JP5218379B2 - Degreasing degree determination device - Google Patents

Description

  The present invention relates to a degreasing degree determination device, and more particularly to a technique for determining the degree of degreasing on the surface of a measurement object by irradiating the surface of the measurement object with light and detecting fluorescence from the surface of the measurement object.

  Conventionally, various methods for detecting the degree of degreasing or dirt on the surface of an object to be measured have been proposed.

  The first is a method that utilizes the water wetting phenomenon. This is a method of detecting a place repelled from the surface of the processed product as an unwashed portion by spraying pure water on the entire processed product after degreasing.

  The second is a total organic carbon concentration measurement method. This is to estimate the oil concentration from organic carbon in water or cleaning liquid. The dirt remaining in the cleaning solution is extracted, and the management of the cleaning solution or the cleaning degree of the cleaned metal is evaluated.

  The third is a surface cleanliness analysis method. This is a method of measuring elements on the target surface in an ultra vacuum.

  The fourth is a method for measuring the lubricating oil film thickness. This measures the oil film thickness for control of the internal combustion engine. For the purpose of quantitatively detecting the oil film thickness by laser-induced fluorescence, a fluorescent additive is mixed into the oil in order to increase detection sensitivity. The oil film thickness can be accurately read by the fluorescence intensity.

  The fifth is an oil film thickness measuring method. This is because there is continuously a new known oil film in which no natural degradation or the like has occurred, and ultraviolet light is incident on the oil film surface as excitation light, and the integrated value of the fluorescence intensity generated from the oil film surface of 100 μm or less is a metal. The amount of oil film applied to the surface is estimated. For the evaluation of the oil film to be measured, a calibration curve obtained by measuring the correlation between the oil film thickness and the fluorescence intensity is used.

  The sixth is a degreasing surface oil content measuring method. In this method, ultraviolet / visible light is incident as excitation light on a very thin oil film having a thickness of several μm or less, and fluorescence intensity is measured. In order to evaluate the degree of cleaning, the degreased state is extracted by using a calibration curve between the fluorescence intensity and the oil film amount.

JP 2009-128263 A Japanese Patent Laid-Open No. 10-177016 JP 2009-103630 A Japanese Patent No. 3508852 JP-A-9-210908 Patent No. 2915294 Japanese Patent Laid-Open No. 5-118898 JP-A-57-86743

  As a measure of the degreasing state, there is “wetability” of water. In the visual inspection of the “wetting property” of the processed product after degreasing before painting the processed product, there is an empirical rule that passes “wetting property” of 80% or more, but there is no quantitative property. For this reason, it can be judged only artificially whether the degreasing state is sufficient, and abundant technical experience is required. In addition, there is a problem that the cause of the failure that occurs in the production line cannot be determined.

  In addition, since the assembled processed product does not always have a constant part, even if the front and rear weights are measured, the error in cleaning degree evaluation becomes large, and it is difficult to evaluate the processed product after degreasing with a small remaining amount. Further, it is not practical because the cleaning liquid and the container must be replaced each time they are measured. Although the deterioration of the oil can be evaluated, the degreasing state of the rust preventive oil adhering to a minute amount cannot be measured.

  In addition, measurement of the surface of a processed product immediately after degreasing requires a large and expensive system, and generally requires measurement in an ultra-vacuum or vacuum state. Therefore, it is not suitable for checking all products. For example, a car body before painting of an automobile has a total length of about 5 m, and the amount of investment for preparing a vacuum facility environment is high. In addition, it takes time for the elements adhering to the surface to measure the entire surface of the workpiece, making it difficult to apply to the production line.

  In addition, when a fluorescent additive is mixed in the rust-preventing oil, another development is required for the performance of the rust-preventing oil not to change, and additional development costs are required. It is desirable to have a method that can maintain sensitivity with only the components of the current rust prevention oil as much as possible.

  Further, simply detecting fluorescence and comparing it with a calibration curve cannot eliminate the influence of moisture on the surface of the workpiece and the influence on the shape.

  The present invention has been made in view of the above-described problems of the prior art, and on a quantitative basis, the surface of the object to be measured is not affected by the procedure of the manufacturing process or individual weight, regardless of the nature of the oil content. An apparatus and a method capable of automatically detecting a degreasing state are provided.

The present invention is a degreasing degree determination apparatus, comprising: a light source that irradiates light on the surface of the object to be measured; a detection unit that detects fluorescence from the surface of the object to be measured based on the light; and a spatial distribution of the intensity distribution of the fluorescence. An operation for determining the degree of degreasing on the surface of the object to be measured using at least two indices, a first index obtained by pattern analysis and a second index obtained by statistical analysis of the fluorescence intensity distribution. Means.

  In one embodiment of the present invention, the analysis of the spatial pattern is a spatial frequency analysis (eg, Fourier analysis or wavelet analysis), or a geometric analysis. Each has a power spectrum, wavelet coefficients, or geometric quantities. Statistical analysis is a coefficient of variation which is an average value, standard deviation, or a ratio thereof.

  In the present invention, the homogeneity of degreasing is determined using an index obtained by analyzing the spatial distribution of the fluorescence intensity distribution. Spatial pattern analysis includes power spectra, wavelet coefficients, and geometric quantities. The power spectrum and wavelet coefficients change according to the uniformity of degreasing. Naturally, geometrical quantities such as the diameter of the dirt particles, the distance between the centers of gravity, and the area of the dirt also change. Therefore, the degree of degreasing can be quantitatively evaluated by analyzing the spatial pattern.

