JP3326960B2 - Paint film thickness measuring device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a coating film thickness measuring technique capable of measuring a coating film thickness in an undried state immediately after a coating material has been applied. The present invention relates to a measurement technique capable of judging the following and feeding back to subsequent coating conditions.

[0002]

2. Description of the Related Art As a device for measuring a coating film thickness in an undried state immediately after coating, there are, for example, a contact type device using a needle gauge, and a non-contact type device of an electromagnetic type or an eddy current type. FIG. 23 is a cross-sectional view showing the principle of an example of a measuring device using magnetism among the conventional devices as described above. FIG.
In, as shown in first (a), in advance to position the non-contact film thickness sensor 82 to face the painted surface of the object to be coated 81 of the steel sheet in close distance h _0. Then, a magnetic field is generated between the object to be coated 81 and the non-contact film thickness sensor 82 by a transmission / reception coil (not shown) provided in the non-contact film thickness sensor 82. In this state, when the paint 83 in a wet state is applied to the surface of the object 81 to be coated, the magnetic field between the object 81 and the non-contact thickness sensor 82 after the coating is attenuated by the electromagnetic resistance due to the coating thickness. Is sensed by the transmitting and receiving coil in a state lower than before the painting. Thus, by detecting the change in the magnetic flux attenuated in proportion to the film thickness h, the coating film thickness can be measured. However, in the conventional film thickness measuring device as described above, the distance between the object to be coated 81 and the non-contact film thickness sensor 82 is set to a predetermined close distance before coating,
Since it is necessary to precisely maintain the positional relationship before and after painting, it is necessary to keep the sensor set to a close distance even during painting, which is not practical. In addition, since the measurement must be performed twice before and after coating, there is a problem that it is troublesome and the measurement accuracy is poor. Further, in the contact type device using the needle gauge, there is a problem that the coating quality is deteriorated because the coating surface is damaged.

In order to solve the above problems, the present applicant has already filed an application for measuring the thickness of a coating film in a non-contact manner based on the roughness of an undried coating surface immediately after the application of a coating material (Japanese Patent Application Hei 4-306966, unpublished). The above measuring device measures the roughness of the undried coating surface immediately after coating and the wavelength of the unevenness waveform of the coating surface using an optical surface roughness meter or an imaging device, and based on them, the film thickness in the undried state. (Wet film thickness) is measured, and the film thickness after drying (dry film thickness) is predicted.

[0004]

As described above, the conventional contact-type apparatus has a problem that the coating surface is damaged, so that the coating quality is deteriorated. In addition, a non-contact apparatus using magnetism is used. In such a case, there is a problem that the measurement is troublesome and the measurement accuracy is poor. Further, in the prior application of the present applicant which solved the problem of the conventional apparatus as described above, it is possible to perform accurate measurement without contact and easily, but in the actual painting work, the following is required. There's a problem.

That is, in the case of successive painting on a painting automation line, such as in the case of painting the body of an automobile, the quality of the painting such as film thickness is fed back as soon as possible to improve the next painting condition. It is necessary to always keep the best paint condition. Also, as in the case of a car body, a painted surface is wide, and a painted object having surfaces in different states such as a horizontal surface and a vertical surface is present, because the painted state is not necessarily uniform by each part. In order to perform accurate measurement, it is necessary to measure each part. However, in the above-mentioned prior application, the surface condition of the paint is basically observed by one image pickup device (or optical measuring device). It is necessary to perform imaging and arithmetic processing of different parts. For this reason, a considerably long measurement processing time is required, and it is not possible to image a large number of locations within a short time. As in (side view), it was not possible to determine the quality of the coating by observing many parts having different coating conditions at the same time and under the same conditions. Therefore, there is a problem that it is unsatisfactory to feed back the quality of the coating state as soon as possible to improve the next coating condition and to always maintain the best coating state.

The present invention further improves the prior application of the present applicant as described above, and determines the coating state such as the film thickness quickly and accurately during coating, and can immediately feed back to the subsequent coating conditions the coating film thickness. It is an object to provide a measuring device.

[0007]

Means for Solving the Problems In order to achieve the above object, the present invention is configured as described in the claims. That is, the invention described in claim 1 is:
As shown in FIG. 1 (a), a plurality of image pickup means 100 for picking up the roughness of the undried paint surface immediately after application of the paint at different portions of the paint surface, and image information from the plurality of image pickup means. Image processing means 101 for performing image processing on each of them, and based on the image processing data processed by the image processing means, the roughness of the coating surface and the wavelength of the uneven waveform of the coating surface are calculated for each of the above-described locations. Roughness calculating means 102, a coating condition input means 103 for inputting at least a coating condition including a viscosity of the paint, and a time change amount and a wavelength of the roughness calculated from the roughness calculated by the roughness calculating means. A film thickness calculating means 104 for calculating the thickness of the coating for each location based on the coating conditions from the coating condition input means, and a coating based on the calculation result of the film thickness calculating means. It has an average film thickness calculation unit 105, the calculating the average thickness of. In addition, each of the above means,
For example, they correspond to the following means in the embodiment of FIG. That is, the imaging unit 100 includes the imaging units 2-1 to 2-1.
2-4, the image processing means 101 includes image processing units 3-1 to 3-3.
-4, the roughness calculating means 102 includes first calculating units 4-1 to 4-
4, the coating condition input means 103 inputs the
The film thickness calculating means 104 corresponds to the third calculating sections 6-1 to 6-4, and the average film thickness calculating means 105 corresponds to the fourth calculating section 7, respectively.

