roughness is "largest" or "smallest" among the wavelengths that meet Condition 1. don't mean Of course, the wavelength at which the reflectance due to the surface roughness is "most" or "least" may be selected here, but is not necessarily limited to those wavelengths. "Of the two wavelengths of reflected light, one is selected so that the fluctuation range of the reflectance due to the surface roughness of the object to be inspected is as small as possible, and the other is selected as large as possible." It refers to selecting two wavelengths so that the difference in amplitude due to surface roughness is large to the extent that it does not hinder the NDSI analysis of . As a guideline, for example, the light of each wavelength is arranged in descending order of the amplitude of the reflectance due to the surface roughness (the difference between the reflectance at the surface roughness with the highest reflectance and the reflectance at the surface roughness with the lowest reflectance). When they are arranged, it is sufficient to set the wavelength selected from the wavelengths positioned within about the upper third to λ1 and the wavelength selected from the wavelengths positioned within the lower one-third to λ2, respectively. . Alternatively, first, light having a wavelength whose reflectance amplitude is located within about the lower one-third is selected as light having a wavelength λ2, and for light having a wavelength λ1, wavelengths having a reflectance amplitude greater than or equal to λ2 are selected. You may select by the method of selecting from light.
 具体的な選定の手順の一例を以下に説明する。まず図2において、条件1を満たし、且つ表面粗度による反射率の振れ幅がなるべく小さい波長qの反射光を、検査に用いる一方の反射光(波長がλ2の反射光)として選定する。 An example of a specific selection procedure is described below. First, in FIG. 2, the reflected light of wavelength q that satisfies condition 1 and has the smallest possible fluctuation of reflectance due to surface roughness is selected as one reflected light (reflected light of wavelength λ2) used for inspection.
 次に、各検査対象における波長λ2の光の反射率を基準とし、その他の波長の光の反射率を正規化する。この正規化された反射率に基づいて図2のグラフを描き直すと、図3のようになる。この図3のグラフにおいて、上記条件1、2に合致する他方の波長(波長λ1)を選定する。表面粗度の大小と反射率の大小が正に相関し、且つ表面粗度による反射率の振れ幅がなるべく大きいという条件には、例えば波長pの反射光が該当するので、この波長pの反射光を、検査に用いる他方の反射光(波長がλ1の反射光)として選定する。 Next, the reflectance of light of wavelength λ2 in each inspection object is used as a reference, and the reflectance of light of other wavelengths is normalized. If the graph of FIG. 2 is redrawn based on this normalized reflectance, it will become like FIG. In the graph of FIG. 3, the other wavelength (wavelength λ1) that meets the conditions 1 and 2 is selected. The condition that the magnitude of the surface roughness and the magnitude of the reflectance are positively correlated and that the fluctuation range of the reflectance due to the surface roughness is as large as possible corresponds to, for example, the reflected light of the wavelength p. The light is selected as the other reflected light (reflected light with wavelength λ1) used for inspection.
 尚、検査対象が鋼材である場合、波長λ1の光としては620nm以上700nm以下程度、波長λ2の光としては450nm以上520nm以下程度の波長の光をそれぞれ選択すると、検査にとって特に好適である(すなわち、これらの波長が上記条件1、2によく合致する)ことを本願発明者らは見出している。ただし、この数値は無論、検査対象を構成する金属の種類によって変わり得る。鉄以外の金属に対して本発明の評価方法を実施する場合には、上記と同様の手法により、検査に用いる2波長(波長λ1、λ2)の光を特定すればよい。また、検査対象が鋼材であっても、試験の方法等によっては、波長λ1、λ2の光として好適な光の波長は上記の数値とは異なり得る。上に例示した数値はあくまで一例であることを留意すべきである。 When the object to be inspected is steel, it is particularly suitable for inspection to select light with a wavelength of about 620 nm or more and 700 nm or less as the light with the wavelength λ1 and light with a wavelength of about 450 nm or more and 520 nm or less as the light with the wavelength λ2. , these wavelengths well meet the above conditions 1 and 2). However, this figure can of course vary depending on the type of metal that constitutes the object to be inspected. When the evaluation method of the present invention is applied to metals other than iron, light of two wavelengths (wavelengths λ1 and λ2) used for inspection may be specified by the same technique as described above. Further, even if the object to be inspected is a steel material, the wavelengths of light suitable for the light of wavelengths λ1 and λ2 may differ from the above numerical values depending on the test method and the like. It should be noted that the numerical values illustrated above are only examples.