  On the other hand, the index obtained by statistical analysis of the fluorescence intensity distribution includes the average value and standard deviation of the fluorescence intensity, and these values change according to the degreasing uniformity. Therefore, the degree of degreasing can be evaluated with higher accuracy by using not only the index obtained by analysis of the spatial pattern but also the index obtained by statistical analysis in addition to this.

  When using the average value or standard deviation, these values vary depending on whether water is present or absent on the surface of the object to be measured, but the coefficient of variation (= standard deviation) is the ratio between the average value and the standard deviation. / Average value) can be used as an index to eliminate fluctuations due to the presence or absence of water. That is, by using the coefficient of variation as an index, it is possible to accurately determine the degree of degreasing regardless of the state of the surface of the object to be measured.

  According to the present invention, it is possible to automatically detect the degreasing state of the surface of the object to be measured regardless of the nature of the oil content, and the accuracy and efficiency are remarkably improved as compared with the determination of the degreasing state by visual observation.

It is a block diagram of embodiment. It is a figure which shows the relationship between wettability and fluorescence intensity (luminance). FIG. 3 is a partially enlarged view of FIG. 2. It is a figure which shows wettability and oil film thickness distribution (standard deviation). It is a figure which shows the luminance histogram of wettability 50% and 100%. It is a figure which shows the luminance value of each sample. It is a figure which shows the relationship between the wettability and the gradient of a power spectrum. It is a figure which shows the relationship between wettability and power spectral density. It is a figure which shows the average intensity | strength and standard deviation of each sample. It is a figure which shows each sample (with water and without water) and a coefficient of variation (standard deviation / average value). It is a figure which shows the relationship between the gradient of a power spectrum, and a variation coefficient. It is a figure which shows a mother wavelet. It is a figure which shows the relationship between a wavelet coefficient (average amount) and average intensity | strength (average luminance value). It is a figure which shows the relationship between wettability and a wavelet coefficient. It is a figure which shows the relationship between a power spectrum density and a variation coefficient. It is a figure which shows the relationship between a wavelet coefficient and a variation coefficient. It is a figure which shows the relationship between the gradient of a power spectrum, and an area ratio. It is a figure which shows the relationship between a wavelet coefficient and an area ratio. It is a figure which shows the relationship between an area rate and a variation coefficient. It is a figure which shows the relationship between an area ratio and average intensity | strength. It is a figure which shows the relationship between the gradient of a power spectrum, and average intensity | strength. It is a figure which shows the relationship between a power spectrum density and average intensity | strength. It is a figure which shows the relationship between a wavelet coefficient and average intensity | strength. It is a figure which shows the relationship between wettability and an area ratio. It is a figure which shows the relationship between a wavelet coefficient and a variation coefficient. It is a figure which shows the correction method when the sample is inclined. It is a figure which shows the correction method in case a sample has a curvature. It is a figure which shows the angle of a sample, and Bin / Bout. It is a figure which shows the time series determination of a degreasing degree. It is a figure which shows the time change of the gradient of a power spectrum and the fluorescence intensity in the system of FIG. It is a figure which shows the other time series determination of a degreasing degree. It is a figure which shows the time change of the gradient of a power spectrum and the fluorescence intensity in the system of FIG.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

<First Embodiment>
In FIG. 1, the whole block diagram of the degreasing degree determination apparatus in this embodiment is shown. Laser light (248 nm, 300 mJ) emitted from the KrF excimer laser 14 is irradiated onto the sample 30 through the mirror 16, the aperture 18, the mirror 20, and the silica glasses 22 and 26. The silica glasses 22 and 26 are provided with beam diffusers 24 and 28, respectively, for adjusting the irradiation energy by diffusing the beams. For example, the reflectance of the silica glass 22 is 10%, the irradiation energy is 30 mJ, the reflectance of the silica glass 26 is 10%, and the irradiation energy is 3 mJ. The size of the laser beam irradiated on the sample 30 is, for example, 16 mm × 20 mm. Laser light irradiation from the excimer laser 14 is controlled by the pulse generator 12 supplying a drive pulse to the excimer laser 14 in accordance with a control command from the controller 10. The fluorescence from the sample 30 is measured by a CCD camera (image intensifying CCD camera) 32. An optical cut filter is attached to the UV lens of the CCD camera 32. The sample 30 is fixed to a slider, moved 22 mm for each measurement, and fluorescence is measured at a total of 14 locations, 7 locations up and down. The measurement wavelength of fluorescence is 270 nm to 380 nm. The measurement result obtained by the CCD camera 32 is supplied to the controller 10 and analyzed. Of course, the measurement result of the CCD camera 32 may be separately supplied to a computer and analyzed by the computer. The controller 10 or the computer determines the degree of degreasing of the sample 30 based on the measurement result of the CCD camera 32.

Sample 30 is a steel sample,
(1) The rust preventive oil is applied to the entire surface (2) The oil is applied to a part of the region (3) The three types of the degreased state where the oil is not applied, Wetability relationship is area ratio (1) 0%
(2) 50%
(3) 100%
It is set to become.

  FIG. 2 shows the measurement results of three types of samples 30. The measurement result represents the average value of all 14 images. When the sample (1) and the sample (2) are compared, the ratio of the values is 50 times, and it can be seen that the determination can be made quantitatively.

  FIG. 3 shows the results of wettability of 50% (sample (2)) and 100% (sample (3)). From the samples with different wettability, the fluorescence intensity ratio is 1.6 times, and the standard deviation is 33.1 for sample (2) and 9.0 for sample (3).

  FIG. 4 shows the difference in standard deviation shown in FIG. 3 as a distribution. It turns out that the place where there is much remaining amount of oil can be judged intuitively.