Next, a second aspect of the present invention will be described with reference to FIG.
As shown in (b), the following components are added to the invention described in claim 1. That is, based on the roughness calculated by the roughness calculating means 102, the time variation of the roughness obtained from the roughness, and the wavelength, the presence or absence of dripping of the painted surface is determined for each of the above-described locations. In accordance with the sag determining means 106 and the average film thickness calculated by the average film thickness calculating means 105 and the determination result of the sagging determining means 106,
A coating quality judging means 107 for making a quality judgment according to a predetermined quality judgment level of the coating quality and calculating an optimum film thickness in accordance with the quality judgment level is added. Each of the above-mentioned means is described in, for example, FIG.
Correspond to the following means in the embodiment. That is, the dripping determining means 106 determines whether the second operation units 5-1 to 5-4
In addition, the coating quality judging means 107
Each corresponds.

Next, the invention according to claim 3 is obtained by adding the following constituent elements to the invention according to claim 1. That is, based on the roughness calculated by the roughness calculating means 102, the time variation of the roughness obtained from the roughness, and the wavelength, the presence or absence of dripping of the painted surface is determined for each of the above-described locations. , A sharpness determining means 106 for calculating the sharpness of the painted surface for each of the above-described locations based on the image processing data processed by the image processing means 101, The average clarity calculating means 109 for calculating the average clarity of the painted surface based on the calculation result of the illuminance calculating means, the average film thickness calculated by the average film thickness calculating means 105, and the determination by the sagging determining means 106 In accordance with the result and the average sharpness calculated by the average sharpness calculating means 109, a good or bad judgment is made according to a predetermined good or bad judgment level of the coating quality, and an optimum judgment is made in accordance with the good or bad judgment level. Paint quality judgment to calculate film thickness And stage 107, is obtained by adding a. The above-described units correspond to, for example, the following units in the embodiment of FIG. That is, the dripping determining means 106 is in the second calculating sections 5-1 to 5-4, the sharpness calculating means 108 is in the fifth calculating sections 9-1 to 9-4, and the average sharpness calculating means 109 is the sharp. The coating quality determination unit 107 corresponds to the coating quality determination unit 11, and the coating quality determination unit 107 corresponds to the coating quality determination unit 11.

Next, the invention according to claim 4 is the invention according to claim 1.
In the invention described in any one of claims 1 to 3, the imaging means 100
An imaging unit that captures an image of a non-horizontal surface of an object to be coated, and an imaging unit that captures an image of a horizontal surface are provided. It is configured to determine the presence or absence. The surface that is not a horizontal plane means a vertical surface or a slope. Next, the invention according to claim 5 is the invention according to claims 1 to 4,
The above-mentioned coating condition input means 103 is a signal for distinguishing between the first spray coating in which the coating is performed only by one spray and the second spray coating in which the second coating is performed in a state where the first coating is incompletely dried. The film thickness calculating means 104 is configured to calculate the film thickness using different paint viscosity values for the first spray coating and the second spray coating. According to a sixth aspect of the present invention, in the invention of the fifth aspect, the coating viscosity of the lower layer by the first spraying and the upper layer by the second spraying are used as the paint viscosity value in the second spray coating. The film thickness is calculated using the average value of the coating viscosity of the film.

[0011]

According to the first aspect of the present invention, there are provided a plurality of image pickup units, and a calculation unit (image processing means, roughness calculation means, film thickness calculation means, average film thickness calculation means) for respectively processing image information captured by each of the image pickup units. Means), and coating condition input means for inputting coating conditions, simultaneously image a plurality of portions of the object to be coated, perform arithmetic processing on each of them to obtain a film thickness at each of the portions, and further calculate an average film thickness thereof. It is configured to ask. With this configuration, it is possible to observe many parts having different coating conditions at the same time and under the same conditions, and to quickly obtain the film thickness and the average film thickness at a plurality of locations on the object to be coated. The film thickness and the average film thickness thus obtained can be used by displaying the numerical values as they are, or can be used by the coating quality determining means 107 for automatic control. Can also be given as

The invention described in claim 2 is the first invention.
In addition, the sagging determining means 106 and the coating quality judging means 107 are added to the invention described in (1), and based on the average film thickness and the presence or absence of sagging, a quality judgment is performed according to a predetermined quality judging level of the coating quality, In addition, it is configured to calculate an optimum film thickness in accordance with the quality judgment level. In this configuration, it is possible to determine the quality of the coating by observing many portions having different coating conditions at the same time and under the same conditions. Therefore, it is possible to immediately feedback the quality of the coating state to improve the next coating condition, and to always maintain the best coating state. According to a third aspect of the present invention, a dripping determining unit 106, a sharpness calculating unit 108, an average sharpness calculating unit 109, and a coating quality determining unit 107 are added to the first aspect. Then, according to the average film thickness, the presence or absence of sagging, and the average sharpness, a pass / fail judgment is made according to a predetermined pass / fail judgment level of the coating quality, and an optimum film in accordance with the pass / fail judgment level is determined. It is configured to calculate the thickness. In this configuration, the quality of the coating is determined based on the film thickness, the presence or absence of sagging, and the sharpness at each location, so that the quality of the coating can be determined with higher accuracy. Therefore, it is possible to immediately feedback the quality of the coating state to improve the next coating condition, and to always maintain the best coating state. Further, the invention according to claim 4 separately captures an image of a non-horizontal surface (vertical surface or inclined surface) and a horizontal surface of the object to be coated, and determines the droop only for image information of the non-horizontal surface. is there. That is, sagging generally occurs on vertical surfaces and slopes,
Since it is less necessary to judge the droop on the horizontal plane, that part is omitted.