 このような原理により、図1に示す如き評価装置1を用いて検査対象の表面粗度を検査する場合、まず照射部2から検査対象へ光を照射し、撮像部3で検査対象の表面の画像データを取得する。すなわち、受光部7で受光した光から、画像作成部8で画像データを作成する。ここで取得される画像データは、例えば検査対象の表面を数cm×数cm~1m×1m程度の範囲で撮影した画像である。解析部9は、この画像データのうち、適当な範囲(得られた画像のうち、検査対象とする一部の領域を選択してもよいし、画像データの全体を対象としてもよい)に含まれる各ピクセル毎に、波長がλ1およびλ2の光の強度に基づき、上記式(1)を用いてNDSI値を算出する。ピクセル毎に得られたNDSI値の平均値を算出すれば、これを表面粗度を示す値として評価することができる。 When inspecting the surface roughness of an object to be inspected using the evaluation apparatus 1 as shown in FIG. Get image data. That is, the image data is created by the image creating section 8 from the light received by the light receiving section 7 . The image data acquired here is, for example, an image of the surface of the object to be inspected photographed in a range of several cm×several cm to 1 m×1 m. The analysis unit 9 selects an appropriate range of the image data (a part of the obtained image may be selected as an inspection target, or the entire image data may be selected). Calculate the NDSI value using equation (1) above based on the intensity of light at wavelengths λ1 and λ2 for each pixel in the pixel. By calculating the average value of the NDSI values obtained for each pixel, it can be evaluated as a value indicating the surface roughness.
 こうして算出したNDSI値と、鋼材の表面粗度との実際の関係の一例を図4に示す。横軸は、粗面処理を異なる度合いで施した種々の鋼材について粗度計を用いて計測した表面粗度、縦軸は各鋼材について上記方法により算出したNDSI値である。ここに示すように、両値は強い相関を示し(尚、サンプル数n=24、相関係数r=0.958である)、NDSI値が表面粗度の指標として有用であることがわかる。 Fig. 4 shows an example of the actual relationship between the NDSI value thus calculated and the surface roughness of the steel material. The horizontal axis is the surface roughness measured using a roughness meter for various steel materials subjected to different degrees of surface roughening, and the vertical axis is the NDSI value calculated by the above method for each steel material. As shown here, both values show a strong correlation (number of samples n=24, correlation coefficient r=0.958), and the NDSI value is useful as an index of surface roughness.
 また、同NDSI値は、表面粗度のみならず除錆度の評価にも用いることが可能である。金属表面における反射光に基づくNDSI値は、上述の如く表面粗度に応じて変動するが、除錆度にも影響され、錆のある部分においては表面粗度によらず大きい値を示すことが本願発明者の研究により判明している。例えば鋼材において、上記手法により決定した波長の光(620nm≦λ1≦700nm、450nm≦λ2≦520nm)に基づき、上記式(1)によりNDSI値を算出する場合、錆のある領域(発錆部)においては、NDSI値は概ね一定値(具体的な値は計測環境等によって変動するが、例えば60程度)を示す。したがって、NDSI値が60以上であれば、その部分には錆が存在すると判断することができる。すなわち、例えば上記評価装置1によって取得された画像データにNDSI値が60以上を示す領域があった場合には、その領域は発錆部であると判断することができる。そして、NDSI値が60未満であるピクセルの割合を除錆度として把握することができる。 In addition, the same NDSI value can be used to evaluate not only surface roughness but also rust removal. The NDSI value based on the reflected light on the metal surface fluctuates according to the surface roughness as described above, but it is also affected by the degree of rust removal. This has been clarified by the research of the inventor of the present application. For example, in steel materials, when calculating the NDSI value by the above formula (1) based on the light of the wavelength determined by the above method (620 nm ≤ λ1 ≤ 700 nm, 450 nm ≤ λ2 ≤ 520 nm), the area with rust (rusted part) , the NDSI value shows a generally constant value (a specific value varies depending on the measurement environment and the like, but is about 60, for example). Therefore, if the NDSI value is 60 or more, it can be determined that rust exists in that portion. That is, for example, if the image data obtained by the evaluation device 1 includes an area having an NDSI value of 60 or more, it can be determined that the area is a rusted portion. Then, the ratio of pixels whose NDSI value is less than 60 can be grasped as the degree of rust removal.
 上述の如き評価装置1(図1参照)を用いた検査の手順は、例えば図5に示すフローチャートに表すことができる。 The inspection procedure using the evaluation device 1 (see FIG. 1) as described above can be represented, for example, by the flowchart shown in FIG.
 検査に先立ち、撮像部3に補正のための白板のデータを取得し、NDSI値の算出に用いる光強度を設定しておく(ステップS1)。上記式(1)で表されるNDSI値の算出に用いる各値(Rλ1およびRλ2)は反射率であり、すなわち相対値であるが、この相対値の算出にあたり、白板の明度を分母として用いるのである。つまり、後のステップで取得される画像のあるピクセルにおいて、ある波長の光の強度を、ステップS1で取得した白板のデータにおける同じ波長の光の強度で割った値が、そのピクセルにおけるその波長の光の反射率である。尚、このステップS1は、光学的な条件が大きく異ならない限り、各現場毎に一度のみ実行すれば十分である。 Prior to the inspection, white board data for correction is acquired in the imaging unit 3, and the light intensity used for calculating the NDSI value is set (step S1). Each value (R λ1 and R λ2 ) used for calculating the NDSI value represented by the above formula (1) is a reflectance, that is, a relative value. I use it. That is, in a certain pixel of an image acquired in a later step, the value obtained by dividing the intensity of light of a certain wavelength by the intensity of light of the same wavelength in the white board data acquired in step S1 is the value of that wavelength at that pixel. is the reflectance of light. It should be noted that it is sufficient to perform this step S1 only once for each site unless the optical conditions differ greatly.