  FIG. 5 shows histograms of sample (2) and sample (3). The difference from the reference can be seen, which can be one of the judgment materials.

  In general, unless an oil film is applied to the metal surface intentionally and using skillful means, the oil film / dirt pattern on the metal surface is uneven. When the fluorescence is generated from the light, the generated fluorescence spreads in its intensity distribution, and a bias appears. By using the standard deviation, the nonuniformity of the oil film / dirt can be shown as a quantitative value, and the degree of degreasing can be distinguished. Further, even if the properties of the oil change, the baseline of the luminance value only rises, so that the same measurement is possible.

Second Embodiment
Using steel samples, prepare three types: (1) coated with rust-preventive oil, (2) washed with water and degreased with acetone, and (3) washed with water and degreased with acetone. Reproduced until degreasing. The laser output is 300 mJ, the sample is irradiated, the size of the laser that strikes the sample is 16 × 20 mm, and the energy is 3 mJ. The fluorescence intensity is measured by a CCD camera 32 in which an optical cut filter is attached to a UV lens.

  FIG. 6 shows the results of the sample when irradiated with a laser having an excitation wavelength of 248 nm. The measurement result represents the average value of the images in the inspection area. In the figure, a represents (1) a rust-preventive oil-coated oil, (b) (2) water degreased with acetone, and (3) water (3) degreased with water and then polished. For comparison, the cases of wettability 0%, 50%, and 100% shown in FIG. Comparing a and i, the ratio of the values is 40 times. That is, it can be seen that the difference in the degree of degreasing between the one coated with rust preventive oil and the acetone is clear. Moreover, since a difference is seen with a and o, it turns out that it is not a complete degreasing state.

  From the above, the degree of degreasing can be evaluated by using the average strength.

<Third Embodiment>
The apparatus in the present embodiment further includes a result display apparatus in addition to the configuration shown in FIG. After determining the degree of degreasing with the controller 10 or computer shown in FIG. 1, the result is displayed on the display device. The determination method by the controller 10 or the computer is histogram distribution, standard deviation, spatio-temporal difference, spatial frequency analysis (Fourier analysis or wavelet analysis), and the like. By applying any one of the determination algorithms, it is possible to determine the degree of degreasing on the surface of the processed product on which a very small amount of non-uniform oil film is deposited after degreasing.

  For example, the gradient of the power spectrum extracted from the spatial data by spatial frequency analysis can be used, and the average value and standard deviation extracted from the spatial data by statistical analysis can be used. As for the gradient of the power spectrum, the fact that the gradient becomes asymptotic to 1 / f fluctuation as the stain approaches the natural origin is used. At this time, the spatial data can obtain an objective determination result by using image data or a time-series development map.

  As an evaluation method, the accuracy is high when the area ratio is used to confirm whether it is completely degreased. The area ratio is the ratio of the area of the non-stained portion to the total area of the sample 30. When calculating the area ratio, the area can be specified by edge detection based on a spatial differential method and binarized image analysis. When using spatial frequency analysis, it is desirable that the spatial resolution has 256 × 256 pixel image size or 256 × 256 or more measurement points. However, when spatial differential analysis is used, there is no influence on the analysis by resolution. The determination method using the area ratio will be described later.

  When quantitatively determining the degree of degreasing, the controller 10 or the computer performs analysis by fixing a threshold value according to a criterion for determination for each remaining amount and oil distribution. The analysis method includes statistical processing, image spatial frequency analysis, and the like, and is determined by one of the processing methods according to the difference in measurement place and area.

  Hereinafter, a case where spatial frequency analysis (Fourier analysis or wavelet analysis) is used will be described.

  When oil is attached, it becomes patchy. Therefore, when the horizontal axis is plotted as the spatial frequency (1 / pixel) and the vertical axis is plotted as the power spectrum, the power spectrum decreases to the right, that is, the power spectrum decreases as the spatial frequency increases. The power spectrum becomes almost horizontal when there is little dirt and it is uniform. Therefore, the gradient of the power spectrum is calculated by the method of least squares, and when this gradient becomes smaller than the determination criterion, it is determined that the degreasing state has been reached.

  FIG. 7 shows a case where various samples are mapped by wettability and power spectrum gradient. The wettability was 0%, 20%, 40%, 60%, 80%, 100%, and Super 100 (S100)%. Here, the super 100% means a state in which the degree of degreasing is further advanced than the 100% degreasing state. In each wettability, the gradient of the power spectrum is shown for each case where the surface of the sample is in a dry state where water is not present and where water is present. The state in which water is present is specifically immediately after washing, and the state in which no water is present is a state dried by nitrogen spray from the state immediately after washing. From the figure, it can be seen that as the degree of degreasing increases, the gradient of the power spectrum decreases and approaches zero. Therefore, the degreasing degree can be quantitatively evaluated by providing a reference threshold value and comparing the gradient of the power spectrum with the threshold value.

  FIG. 8 shows a case where various samples are mapped by wettability and power spectral density. Here, the power spectrum density means an integrated value up to a predetermined spatial frequency of the power spectrum. The predetermined spatial frequency is a frequency that is considered to be noise. As shown in the figure, when the degree of degreasing increases, the power spectral density tends to decrease. Therefore, the degreasing degree can be quantitatively evaluated by providing a reference threshold value and comparing the power spectral density with the threshold value.

<Fourth embodiment>
In the present embodiment, a determination method that takes into account the influence of the presence or absence of moisture is shown. Using a steel sample, the state after degreasing is measured with an alkaline cleaner used in the production line. Both the surface state including moisture immediately after cleaning and the surface state after drying by nitrogen spray from the state are measured.