Further, the invention according to claim 5 relates to a film thickness calculation in a so-called double spray coating in which a second spray is performed in a state where the first coating is incompletely dried, and a coating condition input is performed. As information to be input from the means 103, a signal for discriminating between one-time spray painting and two-time spray painting in which painting is performed only by one time spraying is input.
The film thickness is calculated using different paint viscosity values. With this configuration, once spraying and 2
It is possible to accurately calculate the film thickness by distinguishing the spraying. The invention according to claim 6 uses the average value of the coating viscosity of the lower layer by the first spraying and the coating viscosity of the upper layer by the second spraying as the value of the paint viscosity in the second spraying. It was made. As will be described in detail later, in the case of the second spraying, the lower layer sprayed the first time and the upper layer sprayed the second time have different time points of spraying. The coating viscosity at a certain point has a different value. Therefore, as described above, by using the average value of the two as the paint viscosity, the film thickness in the second spraying can be accurately calculated.

[0014]

FIG. 2 is a block diagram of a first embodiment of the present invention, in which the present invention is applied to a vehicle body painting line. First, an outline of the entire configuration will be described with reference to FIG. Reference numeral 1 denotes a body of a body to be coated, which is painted while moving on a painting line at a predetermined speed. Reference numeral 2 denotes an imaging unit for imaging a wet coating surface immediately after coating. Four imaging units 2-1 to 2-4 are provided as imaging units 2, each of which captures an image of a different part of the vehicle body. In this embodiment, the upper surface of the vehicle body,
An example is shown in which a plurality of locations are imaged for each site such as a right side surface and a left side surface. For example, in FIG. 2, two imaging units 2-1 and 2-2 are used to image the upper surface (horizontal surface) of the vehicle body such as an engine hood, and an imaging unit 2 is used to image the left side (vertical surface) of the vehicle body such as a left fender. When two of 3 and 2-4 are provided (the right side of the vehicle is not shown)
Is exemplified. The imaging is performed after a predetermined time (for example, 1 to 2 minutes) after the paint is sprayed. Therefore, the imaging unit 2 is installed at a position where the vehicle body reaches after, for example, 1 to 2 minutes in accordance with the moving speed of the painting line.

The roughness information (details will be described later) of the painted surface imaged by the image pickup units 2-1 to 2-4 is subjected to image processing by the image processing units 3-1 to 3-4. The image processing unit is composed of an image memory for storing image information and an arithmetic device such as a computer.

The image processing data processed by each of the above image processing units is sent to each of the first arithmetic units 4-1 to 4-4. The first arithmetic units 4-1 to 4-4 calculate the roughness information of the coating surface from the input image processing data, that is, the roughness R corresponding to the surface average value of the peak-to-peak of the unevenness of the coating surface. _a (specifically, the power spectrum integral value P described later is used) and the wavelength λ of the uneven waveform (specifically,
A peak wavelength λ in a long wavelength region described later is used), and _a time variation ΔRa of the roughness _Ra is calculated. These values are calculated independently for each imaged location.

Further, the second calculation units 5-1 to 5-4 perform coating at each location according to the roughness information (R _a , λ) obtained by each of the first calculation units and the time variation ΔR _a. The presence or absence of the sagging state of the film is determined. The coating condition input unit 8 is a coating condition input unit such as a keyboard, for example.
The paint component information such as the content of volatile components, and the paint conditions such as the viscosity and temperature of the paint are input. Further, the third calculation units 6-1 to 6-1
6-4, at each location, according to the coating condition from the coating condition input unit 8, the roughness information (R _a , λ) and the time variation ΔR _a obtained by each first calculation unit. Calculate the wet coating thickness. Note that, if the sagging state occurs as a result of the calculation by the second calculation unit, the thickness calculation in the third calculation unit may be stopped. Further, the fourth arithmetic unit 7 receives the results of the third arithmetic units 6-1 to 6-4 and averages the wet film thickness at a plurality of locations. For example, an average value of the wet film thickness calculated for a plurality of locations for each part (for example, an average film thickness for an engine hood) is calculated. Further, the average film thickness of the entire vehicle body can be calculated.

On the other hand, the fifth calculation units 9-1 to 9-4 receive the image processing data of the image processing units 3-1 to 3-4, and
The sharpness of the painted surface in an undried state (details will be described later) is calculated for each imaged location. Then, the sharpness averaging unit 10 performs an averaging process on the calculation results of the fifth calculation units 9-1 to 9-4 to calculate an average sharpness for each part. Further, the average film thickness of the entire vehicle body can be calculated. Next, the coating quality determination unit 11 compares the average film thickness calculated by the fourth calculation unit 7 with each of the second calculation units 5-1 to 5-4.
Of the sag calculated in the above, and the sharpness averaging processing unit 10
Enter the average sharpness obtained in the above, and according to them, the coating quality, that is, whether the coating film thickness and the sharpness are within a predetermined range, and determine whether there is sagging, the subsequent coating conditions Is output as an instruction signal for setting the optimal conditions. The above instruction signal is displayed on a display device 12 such as a liquid crystal display device or a CRT display device and presented to the operator, and is also sent to the coating condition control system 13 so that the operating condition of the coating gun 14 is maintained at the optimum condition. To control. In addition, the above-mentioned first to fifth arithmetic units,
The sharpness averaging processing unit 10 and the coating quality determination unit 11
Although it is configured by an arithmetic device such as a computer, in order to improve the arithmetic processing speed, the first to fifth arithmetic units are respectively provided for each system (for example, 4-1 to 5-1 to 6-1 to 9-1). May be configured by an independent arithmetic device,
Alternatively, each of the arithmetic units may be configured by an independent arithmetic device.