 検査対象の表面に照射部2から光を照射し、検査対象の表面の画像データを取得する(ステップS2)。ここでは、少なくとも上記2波長の光について画像データを作成するが、これに加えてその他の波長、例えばRGBにあたる波長の光による画像データを作成してもよい。 The surface of the object to be inspected is irradiated with light from the irradiation unit 2, and image data of the surface of the object to be inspected is acquired (step S2). Here, image data is created for light of at least the two wavelengths, but in addition to this, image data may be created for light of other wavelengths, for example, wavelengths corresponding to RGB.
 取得した画像データの明度等を補正し(ステップS3)、ピクセル毎に取得された各波長の光強度のデータを、ガウシアンフィルタ等を用いて平滑化する(ステップS4)。 The brightness of the acquired image data is corrected (step S3), and the light intensity data of each wavelength acquired for each pixel is smoothed using a Gaussian filter or the like (step S4).
 画像データを、表示部4に表示する(ステップS5)。ステップS2においてRGBにあたる波長の光による画像データを作成した場合、このステップS5では、表示部4に例えば図6に示すように、RGBによる検査対象の画像を表示することができる。 The image data is displayed on the display unit 4 (step S5). When the image data of the light of the wavelength corresponding to RGB is created in step S2, in this step S5, as shown in FIG.
 評価装置1のユーザは、表示部4に表示された画像のうち、粗面処理の評価の対象とする領域を選択する(ステップS6)。この時の選択範囲の一例を図6中に矩形で示す。ここに示した例の場合、表示された画像のうち、検査に使用し得る表面の様子を捉えた部分は中央の領域であるので、この領域を選択する。以降の粗面処理に関する評価を行うステップは、ここで選択された範囲内で行う。 The user of the evaluation device 1 selects an area to be subjected to evaluation of the roughening process from the image displayed on the display unit 4 (step S6). An example of the selection range at this time is indicated by a rectangle in FIG. In the case of the example shown here, the portion of the displayed image that captures the appearance of the surface that can be used for inspection is the central region, so this region is selected. The subsequent step of evaluating the surface roughening treatment is performed within the range selected here.
 尚、このステップS6は、例えばステップS2で取得された画像内に異物など、検査に使用したくない部分がある時などに実行する工程であって、必要がなければ省略してもよい。また、このステップS6における領域の選択を行う場合、ユーザの操作によらず、評価装置1によって自動的に行うようにしてもよい。その場合、例えば、表示部4に表示される画像のうち選択する一定の領域を予め記憶しておき、記憶した前記領域を、画像毎に評価の対象として選択するように設定しておけばよい。また、表示される画像の全領域を、評価の対象として自動的に選択するよう設定してもよい。 Note that this step S6 is a process that is executed, for example, when there is a portion that should not be used for inspection, such as a foreign substance, in the image acquired in step S2, and may be omitted if not necessary. Further, when selecting the region in step S6, the selection may be automatically performed by the evaluation device 1 without depending on the user's operation. In that case, for example, a certain area to be selected from the image displayed on the display unit 4 may be stored in advance, and the stored area may be set to be selected as an evaluation target for each image. . Alternatively, it may be set so that the entire area of the displayed image is automatically selected as the evaluation target.
 選択した領域に含まれる各ピクセルについて、上記2波長の光の反射率を計算し、NDSI値(上記式(1)参照)を算出する(ステップS7)。 For each pixel included in the selected area, the reflectance of light of the above two wavelengths is calculated, and the NDSI value (see formula (1) above) is calculated (step S7).
 続いて、各ピクセルについて算出されたNDSI値に基づき、表面粗度、ブラスト率、発錆部の面積、除錆度といった検査対象の粗面処理に関する評価を行い、さらにそれらに基づき、粗面処理の品質に関する最終的な評価を行う。表面粗度とブラスト率を求める工程はステップS8、S9、発錆部の面積と除錆度を求める工程はステップS10、S11である。 Subsequently, based on the NDSI value calculated for each pixel, the surface roughness, blasting rate, area of the rusted portion, degree of rust removal, and other evaluations of the surface roughening of the inspection object are performed. make a final assessment of the quality of Steps S8 and S9 are steps for obtaining the surface roughness and the blast rate, and steps S10 and S11 are steps for obtaining the area of the rusted portion and the degree of rust removal.