  FIG. 9 shows the result. The wettability is 40%, 60%, 80%, 100%, and indicates the average brightness and standard deviation. Comparing the distribution images when there is moisture after degreasing and when it is dried, the sample with moisture has higher fluorescence intensity. Therefore, it cannot be simply compared with the luminance average or standard deviation, and it is necessary to use an index that excludes the influence of the presence or absence of moisture. Therefore, in this embodiment, the degree of degreasing is evaluated using the coefficient of variation = standard deviation / average value. In addition, when the distribution according to the presence or absence of moisture is observed for each wettability, it is found that the distribution pattern is similar although there is a difference in strength depending on the presence or absence of moisture.

  FIG. 10 shows the relationship between wettability and coefficient of variation (= standard deviation / average value). As shown in the figure, it can be seen that the same tendency is shown regardless of the presence or absence of water when evaluated by the coefficient of variation, that is, the ratio between the standard deviation and the average value. As a result, if the evaluation is performed by the coefficient of variation obtained by dividing the standard deviation of the image obtained in the degreased state immediately after washing by the average value, the oil component present can be detected regardless of the presence or absence of moisture. The degree of degreasing can be compared relatively without the influence.

FIG. 11 shows the mapping result when the horizontal axis represents the power spectrum gradient and the vertical axis represents 1 / variation coefficient. The wettability is 20%, 40%, 60%, 80%, 100%, and super 100%. In the figure, the image is divided into four regions according to the gradient of the power spectrum and the magnitude of 1 / variation coefficient. That is,
(I) A region where the gradient of the power spectrum is less than or equal to a predetermined value and 1 / variation coefficient is less than or equal to a predetermined value (II) A region where the gradient of the power spectrum is less than or equal to a predetermined value and the 1 / variation coefficient exceeds a predetermined value (III ) Region where the power spectrum gradient exceeds a predetermined value and the 1 / variation coefficient is equal to or less than the predetermined value (IV) The case where the power spectrum gradient exceeds the predetermined value and the 1 / variation coefficient exceeds the predetermined value. Area (I) is an area where dispersed dirt is generated, area (II) is a clean area, area (III) is an area where distributed dirt is generated, and (IV) is a thin film dirt. It is an area. Here, the dispersed dirt is a state in which dirt is present almost uniformly. In addition, distributed dirt is normal dirt in which various sizes of dirt are present. Thin film dirt is a state in which dirt is thin and uniformly present. In general, when rust-preventing oil is applied and running water is degreased with a liquid such as an organic solvent, an alkaline solvent, or an acidic solvent, the oil remains mainly as distributed dirt. Even if the gradient of the power spectrum is less than or equal to a predetermined value, if the 1 / variation coefficient is less than or equal to the predetermined value, there is a possibility that dispersion contamination has occurred. On the other hand, the wettability 100% and the super 100% are mapped to the clean region of the region (II), and the wettability 20%, 40%, 60%, and 80% are all mapped to the distribution stain.

  Therefore, the degreasing degree can be more accurately evaluated by using both the power spectrum gradient and the coefficient of variation. Based on the mapping result, the controller 10 or the computer determines whether the degreasing degree of the object to be measured is “clean” or, more specifically, “clean”, “thin film dirt”, “dispersed dirt”, “distribution”. It is possible to determine whether it is “dirt” and display it on the display device. The determination result may be displayed separately for “clean” and other than that. The former can be displayed as “degreasing OK”, and the latter can be displayed as “degreasing NG”.

<Fifth Embodiment>
In the above embodiment, the degree of degreasing is determined using the gradient of the power spectrum, but the degree of degreasing can also be determined using wavelet coefficients.

  In wavelet analysis, a signal is expressed by a finite length function called a mother wavelet. By scaling (extending / contracting) and translating (translating) the mother wavelet, waveforms of various scales similar to this are extracted without losing spatial axis information. The definition formula is as follows.

W (a, b) in the above equation is a wavelet coefficient and indicates the strength of similarity with the mother wavelet Ψ (t). The wavelet coefficient W has two pieces of information, namely scale information and spatial information, in addition to its own information.

  FIG. 12 shows an example (Morlet) of the mother wavelet used in this embodiment. FIG. 13 shows a mapping result of wavelet coefficients and average luminance values when wavelet analysis is performed on each wettability sample. As the degree of degreasing increases to 80%, 100%, 100% super, the wavelet coefficient decreases. In addition, the average luminance value also decreases relatively. FIG. 14 shows the relationship between each wettability and the wavelet coefficient. In the figure, the wavelet coefficient sharply decreases with a wettability of 60% as a boundary. Therefore, the degree of degreasing can be accurately evaluated by comparing the wavelet coefficient with a predetermined threshold value.

<Sixth Embodiment>
FIG. 15 shows the relationship between the power spectral density and the coefficient of variation (= standard deviation / average value). In the figure, the horizontal axis represents power spectral density, and the vertical axis represents 1 / variation coefficient. When wetting 40%, 60%, 80%, 100%, and 100% super samples are plotted, 40%, 60%, and 80% are plotted in the “residual” area, and 100% super is the “clean” area. Is plotted in Here, the “residual” region is defined as a region in which the power spectral density is larger than a predetermined threshold and the 1 / variation coefficient is smaller than the predetermined threshold. The “clean” region is defined as a region where the power spectral density is smaller than the threshold and the 1 / variation coefficient is larger than the threshold. As shown in the figure, the “residual” region and the “clean” region are at opposite positions on the two-dimensional map, and both regions can be clearly distinguished. Accordingly, the degree of degreasing can be accurately evaluated by comparing the power spectral density with a predetermined threshold and comparing the coefficient of variation (or 1 / variation coefficient) with the predetermined threshold. The controller 10 or the computer can determine whether the object to be measured is “clean” or “residual” based on the result of FIG. 15 and display the result on the display device.