Next, the operation will be described. First, the principle of film thickness measurement in the present invention will be described. The film thickness measuring method according to the present invention measures the coating film thickness by focusing on the smoothing phenomenon of the coating surface in an undried state immediately after application of the coating material, that is, in a wet state. FIG. 3 is a cross-sectional view of the coating film after painting. Immediately after coating, as shown in (a), the coated surface is in an uneven state due to the initial bonding of the adhered particles. Then, as time passes, as shown in (b), smoothing is gradually performed by the leveling force, and finally, as shown in (c), a smoothed state is obtained. In the present invention, attention is paid to such a smoothing phenomenon, and the unevenness state of the coating surface in a wet state is measured, whereby the coating film thickness after smoothing or after drying is calculated. In order to measure the unevenness state in the wet state as described above, various methods such as a light interference type surface roughness meter (for example, “Mechanical Engineering Service Section, Japan Society of Mechanical Engineers, September 30, 1989”)
3rd edition of the new edition, B2, pp. 207-208)
Here, there will be described a method in which an image of a painted surface is imaged by an imaging means (for example, a CCD camera) and the information is image-processed.

FIG. 4 is a sectional view showing an example of the image pickup section 2. As shown in FIG. 4, the basic configuration of the imaging unit is a light source 3
1. Light / dark pattern plate 32, reflector 33, lens 34, CC
It comprises a D camera 35. The light / dark pattern plate 32 is an opaque plate provided with linear slits at predetermined intervals (for example, 1 mm intervals) (or an opaque stripe pattern printed at predetermined intervals on a transparent plate). And light source 3
The parallel light beam from 1 is reflected by the light / dark pattern plate 32 and the reflecting mirror 33.
By irradiating the coating surface obliquely through the lens and the lens 34, a stripe pattern corresponding to the slit is formed on the object to be coated. This stripe pattern has a waveform distorted according to the unevenness on the object to be coated. The reflected light is imaged by the CCD camera 35, and the above-mentioned distorted stripe pattern, that is, information on the surface roughness is input. The image information of the stripe pattern as described above is subjected to image processing, and power spectrum frequency analysis (for example, fast Fourier transform processing: FFT) is performed to obtain a power spectrum PS.

FIG. 5 is a frequency characteristic diagram of the power spectrum PS. The vertical axis represents the power spectrum PS, and the horizontal axis represents the frequency f (the reciprocal of the wavelength λ, f = 1 / λ). In FIG. 5, a first peak waveform is a power spectrum of a basic waveform by a basic fringe corresponding to the slit, and a second peak waveform is a long wavelength region (10
Power spectrum corresponding to about 1 mm) and the third peak waveform are in the middle wavelength region (1 to 0.1 mm) of the uneven waveform.
The fourth peak waveform indicates a power spectrum corresponding to the short wavelength region (0.1 mm or less) of the concavo-convex waveform. In the above power spectrum waveform, the peak wavelength in the long wavelength region of the uneven waveform, that is, the wavelength λ corresponding to the peak value of the second peak waveform
Is obtained, and the integrated value of the second peak waveform (the area of the hatched portion) is obtained as a value indicating the surface roughness, and this is set as the power spectrum integrated value P. The wavelength λ (peak wavelength in the long wavelength region) and the power spectrum integration value P have a relationship with the film thickness as described below. Based on these values, the film thickness is calculated using the following smoothing theoretical formula. Can be calculated.

[0022] First, explaining the smoothing characteristics of the power spectrum integral value P, and the surface of the uneven surface mean corresponding surface roughness value R _a and the power spectrum integral value P (peak-to-peak value), The relationship is as shown in FIG. 6, and the relationship is shown by the following (Formula 1) and (Formula 2) formulas. _{P = Q + k × √R a} ... ( number _{1) R a = {(P} -Q) / k} 2 ... ( Equation 2) However, in the above formula, Q is the roughness correction value, k is Roughness transform coefficients is there. In the derivation of the theoretical equation for smoothing based on the power spectrum analysis value, first, the surface roughness _Ra is expressed by the following equation (formula 3) as the theoretical equation for wet coating film smoothing (approximate equation). _{R a = R a0 · exp (} -t / τ) ... ( Equation 3), however, (the value immediately after time 0 i.e. paint) R _a0 is the initial value of R _a, t is the time elapsed after coating. Further, τ is a time constant derived from the basic equation of the viscous fluid, and is as shown in the following equation (8). When the above equation (2) is substituted into the equation (3), the following equation (4) is obtained. {(P−Q) / k} ² = {(P ₀ −Q ₀ ) / k} ² exp (−t / τ) (4) where P ₀ is the initial value of P (the value at time 0) And Q ₀ is the initial value of Q. In the above equation (4), if P and P ₀ are values including the respective correction values Q and Q _{0 and} are expressed as (P ₀ −Q ₀ ) → P ₀ , (P−Q) → P,
The expression (4) can be expressed as the following expression (5). P = P ₀ · exp (−t / 2τ) (Equation 5) Further, the time constant τ is expressed by the following (Equation 6). τ = 3ηλ ⁴ / 16π ⁴ γh ³ (Equation 6) where η is the viscosity of the paint, λ is the peak wavelength in the long wavelength region, γ is the surface tension of the coating film, and h is the film thickness in a wet state (imaging) (Average value of parts). From the above, the coating film thickness h based on the power spectrum analysis value is expressed by the following (Equation 7).

[0023]

(Equation 7)

Here, P ₁ is the value of the power spectrum integrated value P at the time point t ₁ , and P ₂ is the time point t ₂ (where ₋₁ <t ₂ ).
Is the value of P at. Note that τ ′ _i is represented by the following (Equation 8). τ ′ _i = 3η (t _i ) · λ ⁴ / 16π ⁴ γ (8) where i = 1 or 2, and η (t _i ) is a function of the viscosity of the paint and the elapsed time after painting. Indicates that That is, what is input from the coating condition input means 8 is the viscosity η of the coating before coating, but the coating viscosity after coating is a value η (t _i ) that changes according to the elapsed time after coating. . This value is
This value is determined by the paint composition (such as the proportion of volatile components in the paint) and the temperature. As can be seen from the above equation (7),
From the values of the viscosity η of the paint, the surface tension γ of the paint film, the peak wavelength λ in the long wavelength region of the uneven waveform, and the integrated value P of the power spectrum at _two time points t ₁ and t ₂ after coating, the film thickness h in the wet state is obtained. Can be requested. Among the above values, the viscosity η of the paint and the surface tension γ of the paint film are values determined by the properties of the paint, so input a known value, and input the peak wavelength λ in the long wavelength region and the power spectrum integration. As the value P, a value obtained by processing the above-described image information is used.