 ステップS8では、ステップS7で求めた各ピクセルのNDSI値の平均値を算出する。この平均値に基づき、予め実験で求めたNDSI値と表面粗度の関係(図4参照)から、表面粗度とブラスト率を算出する(ステップS9)。ここで、ブラスト率とは、粗面処理によって対象表面に適正なアンカーパターンが形成された面積の比率であり、表面粗度と相関している。表面粗度はNDSI値に基づいて図4から求めることができるが、表面粗度とブラスト率は相関するので、図4から求めた表面粗度に基づいてブラスト率も求めることが可できる。 In step S8, the average value of the NDSI values of each pixel obtained in step S7 is calculated. Based on this average value, the surface roughness and the blast rate are calculated from the relationship between the NDSI value and the surface roughness (see FIG. 4) previously obtained by experiment (step S9). Here, the blast rate is the ratio of the area in which the appropriate anchor pattern is formed on the target surface by surface roughening, and correlates with the surface roughness. The surface roughness can be obtained from FIG. 4 based on the NDSI value, but since the surface roughness and the blast rate are correlated, the blast rate can also be obtained based on the surface roughness obtained from FIG.
 ステップS10、S11では、取得された画像において、対象とする各ピクセルのNDSI値を予め設定された閾値と参照し、発錆に関する評価を行う。まずステップS10では、画像データを、ステップS7で求めた各ピクセルのNDSI値に基づいて二値化する。二値化に用いる閾値は、予め実験により求めた発錆部の判定に適したNDSI値である。NDSI値が閾値以上であるピクセルは発錆部にあたり、NDSI値が閾値以上であるピクセルの割合に基づき、発錆部の面積および除錆度を算出することができる(ステップS11)。 In steps S10 and S11, the NDSI value of each target pixel in the acquired image is referred to as a preset threshold to evaluate rusting. First, in step S10, the image data is binarized based on the NDSI value of each pixel obtained in step S7. The threshold value used for binarization is an NDSI value that is suitable for determining a rusted portion and is obtained in advance through experiments. A pixel with an NDSI value equal to or greater than a threshold corresponds to a rusted portion, and the area of the rusted portion and the degree of rust removal can be calculated based on the ratio of pixels with an NDSI value greater than or equal to the threshold (step S11).
 ステップS7~S11においては、表示部4にて対象物の画像や、各種数値等を適宜表示することができる。例えば、ステップS7で各ピクセルについてNDSI値を算出した後、NDSI値の大小に応じて各ピクセルを色分けした画像を、図7に示す如く表示することができる。また、ステップS10にてピクセルを色分けした画像を、発錆部を示す画像として図8に示す如く表示することができる。ユーザは、例えばこれらの画像を図6に示す如き画像と見比べ、図6の画像に表れている検査対象の表面のうち、どの領域で表面粗度やブラスト率が高いか(または低いか)、あるいは、どの領域が発錆部にあたるか等を把握することができる。また、検査対象の表面に汚れ等が付着していた場合は、その位置を図6に示す画像から把握することができる。また、図7、図8に示す画像においてNDSI値の異常な領域が見られた場合には、その領域が目視でどのように見えるか(その領域に汚れや錆等が存在するかどうか)を図6に示す画像で確認することができる。 In steps S7 to S11, the display unit 4 can appropriately display the image of the object, various numerical values, and the like. For example, after calculating the NDSI value for each pixel in step S7, an image in which each pixel is color-coded according to the magnitude of the NDSI value can be displayed as shown in FIG. Further, the image in which the pixels are color-coded in step S10 can be displayed as an image showing the rusted portion as shown in FIG. The user compares these images with the image shown in FIG. 6, for example, and determines which region of the surface to be inspected shown in the image of FIG. 6 has high (or low) surface roughness and blast rate. Alternatively, it is possible to grasp which region corresponds to the rusted portion. Also, if dirt or the like is attached to the surface of the object to be inspected, its position can be grasped from the image shown in FIG. Also, if an area with an abnormal NDSI value is found in the images shown in FIGS. This can be confirmed by the image shown in FIG.
 尚、表示部4には、図6~図8に示す如き画像に加え、各種の値などの文字情報(例えば選択した領域におけるNDSI値の平均値や、発錆部の検出に用いるNDSI値の閾値、これらに基づいて算出された表面粗度やブラスト率、除錆度など)を適宜表示することもできる。また、表示部4がタッチパネル式のディスプレイであり、操作部5の機能をも兼ねている場合には、操作ボタン等を表示することもできる。 In addition to the images shown in FIGS. 6 to 8, the display unit 4 displays character information such as various values (for example, the average value of the NDSI values in the selected area and the NDSI values used for detecting rusted portions). Threshold value, surface roughness, blast rate, degree of rust removal calculated based on these values, etc.) can also be displayed as appropriate. Further, when the display unit 4 is a touch panel type display and also functions as the operation unit 5, it is possible to display operation buttons and the like.