<Seventh embodiment>
FIG. 16 shows the relationship between the wavelet coefficient and the variation coefficient (= standard deviation / average value). In the figure, the horizontal axis is the wavelet coefficient, and the vertical axis is the 1 / variation coefficient. If wetability samples of 40%, 60%, 80%, 100% and super 100% are plotted, 40% and 60% are plotted in the “residual” area, and 100% and super 100% are “clean”. Is plotted in the region. Here, the “residual” region is defined as a region where the wavelet coefficient is larger than a predetermined threshold and the 1 / variation coefficient is smaller than the predetermined threshold. The “clean” region is defined as a region where the wavelet coefficient is smaller than the threshold and the 1 / variation coefficient is larger than the threshold. As shown in the figure, the “residual” region and the “clean” region are at opposite positions on the two-dimensional map, and both regions can be clearly distinguished. Therefore, the degree of degreasing can be accurately evaluated by comparing the magnitude of the wavelet coefficient with a predetermined threshold and comparing the coefficient of variation (or 1 / variation coefficient) with the predetermined threshold.

<Eighth Embodiment>
FIG. 17 shows the relationship between the gradient of the power spectrum and the area ratio. In the figure, the horizontal axis represents the power spectrum gradient and the vertical axis represents the area ratio. The area ratio is the ratio of the area of the unstained part to the total area of the sample. When wetting samples of 40%, 60%, 80%, 100% and 100% super are plotted, 40% and 60% are plotted in the “residual” area, and 100% and 100% super are the “clean” area. Is plotted in Here, the “residual” region is defined as a region where the gradient of the power spectrum is larger than a predetermined threshold and the 1 / variation coefficient is smaller than the predetermined threshold. The “clean” region is defined as a region where the gradient of the power spectrum is smaller than the threshold and the 1 / variation coefficient is larger than the threshold.

  As the area ratio is larger, it is possible to determine that the degree of degreasing is better because the non-dirty part is larger. However, using a two-dimensional map as shown in FIG. By considering the gradient, the degree of degreasing can be determined more clearly.

<Ninth Embodiment>
FIG. 18 shows the relationship between the wavelet coefficient and the area ratio. In the figure, the horizontal axis is the wavelet coefficient, and the vertical axis is the area ratio. When wetting samples of 40%, 60%, 80%, 100% and 100% super are plotted, 40% and 60% are plotted in the “residual” area, and 100% and 100% super are the “clean” area. Is plotted in Here, the “residual” region is defined as a region having a wavelet coefficient larger than a predetermined threshold and an area ratio smaller than the predetermined threshold. The “clean” region is defined as a region having a wavelet coefficient smaller than a threshold value and an area ratio larger than the threshold value.

  From the figure, the degree of degreasing can be accurately evaluated by comparing the wavelet coefficient with a predetermined threshold and comparing the area ratio with the predetermined threshold.

<Tenth Embodiment>
FIG. 19 shows the relationship between the area ratio and the coefficient of variation. In the figure, the horizontal axis represents the area ratio, and the vertical axis represents 1 / variation coefficient. When wetting samples of 40%, 60%, 80%, 100% and 100% super are plotted, 40% and 60% are plotted in the “residual” area, and 100% and 100% super are the “clean” area. Is plotted in Here, the “residual” region is defined as a region having an area ratio smaller than a predetermined threshold and 1 / variation coefficient smaller than the predetermined threshold. A “clean” region is defined as a region having an area ratio smaller than a threshold value and 1 / variation coefficient larger than a threshold value.

  From the figure, the degree of degreasing can be accurately evaluated by comparing the area ratio with a predetermined threshold value and comparing the coefficient of variation with a predetermined threshold value.

<Eleventh embodiment>
FIG. 20 shows the relationship between the area ratio and average intensity (average luminance value). In the figure, the horizontal axis represents the area ratio, and the vertical axis represents the average intensity. When wetting samples of 40%, 60%, 80%, 100% and 100% super are plotted, 40% and 60% are plotted in the “residual” area, and 80%, 100% and 100% super are all Plotted in the “clean” area. Here, the “residual” region is defined as a region having an area ratio smaller than a predetermined threshold and an average intensity larger than the predetermined threshold. The “clean” region is defined as a region having an area ratio larger than a threshold value and an average intensity smaller than the threshold value.

  From the figure, the degree of degreasing can be accurately evaluated by comparing the area ratio with a predetermined threshold value and comparing the average strength with a predetermined threshold value.

<Twelfth embodiment>
FIG. 21 shows the relationship between the gradient of the power spectrum and the average intensity. In the figure, the horizontal axis represents the gradient of the power spectrum, and the vertical axis represents the average intensity. When wetting samples of 40%, 60%, 80%, 100% and 100% super are plotted, 40% and 60% are plotted in the “residual” area, and 100% and 100% super are the “clean” area. Is plotted in Here, the “residual” region is defined as a region where the gradient of the power spectrum is larger than a predetermined threshold and the average intensity is larger than the predetermined threshold. A “clean” region is defined as a region where the slope of the power spectrum is less than the threshold and the average intensity is less than the threshold.

  From the figure, the degree of degreasing can be accurately evaluated by comparing the magnitude of the power spectrum with a predetermined threshold value and comparing the average intensity with a predetermined threshold value.