FIG. 7 is a characteristic diagram showing a wet smoothing dynamic characteristic (power spectrum integral value P) obtained by comparing a measured value with a theoretical value of smoothing using the above equation (7). In FIG. 7, the horizontal axis represents the elapsed time after painting, and the vertical axis represents the power spectrum integrated value P. In the above measurement, an image immediately after application is taken by the imaging unit 2 and power spectrum analysis is performed. From FIG. 7, it can be seen that the measured value has a smoothing characteristic almost coincident with the theoretical value. Table 1 shows that the film thickness 6
It is a table | surface which shows the result of having measured the film thickness h using the estimation formula of the said (Formula 7) about two samples of 0 micrometers and 54 micrometers. As shown in Table 1, it can be seen that measurement is possible with an accuracy of several μm.

[0026]

[Table 1]

In the embodiment shown in FIG. 2, each image pickup unit 2-1
2-4, each of the image processing units 3-1 to 3-4, each of the first arithmetic units 4-1 to 4-4, and each of the third arithmetic units 6-1 to 6-4 perform the processing described above. , determine the thickness h of each imaging location, further in the fourth arithmetic unit 7, and the average value, i.e. determine the average thickness h _a. This average film thickness h
_{For a} , an average value for each part (for example, engine hood) and an average value for the entire vehicle body are obtained. In the determination of sag in the second arithmetic unit 4 described later, if it is determined that sagging is present, it is meaningless to perform a precise film thickness calculation, so that the coating quality judging unit 11 has an abnormal film thickness. A signal to the effect (thickness: large) may be input and the thickness averaging process in the fourth arithmetic unit 7 may be omitted. Further, in the above equation (7), two time points t ₁ and t ₂ after painting are obtained.
Are calculated using the two values P ₁ and P _{2 in the above} and the amount of time change of the roughness information. Therefore, it is necessary to image the same place at two points after painting. For this purpose, it is necessary to move the imaging unit 2 in accordance with the movement of the vehicle body on the painting line, so that the apparatus becomes complicated. To avoid this, there are the following methods. That is, in addition to the body to be coated, a test piece is prepared and the coating is performed under the same conditions as the object to be coated, at time t ₁ (for example, t ₁ = 10 seconds,
As the value P _{1 at} t ₁ <t ₂ ), a value obtained by processing the image information of the test piece is used. With this configuration, each imaging unit needs to perform only one imaging at the time point t ₂ (for example, one to two minutes after painting). Further, the measurement up to now is to calculate the film thickness in the wet state, but the film thickness in the wet state and the dry film thickness after drying are:
There is a certain correlation depending on the volatile components in the paint. Therefore, the dry film thickness can be easily estimated by multiplying the measured wet film thickness by a coefficient determined according to the content of the paint.

Next, the principle of sag determination in the present invention will be described. If the painted surface is not horizontal but is vertical or oblique, depending on the properties of the paint (insufficient viscosity) and the amount applied (if the amount is too large), sagging may occur. FIG. 8 is a cross-sectional view of the wet coating film surface with and without sagging.
(B) shows a case where droop has occurred. In a normal case without sagging as shown in FIG. 8 (a), as described with reference to FIG. 2, the coating surface immediately after coating has relatively large irregularities, and gradually becomes smoother with the lapse of time due to the smoothing phenomenon. To become flat. However, when the sagging as shown in FIG. 8B occurs, the state of the coating film surface is greatly different from that of FIG. 8A, the initial irregularities are small, the wavelength of the irregularities is long, and the smoothing speed is very high. It becomes small, and there is almost no change. When sagging occurs, the film thickness increases as illustrated.

FIG. 9 is a diagram showing the time-change characteristics of the power spectrum integral value P representing the roughness of the painted surface. As can be seen from FIG. 9, the initial value of the power spectrum integrated value P is large in a normal state without sagging, and is greatly attenuated with the passage of time. The value of P is small from the beginning and hardly changes. The above properties are used the power spectrum integral value P as a value indicating the roughness of the surface, the surface roughness R _a corresponding to the area average value of the unevenness of the surface (peak-to-peak value) It can be determined in the same manner even when used. In the present invention, the presence or absence of sagging is determined using the above phenomenon.

FIG. 10 is an embodiment of a flowchart for judging droop. In FIG. 10, first, in step S1, it is determined whether or not the value of the peak wavelength λ in the long wavelength region of the uneven surface waveform of the painted surface at the time point t is equal to or less than a predetermined value (normal lower limit value of λ). I do. For example, if the wavelength of the reference was lambda _s, determines whether the λ ≦ λ _s. Since the peak wavelength λ in the long wavelength region on the normal painted surface falls within a range of about 2 to 6 mm, the above-described reference wavelength λ
_s is set to, for example, 2 mm. This judgment is "yes"
If so, it can be determined that there is no drooping normal state. Next, in step S2, it is determined whether or not the value indicating the roughness of the coating film surface, for example, the value of the power spectrum integrated value P is equal to or larger than a predetermined value (the lower limit of the normal roughness). For example, if the reference power spectrum integral value of a P _s, P _s ≦ P
Is determined. And if "yes",
It can be determined that the coating surface is in a normal state in which dripping is unlikely. Next, in step S3, it is determined whether or not the time variation of the surface roughness is equal to or greater than a predetermined value (the lower limit of the normal variation). For example, the time variation ΔP of the power spectrum integrated value P is represented by the following (Equation 9).