 ステップS9で求めた表面粗度またはブラスト率と、ステップS10で求めた除錆度から、粗面処理の品質を評価する(ステップS12)。ここでの評価は、検査対象や分野、現場等によって種々に異なる評価基準との整合性を考慮して決定する。船舶の鋼材におけるスイープブラストの品質評価では、例えばブラスト率が30%以上、且つ除錆度が90%以上であれば合格とされるので(尚、これらの数値は一例であって、具体的な基準は対象や現場によって異なり得る)、NDSI値から算出された表面粗度に応じたブラスト率と、二値化によって算出された除錆度に基づき評価を行う。尚、このステップS12における評価は、予め入力された基準(事業所や船主監督など、装置を運用する環境に応じて予め設定しておいた、ブラスト率や除錆度等に関する基準値)に基づき撮像部3の解析部9で行ってもよいし、ステップS9やステップS11の結果に基づいて人が行ってもよい。 The quality of the surface roughening treatment is evaluated from the surface roughness or blast rate obtained in step S9 and the degree of rust removal obtained in step S10 (step S12). The evaluation here is determined in consideration of consistency with various evaluation standards depending on the inspection object, field, site, and the like. In the quality evaluation of sweep blasting of steel materials for ships, for example, if the blast rate is 30% or more and the degree of rust removal is 90% or more, it is considered acceptable (these figures are only examples, and specific The criteria may differ depending on the object or site), and the evaluation is performed based on the blasting rate according to the surface roughness calculated from the NDSI value and the rust removal degree calculated by binarization. It should be noted that the evaluation in step S12 is based on pre-inputted criteria (reference values regarding blast rate, rust removal, etc., set in advance according to the environment in which the device is operated, such as the office and ship owner supervision). This may be performed by the analysis unit 9 of the imaging unit 3, or may be performed by a person based on the results of steps S9 and S11.
 表示部4に表示された結果(表面粗度、ブラスト率、発錆部面積、除錆度、粗面処理の品質、のうち一部または全部、あるいはその他の情報)を記録したり、図示しない印刷機で印刷するなど適宜出力して(ステップS13)、検査を終了する。 The results displayed on the display unit 4 (part or all of the surface roughness, blasting rate, rusted area, degree of rust removal, quality of surface roughening, or other information) are recorded or not shown. It is output as appropriate, such as by printing with a printing machine (step S13), and the inspection ends.
 このように、本実施例の如き評価方法および評価装置では、検査に適した波長として予め特定された2波長の光の反射率を用い、NDSI解析によって表面粗度や発錆度に関する評価を行う。表面粗度または発錆度のいずれかを評価する技術であれば、これまでにも種々提案されているが、その両方を同じNDSI解析によって簡便に評価し得る技術は、本発明者の知る限り類例がない。金属表面の粗面処理の評価にあたっては、表面粗度と発錆度の両方を評価する必要がある。検査官の目視による検査は無論これを充足していたのであるが、これまでに開発されてきた機械的な評価技術では、表面粗度または発錆度のいずれかを評価する装置または方法を提供するに留まり、両方を一度に評価することはできなかった。本実施例のようにすれば、簡単な計算による両方の指標を評価し、さらにはそれらに基づいて粗面処理に関する評価そのものまでを出力することができる。 As described above, in the evaluation method and evaluation apparatus of this embodiment, the reflectance of light of two wavelengths previously specified as wavelengths suitable for inspection is used, and the surface roughness and the degree of rust are evaluated by NDSI analysis. . Various techniques for evaluating either surface roughness or rusting have been proposed so far. No analogy. In evaluating the roughening treatment of the metal surface, it is necessary to evaluate both the surface roughness and the degree of rust formation. Visual inspection by an inspector has, of course, satisfied this requirement, but the mechanical evaluation techniques that have been developed to date provide devices or methods for evaluating either surface roughness or rust formation. It was not possible to evaluate both at the same time. According to the present embodiment, it is possible to evaluate both indexes by simple calculation, and to output the evaluation of surface roughening based on them.
 また、上記の如き評価装置1では、検査対象の表面について1m×1m程度までの範囲を一度に検査することができる。これは、検査官が目視により評価する範囲と同等の範囲である。粗面処理の品質を評価するために開発された従来の装置の中には、検査対象の表面に関してごく狭い範囲しか一度に検査できない装置も存在するが、上に説明したような評価装置1であれば、一度の操作で十分に広い範囲を検査することができる。また、表面粗度や除錆度の評価にはごく単純な演算処理を行えば足りるので、ある程度大きいピクセル数の画像についてピクセル毎に演算を行ったとしても、演算や評価の結果が出るまでに要する時間はわずか(長くて数秒程度)である。よって、画像を取得すれば、その場で検査対象の粗面処理に関する評価を確認できる。このように、本実施例では、評価の精度のほか、評価項目、評価を行う範囲、評価に要する時間においても、従来の検査官の目視による検査を十分に代替し得る。 In addition, with the evaluation apparatus 1 as described above, it is possible to inspect a range of up to about 1 m x 1 m on the surface of the inspection object at once. This range is equivalent to the range visually evaluated by inspectors. Among conventional devices developed for evaluating the quality of surface roughening, there are devices that can inspect only a very narrow range of the surface to be inspected at one time. If so, a sufficiently wide range can be inspected in a single operation. In addition, evaluation of surface roughness and rust removal can be done with very simple arithmetic processing. It takes only a short time (several seconds at most). Therefore, if the image is acquired, the evaluation of the surface roughening of the inspection object can be confirmed on the spot. As described above, in this embodiment, in addition to the accuracy of evaluation, the evaluation items, the range of evaluation, and the time required for evaluation can fully replace the conventional visual inspection by an inspector.