<13th Embodiment>
FIG. 22 shows the relationship between power spectral density and average intensity. In the figure, the horizontal axis represents power spectral density and the vertical axis represents average intensity. When wetting 40%, 60%, 80%, 100%, and 100% super samples are plotted, 40% and 60% are plotted in the “residual” area, and 100% super is plotted in the “clean” area. The Here, the “residual” region is defined as a region where the power spectral density is larger than a predetermined threshold and the average intensity is larger than the predetermined threshold. A “clean” region is defined as a region where the power spectral density is less than the threshold and the average intensity is less than the threshold.

  From the figure, the degree of degreasing can be accurately evaluated by comparing the power spectral density with a predetermined threshold and comparing the average intensity with the predetermined threshold.

<Fourteenth embodiment>
FIG. 23 shows the relationship between wavelet coefficients and average intensity. In the figure, the horizontal axis represents wavelet coefficients, and the vertical axis represents average intensity. When wetting 40%, 60%, 80%, 100% and 100% super samples, 40% and 60% are plotted in the “residual” area, 80%, 100% and 100% super are “clean”. "Is plotted in the area. Here, the “residual” region is defined as a region where the wavelet coefficient is larger than a predetermined threshold and the average intensity is larger than the predetermined threshold. A “clean” region is defined as a region having a wavelet coefficient smaller than a threshold and an average intensity smaller than the threshold.

  From the figure, it is possible to accurately evaluate the degree of degreasing by comparing the magnitude of the wavelet coefficient with a predetermined threshold and comparing the average intensity with the predetermined threshold.

<Fifteenth embodiment>
FIG. 24 shows the relationship between wettability and area ratio. In the figure, the horizontal axis represents wettability and the vertical axis represents the area ratio. As described above, the area ratio is the ratio of the area of the non-stained portion to the total area of the sample, so that the wettability and the area ratio are approximately proportional. Therefore, the degree of degreasing can be evaluated by comparing the area ratio with a predetermined threshold value. However, as shown in FIGS. 17, 18, 19, and 20, the degree of degreasing can be more accurately evaluated by evaluating with a two-dimensional map in which the area ratio is combined with another index.

<Sixteenth Embodiment>
FIG. 25 shows the relationship between wavelet coefficients and variation coefficients. In the figure, the horizontal axis is the wavelet coefficient, and the vertical axis is the 1 / variation coefficient. When wetting samples of 40%, 60%, 80%, 100% and 100% super are plotted, 40% and 60% are plotted in the “residual” area, and 100% and 100% super are the “clean” area. Is plotted in Here, the “residual” region is defined as a region where the wavelet coefficient is larger than a predetermined threshold and the 1 / variation coefficient is smaller than the predetermined threshold. The “clean” region is defined as a region where the wavelet coefficient is smaller than the threshold and the 1 / variation coefficient is larger than the threshold.

  From the figure, the degree of degreasing can be accurately evaluated by comparing the magnitude of the wavelet coefficient with a predetermined threshold and comparing the magnitude of the variation coefficient with a predetermined threshold.

<Seventeenth Embodiment>
In the present embodiment, a case where the sample 30 in FIG. 1 has an angle will be described. When the sample 30 has an angle with respect to the CCD camera 32, the influence on the fluorescence intensity distribution cannot be ignored.

FIG. 26 shows a method of correcting the intensity of the flat plate-like sample 30 with an angle depending on the incident angle and the photographing angle. In this correction method, it is assumed that the object to be measured is mostly degreased, and the scattered light depends on the incident intensity without depending on the incident angle. Also, assuming the pre-painting stage, the surface roughness due to processing was small, so it was not affected. The physical property values used for correction are as follows.
I: fluorescence intensity Ii: incident intensity In: fluorescence intensity per unit area Fs: reabsorption rate γ: fluorescence rate k: fluorescence diffusivity A ′: irradiation area from the incident side A ″: projection area S: beam area θ : Angle between flat plate and incident light −π / 2 <θ <π / 2
ω: angle between the flat plate and the measurement surface −π / 2 <ω <π / 2

Focusing on the beam width of incident light, the beam width increases as the angle θ increases, and the incident intensity per unit area decreases. Considering this, the fluorescence intensity of the flat sample 30 according to the incident angle is
When the height of the beam does not change, considering that the width hitting the flat specimen 30 changes, the above equation is
It becomes. This equation means that if the incident angle θ is known, the fluorescence intensity of the flat plate sample 30 can be converted. Further, the fluorescence intensity per unit area with respect to the imaging surface can be calculated from the above equation.
Is derived. From this equation, the measurement angle between the incident beam and the optical axis of the CCD camera 32 is α = θ + ω.
It becomes. Since the measurement data is obtained by multiplying the sensitivity coefficient from this equation, the physical property value of fluorescence can be deleted. Therefore,
It becomes. At this time, the measurement data Bin is used, and the converted output value is Bout. s represents an incident light region within the measurement range. Measurement data can be converted using this equation.

  Next, the case where the sample 30 in FIG. 1 has a curvature will be described. Even when the sample 30 has a curvature with respect to the CCD camera 32, the influence on the fluorescence intensity distribution cannot be ignored.

FIG. 27 shows a method for correcting the intensity of a curved surface according to the incident angle and the photographing angle. The fluorescence intensity of the minute area dA ′ from the starting point P is obtained from the equation (2).
It becomes. The fluorescence intensity at a minute position from the starting point P of the surface having a two-dimensional curvature as shown in FIG.
It becomes. The integrated value of the fluorescence intensity of the surface with curvature in the two-dimensional direction is
It is. At this time, the integral constant C is a positive constant determined by the range of the curved surface (when 0 <θ <π / 2), and the integrated value of the fluorescence intensity based on the curvature can be obtained from the above equation when the angle θ is known. In addition, the fluorescence intensity per unit area with respect to the imaging surface is calculated from the equation (8) as follows:
It becomes. The light intensity in the minute space is the same as the formula (5), and the conversion formula is the same as the formula (6).