[0031]

(Equation 9)

Here, P (t ₁ ) and P (t ₂ ) are the values of the power spectrum integrated value P at time points t ₁ and t ₂ (where t ₁ <t ₂ ). Therefore, if the reference value of the time change amount of [Delta] P _s, to determine whether [Delta] P _s ≦ [Delta] P,
If "yes", it is determined that it is normal time without droop. If all of the determinations in steps S1 to S3 are "no", it is determined that droop has occurred. FIG.
In the embodiment, each of the second calculation units 5-1 to 5-4 performs the above-described calculation processing, and determines whether or not there is a droop at each imaging location.

Next, the principle of measuring the sharpness of the painted surface in the present invention will be described. The sharpness of the painted surface is defined by the smoothness, the feeling of holding, and the glossiness (glossiness) of the painted surface. The three types of elements will be described in more detail. The smoothness indicates the degree of relatively large waviness distortion on the painted surface, and the feeling of solidity is very fine unevenness on the painted surface. The glossiness indicates how large the difference in brightness on the painted surface is reproduced. Hereinafter, the value of sharpness is indicated as sharpness S, and the respective values of smoothness, solid feeling, and glossiness are indicated as smoothness H, solidness N, and gloss T, respectively. The various quantities representing the sharpness S as described above can be obtained, for example, as follows. That is, the smoothness H and the thickness N of the painted surface are calculated by performing one-dimensional image processing on the contour extracted from the image information of the striped pattern. It can be calculated by detecting.

Hereinafter, an embodiment of the sharpness calculation will be described with reference to FIGS. 12 and 13 based on the flowchart shown in FIG. First, as a pre-process of inputting a measurement image, so that an optimal image can be obtained when measuring sharpness,
Processing for setting the size and position of the image to be input is performed. The reason for performing such a process is to input an image that is not affected by the curvature, since the obtained input image is different depending on the curvature of the painted surface. This process is performed in the following steps S11 to S15. First, an image input from a CCD camera is stored in an image memory. As an example of the stored image,
As shown in FIG. 12A, this is an image corresponding to the reflected light of the stripe reflected on the painted surface. This image is similar to the output stripe image when the painted surface is flat, but when the painted surface is a curved surface, it is enlarged, reduced, and further deformed according to the curvature. Image. When the curvature of the painted surface is large, the position of the image moves within the field of view of the CCD camera, and if the position of the image deviates from the field of view due to this movement, data collection required for measurement is insufficient. This adversely affects the reliability of the measurement result. Therefore, as described below, a process of tracking the position of the stripe image and changing the size of the measurement window is performed. First, the image stored in the image memory is called, and the ellipticity of the camera view A as shown in FIG. 12 is calculated. Similarly, the optical barycenter calculation of the stripe image existing in the camera view A is performed. Do. The calculation of the ellipticity is performed on the basis of the maximum value and the minimum value of the diameter by extracting the contour of the measurement window. Further, since the optical barycenter calculation is a general method that has been conventionally performed, the description of the processing is omitted here (step S1).
1, S12). Next, the center position of the stripe image is obtained based on the result of the optical centroid calculation. This calculation is performed to determine the center position of the measurement window in the process of determining the size of the next measurement window (step S).
13). Next, the size and position of the measurement window are determined based on the ellipticity obtained in the above processing and the center position of the stripe image. For example, as a result of the above measurement, if the camera field of view A is substantially circular as shown in FIG.
The measurement window B is set as shown in FIG. On the other hand, when the camera field of view (A) is elliptical as shown in FIG. 12C, the measurement window B is set as shown in FIG. 12C (step S14).

When the above processing is completed, the sharpness measurement processing is performed. First, a stripe image stored in the image memory is called and binarized using a predetermined threshold. For example, FIG.
The image is as shown in FIG.
5). In order to obtain the smoothness, a process of extracting an outline from the binarized image is performed to obtain an image as shown in FIG. 13B (step S16). However, since the line is very jagged as it is, a process for smoothing the line is performed to obtain an image as shown in FIG. 13C (step S17). Next, the direction of the normal line is determined for each of the constituent pixels of the smoothed outline. That is, FIG.
The direction calculation processing shown in FIG. More specifically, the direction of the normal is obtained for each pixel constituting the contour. This direction is very many (step S1).
8). Then, a number of directions obtained in this way are subjected to statistical processing, and those with little variation in direction as a whole, that is, those with convergence have good smoothness H, while those with large variation, that is, If the divergence is recognized, it is determined that the smoothness H is poor (step S19, step S20).

Next, in order to calculate the durability N, a process of extracting the width of the outline from the binarized image is performed. If it is normal, only stripes of the same width as the stripe reflecting the painted surface should be detected.However, if the durability N is poor, fine islets will be mixed in the stripe, so Those with a width corresponding to the islet are detected. Therefore, it can be said that the extraction of the width is a preceding process for recognizing how many small islands are present (step S21). Next, data having a predetermined value or less, for example, 0.5 mm or less is extracted from the data of the stripe width extracted in the above processing, and the existence ratio of the number is obtained. Based on this ratio, the durability N is calculated (steps S22 to S2).
4). The smaller the above ratio is, the larger the meat retention N is, that is, the better.

Next, in order to measure the glossiness T, first, the luminance difference between the brightest part and the darkest part is determined for each horizontal line of the image input through the measurement window. That is, a graph of the relationship between the position and the luminance is created for the image, and the difference between the maximum luminance and the minimum luminance in the graph is obtained (step S25). This process is performed for all the horizontal lines, and the average of the data in the area of the measurement window is obtained (step S26). The glossiness T is determined according to the luminance difference obtained by the above processing. Since the correlation between the luminance difference and the glossiness T is clear, the calculation for the calculation is very simple (Step S).
27). That is, the larger the difference in luminance, the better the gloss T (glossiness).