 また、評価には特定の2波長の光のみを用いるため、必ずしも高価なハイパースペクトルカメラを利用する必要はなく、図1に示す如き評価装置1は安価に製造し得る。また、撮像部3や照射部2は、電池式の電源部6により稼働し、電源ケーブル等は不要であるので、例えば船殻構造物の内部のような検査現場にも容易に持ち込むことができ、簡便な検査が可能である。また、撮像部3は一般的なカメラ装置と同等のサイズの装置として構成でき、表示部4や操作部5はタッチパネル式のディスプレイ等の装置として構成できるので、一人でも評価装置1を現場に携行し、簡単な操作で評価を行うことができる。 In addition, since only two specific wavelengths of light are used for evaluation, it is not necessary to use an expensive hyperspectral camera, and the evaluation apparatus 1 as shown in FIG. 1 can be manufactured at low cost. In addition, since the imaging unit 3 and the irradiation unit 2 are operated by a battery-powered power supply unit 6 and do not require a power cable or the like, they can be easily brought into an inspection site such as the inside of a ship's hull structure. , a simple inspection is possible. In addition, since the imaging unit 3 can be configured as a device having the same size as a general camera device, and the display unit 4 and the operation unit 5 can be configured as devices such as a touch panel display, even one person can carry the evaluation device 1 to the site. and can be evaluated with a simple operation.
 このような本実施例の金属表面の粗面処理の評価方法および評価装置は、例えば造船の塗装に先立つブラスト作業後の検査において、現状の目視評価に代えて定量的な評価を行う技術として活用することができる。例えば粗面処理について、合格か不合格かの評価が人によって分かれるような場合に、客観的な基準を提示する方法として利用できる。あるいは、塗装作業の初心者に対する訓練や教育のためのツールとしての利用等も想定できる。訓練や教育の現場では、検査官あるいはそれに相当する知識や経験を持つ人員を都度用意することが難しい場合があるが、そういった状況下でも、検査官と同等の評価基準を提示し、もって訓練や教育に役立てることができる。 The evaluation method and evaluation apparatus for the roughening treatment of the metal surface of this embodiment can be used as a technology for performing quantitative evaluation instead of the current visual evaluation, for example, in inspections after blasting work prior to painting in shipbuilding. can do. For example, regarding surface roughening, it can be used as a method of presenting an objective standard when the evaluation of pass or fail differs depending on the person. Alternatively, it can be assumed to be used as a tool for training and education for beginners of painting work. At training and education sites, it is sometimes difficult to prepare inspectors or personnel with equivalent knowledge and experience on a case-by-case basis. It can be used for education.
 尚、上述の評価装置1の構成や評価の手順はあくまで一例であって、同様の原理にて評価を好適に実行できる限りにおいて、装置の構成や手順は適宜変更し得る。例えば、評価装置1を構成する画像作成部8や解析部9について、上では撮像部3に設けた受光部2にて受光した光から画像を作成し、これを解析する場合を説明したが、例えば外部の装置から検査に用いる画像データを画像作成部8にて取得し、これを解析部9が解析するようにしてもよい。この場合、評価装置1は、少なくとも画像生成部8と解析部9とを備えていれば十分である。また、評価の工程について、上では説明の便宜上、表面粗度に関する評価手順と発錆度に関する評価を並行して行うことを想定して説明したが、これらを順に個別に実行するようにしてもよい。 It should be noted that the configuration of the evaluation device 1 and the procedure of evaluation described above are only examples, and the configuration of the device and the procedure can be changed as appropriate as long as the evaluation can be suitably performed on the same principle. For example, regarding the image creation unit 8 and the analysis unit 9 that constitute the evaluation device 1, the case where an image is created from the light received by the light receiving unit 2 provided in the imaging unit 3 and analyzed has been described above. For example, image data used for inspection may be acquired by the image creating unit 8 from an external device and analyzed by the analysis unit 9 . In this case, it is sufficient for the evaluation device 1 to include at least the image generation section 8 and the analysis section 9 . In addition, for the convenience of explanation, the evaluation process was described above assuming that the evaluation procedure for the surface roughness and the evaluation for the degree of rusting were performed in parallel. good.
 以上のように、上記本実施例の金属表面の粗面処理の評価方法においては、粗面処理を施された検査対象の表面の画像データを取得するステップS2と、前記画像データに基づき、予め選定された2つの波長の光に関し、前記画像データの各ピクセルにおけるNDSI値を算出するステップS7と、前記NDSI値に基づき、検査対象の粗面処理に関する評価を行うステップS8~S12とを実行する。このようにすれば、従来の検査官の目視による検査を代替し、客観的な評価を行うことができる。 As described above, in the evaluation method of the roughening treatment of the metal surface of the present embodiment, the step S2 of acquiring the image data of the surface of the object to be inspected which has undergone the roughening treatment; Step S7 of calculating the NDSI value in each pixel of the image data with respect to the light of the selected two wavelengths, and Steps S8 to S12 of evaluating the rough surface treatment of the inspection object based on the NDSI value. . In this way, an objective evaluation can be performed in place of the conventional visual inspection by an inspector.