  In FIG. 28, the experimental result in the flat plate sample 30 is shown. The apparatus is composed of a light source excimer laser 14 and a CCD camera 32, and uses a steel sample 30 of 70 × 150 mm. Rust prevention oil is uniformly applied to the entire surface of the sample 30, and a KrF excimer laser (248 nm) is irradiated at 55 mJ. The beam area is 10 × 100 mm. The position of the laser and the CCD camera 32 is fixed (irradiation angle α), and the flat sample 30 is rotated every 10 degrees to calculate the angle ω of the flat sample 30 and the light intensity at that time. FIG. 28 shows the result when the irradiation angle α = 25 deg. From the figure, when irradiation is performed with α = 25 deg (0.22 rad), the correction value of the light intensity is estimated to have an error of 10% or less when the angle of the flat sample 30 is within a range of −30 degrees <ω <50 degrees by this correction method. It turns out that it is.

  Note that the error is 10% or more when −90 degrees <ω <−30 degrees and 50 degrees <ω <90 degrees. This is because the correction method assumes that the member is long at infinity, and an error occurs in a finite sample. However, there is no problem because the angle of the practically inclined surface and the target surface with curvature is smaller than the range shown in this correction method. Rather, this correction method can be used to roughly approximate a car body with many curved surfaces or inclined surfaces. It can be corrected just by searching.

  According to this embodiment, it is possible to correct the fluorescence intensity with respect to the angle and the curvature, and it is possible to correct the intensity distribution only by referring to the three-dimensional shape information of the product. For example, for the measurement of the shape, there are a method of using a three-dimensional measuring device or using CAD data as a reference database. However, the light source to be used is preferably a high intensity and high uniformity such as a laser. This can be improved by assembling an optical system that makes the strength uniform, such as a diffusion sheet (for example, a homogenizer).

<Eighteenth embodiment>
The degreasing degree determination of the present embodiment can be used for evaluating the degreasing degree in the production line. Then, in the process of the production line, by tracking the degree of degreasing on a time series, it is possible to know the change in the degree of degreasing over time.

  FIG. 29 shows an example of application to a vehicle assembly production line. The vehicle body 100 proceeds to the next assembly process through a degreasing process. The vehicle body 100 before degreasing is advanced to the position of the degreasing step, the vehicle body 100 is immersed in the cleaning liquid to degrease the vehicle body 100, and then is advanced to the position of the degreasing degree inspection step. In the degreasing degree inspection step, the degreasing degree determination device 1 of the present embodiment is provided, and the degreasing degree at a predetermined position (or a plurality of positions) of the vehicle body is measured. The degreasing degree determination device 1 sequentially determines the degreasing degree together with the elapsed time from the start of measurement. The degree of degreasing is determined, for example, by mapping the fluorescence intensity and the gradient of the power spectrum. Then, the sequentially determined results are plotted on the three axes of fluorescence intensity-power spectrum gradient-time and displayed on the display device.

  FIG. 30 shows an example of the degree of degreasing expressed on three axes. By using such a three-dimensional display, it is possible to easily grasp how the degree of degreasing changes with time. For example, when the gradient of the power spectrum suddenly increases after a certain period of time, At that time, any abnormality, for example, an abnormality in the cleaning process or deterioration of the cleaning liquid can be quickly grasped.

  Of course, it is also suitable to install the degreasing degree determination apparatus of the present embodiment at a plurality of positions on the production line and determine the degree of degreasing in each step of the production line.

  FIG. 31 shows a configuration in this case. There are a first degreasing step and a second degreasing step in the production line. The vehicle body 100 before degreasing proceeds to the first degreasing step, and is washed by immersing in a cleaning liquid. Thereafter, the vehicle body 100 proceeds to the second degreasing step, and is again immersed in the cleaning liquid and cleaned. The degreasing degree determination device 1 of the present embodiment is provided at a position before the first degreasing process, a position after the first degreasing process and before the second degreasing process, and a position after the second degreasing process, respectively. The degree of degreasing at a predetermined position is measured. When paying attention to a certain vehicle body 100, the degree of degreasing is determined at the timing of reaching the position before the first degreasing process (indicated by time t = 1 in the figure), and then the timing of reaching the position after the first degreasing process. The degree of degreasing is determined at (denoted by time t = 2 in the figure), and the degree of degreasing is determined at the timing (indicated by t = 3 in the figure) at which the position after the second degreasing step is reached. From this, the change over time in the degree of degreasing becomes clear. Even in this case, it is possible to clearly grasp the time change by plotting on the three axes of fluorescence intensity-power spectrum gradient-time and displaying it on the display device.

  FIG. 32 shows an example of the degree of degreasing expressed on three axes. By using such a display, it is possible to easily grasp at which point of the production line the degree of degreasing is reduced or deteriorated.