Next, the comparison of the sharpness between the wet-coated surface in an undried state and the dry-coated surface after drying will be described. First, the smoothness H of the sharpness will be described. As shown in FIG. 14, the value of the smoothness H of the wet painted surface is low immediately after painting, but gradually increases with time according to the above-mentioned smoothing theory. This tendency basically continues even after drying. Therefore, the smoothing target value on the wet painted surface is smaller than the value on the dry painted surface. For example, if the smoothness target value of the wet painted surface is H _w and the smoothness target value of the dry painted surface is H _d , the following equation (10) is obtained. H _d = k ₁ · H _w (Equation 10) where k ₁ is a wet smoothness coefficient and is a value of k ₁ > 1. This coefficient is stored in advance according to the coating conditions such as the coating color. The target value H _w of the smoothness of H wet coated surface is, for example, a value of about H _w ≧ 0.5.

Next, the durability N will be described. As shown in FIG. 15, the wetness N of the wet painted surface increases immediately after application, but after drying, the wetness N decreases due to rough skin during baking. Therefore, the target value of the durability N of the wet painted surface is higher than the target value of the dry painted surface. For example, assuming that the target value of the durability N of the wet painted surface is N _w and the target value of the dry painted surface is N _d , the following expression (11) is obtained. N _d = k ₂ · N _w (Equation 11) Here, k ₂ is a wet durability coefficient and is a value of k ₂ <1. This coefficient is stored in advance according to the coating conditions such as the coating color. In addition, the durability N of the wet painted surface
The target value N _w, for example, a value of the order N _w ≧ 1.0.

Next, the gloss T (glossiness) will be described. As shown in FIG. 16, the glossiness T of the wet painted surface increases immediately after the application similarly to the thickness N, but after drying, the glossiness T due to the rough surface during baking.
Drops. Therefore, the target value of the glossiness T of the wet painted surface is higher than the target value of the dry painted surface. For example, assuming that the target value of the glossiness T of the wet painted surface is T _w and the target value of the dry painted surface is T _d , the following expression (12) is obtained. T _d = k ₃ · T _w (Equation 12) Here, k ₃ is a wet gloss T coefficient, and is a value of k ₃ <1. This coefficient is stored in advance according to the coating conditions such as the coating color. In addition, the durability N of the wet painted surface
The target value T _w, for example, is the value of the order of T _w ≧ 0.6.

The calculation method of the sharpness S (H, N, T) includes a run-length method (a method of calculating from the standard deviation of slit width and the average) and a density gradient method (a method of obtaining from the density vector of slit vertical stripes). ), And a method using the power spectrum integral value P in the uneven waveform of the painted surface image. In the embodiment of FIG. 2, the fifth calculation units 9-1 to 9-4
Performs the arithmetic processing as described above, and measures the sharpness of each imaged portion. Further, the sharpness averaging processing unit 10 averages the sharpness of each part described above for each part and for the entire vehicle, and outputs an average sharpness S _a (H _a , N _a , T _a ). I do.

Next, the coating quality judging section 11 in the embodiment will be described in detail with reference to FIG. Painting quality judgment unit 11
Had an average thickness h _a calculated in the fourth calculation unit 7, and the presence or absence of sagging calculated at each of the second arithmetic unit 5-1 to 5-4,
Enter the average sharpness degree S _a obtained above distinctness of averaging processing unit 10 determines the coating quality, when it is determined to be defective, painted in order to optimize the conditions for subsequent coating conditions Outputs a command signal for changing conditions. Painting condition control system 1
3 drives the coating gun 14 according to the above-mentioned instruction signal,
Paint under optimal conditions.

More specifically, the following judgment is made.
First, the coating quality, the average thickness whether h _a is a predetermined range set in advance, the presence or absence of sag and DOI of S _a
(Especially H _a) whether there within the target range, it is determined.
When the average film thickness ha is smaller than _a predetermined range, the discharge amount of the coating gun 14 is increased, and when the average film thickness is thick, the discharge amount is decreased. Further, when the sagging occurs, it is considered that the viscosity of the coating material is insufficient or the coating amount is too large (the film thickness is large) as described above. That is, when dripping occurs and the average film thickness ha is thicker than _a predetermined range, the amount of paint discharged is too large, and when the average film thickness is in the normal range, the viscosity of the paint is insufficient. Means Therefore, the discharge amount of the coating gun 14, the number of rotations of the bell, the air pressure, the physical properties (viscosity, density, etc.) of the paint are changed according to the determination result.

[0044] Further, the average sharpness degree S _a is processed as follows. The smoothness H of the sharpness S represents the degree of large undulation distortion (long wavelength of the uneven waveform) on the painted surface as described above. This smoothness H is calculated as shown in FIG.
As shown in the figure, there is a correlation with the film thickness h, and if the coating film surface wavelength distribution is the same, the greater the film thickness, the greater the smoothness. Therefore, the average smoothness _Ha is set to a predetermined control range H _L0
Compared to to H _UP, and H _L0 ≦ H _a ≦ H film thickness change instruction value Delta] h = 0 coating quality of current is determined to be OK in the case of _UP.
Further, it is determined that in the case of H _a <H _L0 is the lack smoothness,
The film thickness is increased as the film thickness change instruction value Δh = K _h ′ (H _LO −H _a ). If H _UP <H _a , it is determined that the quality is excessive, and the film thickness is changed to the thickness change instruction value Δh = −K _h (H _a −H _UP ) so as to reduce the film thickness. Note that the above coefficients K _h and K _h ′ correspond to the slope of the characteristic shown in FIG. In FIG. 17, H ₀ is a standard film thickness, and H _0
0-10 indicates a case where the thickness is 10 μm thinner than the standard, and H _{0 + 10} indicates a case where the thickness is 10 μm thicker than the standard. Further, as shown in FIG. 18, the value of the smoothness H changes according to the elapsed time after the coating, so that the management range for determining that the coating quality is OK also has a different value according to the elapsed time. In FIG. 18, after coating 6
The OK range when the pass / fail is determined at the time of 0 second is shown.