 上記実施例において、NDSI値の算出に用いる光の波長は、次の条件に基づき選定することができる。このようにすれば、金属表面の粗面処理に関し、正確で精度の高い評価を行うことができる。
条件1)表面粗度の大小に対し、反射率の大小が正に相関していること。
条件2)条件1を満たした上で、2波長の反射光のうち、一方は検査対象の表面粗度による反射率の振れ幅がなるべく小さく、他方はなるべく大きいこと。
In the above embodiment, the wavelength of light used for calculating the NDSI value can be selected based on the following conditions. In this way, accurate and highly accurate evaluation can be performed regarding the roughening treatment of the metal surface.
Condition 1) The magnitude of reflectance is positively correlated with the magnitude of surface roughness.
Condition 2) In addition to satisfying condition 1, one of the two wavelengths of reflected light should have as little variation in reflectance as possible due to the surface roughness of the object to be inspected, and the other should have as large a variation as possible.
 上記実施例においては、取得された画像データにおいて、対象とするピクセルのNDSI値の平均値を算出し、該平均値に基づいて表面粗度に関する評価を行うことができる。 In the above embodiment, the average value of the NDSI values of the target pixels in the acquired image data can be calculated, and the surface roughness can be evaluated based on the average value.
 上記実施例においては、取得された画像データにおいて、対象とする各ピクセルのNDSI値を予め設定された閾値と参照し、発錆に関する評価を行うことができる。 In the above embodiment, rusting can be evaluated by referring to the NDSI value of each target pixel in the acquired image data as a preset threshold value.
 上記実施例においては、取得された画像データにおいて評価の対象とする範囲を選択し、粗面処理に関する評価を選択された前記範囲内で行うことができる。 In the above embodiment, a range to be evaluated can be selected in the acquired image data, and evaluation of surface roughening can be performed within the selected range.
 また、上記実施例の金属表面の粗面処理の評価装置1は、少なくとも予め選定された前記2つの波長の光に基づき画像データを作成する画像作成部8と、前記画像データに基づきNDSI解析を行う解析部9とを備え、上述の金属表面の粗面処理の評価方法を実行可能に構成されている。このようにすれば、簡便な構成の装置により、上述の作用効果を奏することができる。 Further, the apparatus 1 for evaluating rough surface treatment of a metal surface of the above embodiment includes an image creating unit 8 for creating image data based on light of at least the two wavelengths selected in advance, and an NDSI analysis based on the image data. and an analysis unit 9 for performing the above-described method for evaluating the roughening of the metal surface. In this way, the above effects can be achieved with a device having a simple configuration.
 したがって、上記本実施例によれば、金属表面の粗面処理を簡便且つ好適に評価し得る。 Therefore, according to the present embodiment, the roughening treatment of the metal surface can be easily and favorably evaluated.
 尚、本開示において説明した金属表面の粗面処理の評価方法および評価装置は、上述の実施例にのみ限定されるものではなく、本発明の要旨を逸脱しない範囲内において種々変更を加え得ることは勿論である。 It should be noted that the evaluation method and evaluation apparatus for roughening of a metal surface described in the present disclosure are not limited to the above-described embodiments, and various modifications can be made without departing from the gist of the present invention. is of course.
  1  評価装置
  2  照射部
  3  撮像部
  4  表示部
  5  操作部
  6  電源部
  7  受光部
  8  画像作成部
  9  解析部
1 evaluation device 2 irradiation unit 3 imaging unit 4 display unit 5 operation unit 6 power supply unit 7 light receiving unit 8 image creation unit 9 analysis unit

Claims (8)

  1.  粗面処理を施された検査対象の表面の画像データを取得するステップと、
     前記画像データに基づき、予め選定された2つの波長の光に関し、前記画像データの各ピクセルにおけるNDSI値を算出するステップと、
     前記NDSI値に基づき、検査対象の粗面処理に関する評価を行うステップとを実行する、金属表面の粗面処理の評価方法。
    acquiring image data of a roughened surface of the inspection object;
    calculating an NDSI value at each pixel of the image data for light of two preselected wavelengths based on the image data;
    A method for evaluating roughening of a metal surface, comprising the step of evaluating the roughening of an object to be inspected based on the NDSI value.
  2.  NDSI値の算出に用いる光の波長は、次の条件に基づき選定される、請求項1に記載の金属表面の粗面処理の評価方法。
    条件1)表面粗度の大小に対し、反射率の大小が正に相関していること。
    条件2)条件1を満たした上で、2波長の反射光のうち、一方は検査対象の表面粗度による反射率の振れ幅がなるべく小さく、他方はなるべく大きいこと。
    2. The method for evaluating roughening of a metal surface according to claim 1, wherein the wavelength of light used for calculating the NDSI value is selected based on the following conditions.