  As mentioned above, although each embodiment of this invention was described, this invention is not limited to these embodiment, A various change is possible. That is, the present invention analyzes the intensity distribution of fluorescence from a sample (sample) and determines the degree of degreasing, but analyzes the spatial pattern of the intensity distribution of fluorescence as an index for determining the degree of degreasing. The spatial pattern can include not only a power spectrum and wavelet coefficients but also a geometric pattern. In addition to the area ratio, the geometric pattern includes an equivalent diameter of an object for a specific stain, a distance between a feature for a specific stain and a similar feature, and the like. Here, the equivalent diameter of the object means a diameter in an equivalent circle having the same area as the specific dirt. The distance between similar features means the distance between the dirt centers of gravity of substantially the same size. By analyzing the spatial pattern of the fluorescence intensity distribution, the degree of degreasing can be evaluated as the degree of degreasing. For example, taking the power spectrum as an example of the analysis of the spatial pattern, if small granular oil is present compared to the clean state, the high frequency component of the power spectrum changes, and in the case of thin dirt and small lump of oil. Changes in the middle frequency component of the power spectrum, and in the case of a large lump of oil, changes appear in the low frequency component of the power spectrum. Also, taking geometric features as an example of spatial pattern analysis and calculating a histogram of equivalent diameters, if there is a small granular oil compared to the clean state, if there is a thin dirt and a small oil lump, The histogram changes when there is a lump of oil.

  Further, the present invention uses an index obtained by analyzing the spatial pattern of the fluorescence intensity distribution and an index obtained by statistical analysis of the fluorescence intensity distribution as an index for determining the degree of degreasing, In the embodiment, average intensity, standard deviation, and coefficient of variation are used as an index obtained by statistical analysis. However, an index obtained by statistical analysis of the area ratio may be used, and further, F test or t test is used. May be. The area ratio may be either a geometric amount or an amount obtained by statistical analysis, and strict distinction is not meaningful in the present invention. When grasping the area ratio as a geometric quantity, the relationship between the gradient of the power spectrum and the area ratio in FIG. 17 or the relationship between the wavelet coefficient and the area ratio in FIG. It can be said that the degree of degreasing is used, and when the area ratio is grasped as an amount obtained by statistical processing, the relationship in FIG. 17 or 18 is based on an index obtained by analyzing a spatial pattern and statistical analysis. Thus, it can be said that the degree of degreasing is determined using the two indexes obtained as described above. In either case, there is virtually no change.

Below, the combination of the parameter | index which can be used in order to determine a degreasing degree in this invention is shown collectively. In general, when two indices are used, it is desirable that the indices are independent of each other. That is, rather than using two indices obtained by analyzing a spatial pattern or two indices obtained by statistical analysis, a combination of an index obtained by analyzing a spatial pattern and an index obtained by statistical analysis. Would be more suitable. As described above, it is preferable to adaptively determine which combination is used depending on the measurement location and the difference in area. Of course, it is also possible to make a comprehensive evaluation using a plurality of combinations.
(1) Power spectrum slope and coefficient of variation (= standard deviation / average value)
(2) Power spectrum density and variation coefficient (3) Wavelet coefficient and variation coefficient (4) Power spectrum gradient and area ratio (5) Wavelet coefficient and area ratio (6) Power spectrum gradient and F test (t test)
(7) Power spectral density and F test (t test)
(8) Equivalent diameter and coefficient of variation (9) Distance and coefficient of variation (10) Spectral peak value and coefficient of variation (11) Area ratio and coefficient of variation (12) Average intensity and area (13) Average intensity and diameter (14) Average Intensity and distance (15) Average intensity and power spectrum gradient (16) Average intensity and power spectral density (17) Average intensity and wavelet coefficient

  10 controller, 12 pulse generator, 14 excimer laser, 30 samples, 32 CCD camera.

Claims (11)

A degreasing degree determination device,
A light source for irradiating the surface of the object to be measured;
Detection means for detecting fluorescence from the surface of the object to be measured based on the light;
Using at least two of the first index obtained by analyzing the intensity distribution of the fluorescence by spatial pattern analysis and the second index obtained by statistically analyzing the intensity distribution of the fluorescence, the surface of the object to be measured is used. Arithmetic means for determining the degree of degreasing;
A degreasing degree determination apparatus characterized by comprising: The apparatus of claim 1 .
The first index is any one of a power spectrum gradient, a power spectrum density, a power spectrum peak value, and a wavelet coefficient,
The second index is any one of average intensity, standard deviation, coefficient of variation that is a ratio of average intensity and standard deviation, F test, t test, and area ratio. The apparatus of claim 2 .
The first index is a power spectrum gradient , power spectral density, or wavelet coefficient ,
The second index is a coefficient of variation , F test, t test, or average strength . The apparatus of claim 2 .
The first index is a power spectrum gradient , or wavelet coefficient ,
The second index is an area ratio. A degreasing degree determining apparatus. The apparatus of claim 2 .
The first index is a peak value of a power spectrum,
The second index is a coefficient of variation. A degreasing degree determining apparatus. The apparatus of claim 1 .
The first index is a geometric amount of the intensity distribution of the fluorescence. The apparatus of claim 6 .
The first indicator is the equivalent diameter of the object for a particular soil, or the distance between a feature for a particular soil and a similar feature ,
The second index is a coefficient of variation that is a ratio of an average intensity and a standard deviation. The apparatus of claim 6 .
The first indicator is a soil area , a target equivalent area for a particular soil, or a distance between a feature for a particular soil and a similar feature ,
The second index is an average strength. A degreasing degree determining apparatus. The apparatus according to any one of claims 1 to 8 , further comprising:
Correction means for correcting the intensity distribution of the fluorescence to an intensity distribution at a reference angle or curvature according to an angle formed by the light source and the surface of the object to be measured or a curvature of the surface of the object to be measured. Degreasing degree determination device. The apparatus according to any one of claims 1 to 9 , further comprising:
A degreasing degree determination apparatus comprising: a display unit configured to display a determination result of the calculation unit. In the apparatus in any one of Claims 1-10 ,
The degreasing degree determination apparatus characterized in that the calculation means determines in time series according to a cleaning process of the object to be measured.