    Condition 1) The magnitude of reflectance is positively correlated with the magnitude of surface roughness.
    Condition 2) In addition to satisfying condition 1, one of the two wavelengths of reflected light should have as little variation in reflectance as possible due to the surface roughness of the object to be inspected, and the other should have as large a variation as possible.
  3.  取得された画像データにおいて、対象とするピクセルのNDSI値の平均値を算出し、該平均値に基づいて表面粗度に関する評価を行う、請求項1に記載の金属表面の粗面処理の評価方法。 2. The method of evaluating roughening of a metal surface according to claim 1, wherein an average value of NDSI values of target pixels is calculated in the acquired image data, and the surface roughness is evaluated based on the average value. .
  4.  取得された画像データにおいて、対象とするピクセルのNDSI値の平均値を算出し、該平均値に基づいて表面粗度に関する評価を行う、請求項2に記載の金属表面の粗面処理の評価方法。 3. The method of evaluating roughening of a metal surface according to claim 2, wherein the average value of the NDSI values of the target pixels in the acquired image data is calculated, and the surface roughness is evaluated based on the average value. .
  5.  取得された画像データにおいて、対象とする各ピクセルのNDSI値を予め設定された閾値と参照し、発錆に関する評価を行う、請求項1~4のいずれか一項に記載の金属表面の粗面処理の評価方法。 The rough surface of the metal surface according to any one of claims 1 to 4, wherein the NDSI value of each target pixel in the acquired image data is referred to as a preset threshold value to evaluate rusting. How the treatment is evaluated.
  6.  取得された画像データにおいて評価の対象とする範囲を選択し、粗面処理に関する評価を選択された前記範囲内で行う、請求項1~4のいずれか一項に記載の金属表面の粗面処理の評価方法。 Roughening of a metal surface according to any one of claims 1 to 4, wherein a range to be evaluated is selected in the acquired image data, and evaluation of surface roughening is performed within the selected range. evaluation method.
  7.  取得された画像データにおいて評価の対象とする範囲を選択し、粗面処理に関する評価を選択された前記範囲内で行う、請求項5に記載の金属表面の粗面処理の評価方法。 A method for evaluating roughening of a metal surface according to claim 5, wherein a range to be evaluated is selected in the acquired image data, and the evaluation of surface roughening is performed within the selected range.
  8.  少なくとも予め選定された前記2つの波長の光に基づき画像データを作成する画像作成部と、
     前記画像データに基づきNDSI解析を行う解析部とを備え、
     請求項1または2に記載の金属表面の粗面処理の評価方法を実行可能に構成されている、金属表面の粗面処理の評価装置。
    an image creation unit that creates image data based on at least the two wavelengths of light selected in advance;
    an analysis unit that performs NDSI analysis based on the image data,
    3. A metal surface roughening evaluation apparatus configured to be capable of executing the metal surface roughening evaluation method according to claim 1 or 2.
PCT/JP2022/009211 2021-03-25 2022-03-03 Evaluation method and evaluation device for surface roughening of metal surface WO2022202198A1 (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2023210503A1 (en) * 2022-04-25 2023-11-02 国立大学法人九州大学 Blast state evaluation device, blast state evaluation system, blast state evaluation method, and blast state evaluation program

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS56120904A (en) * 1980-02-29 1981-09-22 Chugoku Toryo Kk Measuring method for rate of removal of coating film
JPS5724810A (en) * 1980-06-11 1982-02-09 Gen Electric Method of and apparatus for measuring contour of surface
US4511800A (en) * 1983-03-28 1985-04-16 Rca Corporation Optical reflectance method for determining the surface roughness of materials in semiconductor processing
JP2005241316A (en) * 2004-02-25 2005-09-08 Nec Corp Metal corrosion degree measuring method and device
JP2018146567A (en) * 2017-03-03 2018-09-20 株式会社神戸製鋼所 Surface quality detection method

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP5724810B2 (en) 2011-09-16 2015-05-27 株式会社湯山製作所 Liquid discharge mechanism and dispensing device
JP6969461B2 (en) 2018-03-16 2021-11-24 Jfeエンジニアリング株式会社 Base treatment inspection equipment and base treatment inspection method

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS56120904A (en) * 1980-02-29 1981-09-22 Chugoku Toryo Kk Measuring method for rate of removal of coating film
JPS5724810A (en) * 1980-06-11 1982-02-09 Gen Electric Method of and apparatus for measuring contour of surface
US4511800A (en) * 1983-03-28 1985-04-16 Rca Corporation Optical reflectance method for determining the surface roughness of materials in semiconductor processing
JP2005241316A (en) * 2004-02-25 2005-09-08 Nec Corp Metal corrosion degree measuring method and device
JP2018146567A (en) * 2017-03-03 2018-09-20 株式会社神戸製鋼所 Surface quality detection method

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2023210503A1 (en) * 2022-04-25 2023-11-02 国立大学法人九州大学 Blast state evaluation device, blast state evaluation system, blast state evaluation method, and blast state evaluation program

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