Next, the glossiness T and the glossiness T of the sharpness are values that are mainly affected by the properties of the paint and the baking temperature. Therefore, these values are displayed on the display 12 and instructed by the operator to change the contents of the paint, the baking temperature and the like. In addition, among the elements constituting the sharpness S, the smoothness H, the thickness N, and the gloss T, the ratio of the influence on the overall sharpness is the largest, with the smoothness H being about 70%. Thus in the coating quality determination unit 11, among the average sharpness degree S _a, the average smoothness H _a only that can be performed a control that almost the target be determined using.
The meat holding degree N and the gloss degree T may be displayed on the display unit 12 or recorded, and the contents of the paint and the baking temperature may be changed at an appropriate time.

As described above, in the present embodiment, a plurality of image pickup units and an operation unit for respectively processing the image information picked up by each of the image pickup units are provided. After processing, the film thickness, the presence or absence of sagging, and the sharpness of each part are obtained, and the quality of the coating is determined using the averaged values. Therefore, it is possible to take images of many places in a short time,
Many parts having different coating conditions can be observed at the same time under the same conditions to determine the quality of the coating. for that reason,
It is possible to immediately feedback the quality of the coating state to improve the next coating condition, and to always maintain the best coating state. In the embodiment of FIG. 2, the case where all of the film thickness measurement, the determination of the presence or absence of sagging, the measurement of sharpness, and the determination of coating quality are performed is illustrated. It is also possible to configure as an apparatus that independently performs only each part of determination of presence / absence and measurement of sharpness. Further, in this embodiment, the basic measurement is performed by imaging and image processing of the painted surface, and the calculation is performed using the power spectrum integral value P and the peak wavelength λ in the long wavelength region as the information on the roughness of the painted surface. The case of performing is exemplified. However, as the roughness information of the painted surface, for example, as described in the prior application (Japanese Patent Application No. 4-306966) of the present applicant,
A method of calculating the peak-to-peak of the unevenness and the wavelength λ of the unevenness using an optical interference type surface roughness meter, or the average roughness R of the surface from the measurement result of the optical interference type surface roughness meter.
There is a method of calculation using the average wavelength of _a concave and convex lambda _a, it may be either.

Next, FIG. 19 is a block diagram of a second embodiment of the present invention. In this embodiment, the determination of the droop on the image information on the horizontal plane is omitted. Generally, drooping rarely occurs on the horizontal plane, and the second arithmetic unit 5-1
The determination of sag in 5-4 is mainly effective on a vertical surface or an inclined surface, so that the second arithmetic unit may be omitted for image information on a horizontal surface. In this embodiment, 5-1 and 5 of the four second arithmetic units are used.
-2 is omitted. Other configurations are the same as those in FIG.

Next, FIG. 20 is a block diagram of a third embodiment of the present invention. In this embodiment, the measurement of sharpness and the coating quality judging section are omitted, and the coating condition control system 13 is controlled only by the film thickness and the presence or absence of dripping. As described above, the most important smoothness of the sharpness has a correlation with the film thickness, so that merely controlling the film thickness within a predetermined standard range can provide a somewhat good coating quality. Can be kept. The other configuration is the same as that of FIG.

Next, FIG. 21 is a block diagram of a fourth embodiment of the present invention. In this embodiment, the imaging unit on the horizontal plane
The image information of the horizontal plane is omitted, and the determination of sag is omitted. In general, a vertical surface is more susceptible to problems such as dripping than a horizontal surface. Therefore, a plurality of image pickup units are provided only on the vertical surface, and the image pickup unit should be omitted for a horizontal surface which is relatively easily maintained. Thereby, the configuration can be simplified. For other configurations,
This is the same as FIG. Further, the imaging unit 2 may be configured to perform imaging at a plurality of points in time after coating, and determine the coating quality using the values of the film thickness and the like obtained respectively.

Next, a fifth embodiment of the present invention will be described. In this embodiment, the second spray coating, ie, the first coating is incompletely dried (for example, the first 1-2 coatings).
(After one minute), the coating thickness is measured when the method of performing the second coating is used. The method of performing the second spraying in a state where the first coating is not completely dried, that is, the so-called double spraying method, is generally considered to have a higher coating efficiency than the method of performing the coating with one spraying. I have. However, in the case of spraying twice as described above, as shown in FIG. 22, the coating film is formed by two layers having different viscosities between the lower layer by the first spraying and the upper layer by the second spraying. . However, in the above-described film thickness calculation, the one-time spraying is used as a reference, and if the same is applied to the two-time spraying, an error occurs in the calculation result. That is, in the case of spraying twice in the equation (8) 'wherein tau showing a _{i' i} = _3η τ shown in equation ^{_{(t i) · λ 4 /}} 16π 4 γ ... ( 8), after coating The value of η (t _i ) representing the viscosity (coating viscosity) of the paint in (1) needs to be different from that in the case of spraying once.

The details will be described below. First, η (t _i ), which is a function of time t, is expressed by the following (Equation 13). η (t _i ) = (η ₀ + k ₁ T) + (η ₁ + k ₂ T) t + k ₃ t ² (Expression 13), where η ₀ , η ₁ : initial viscosity coefficient T: paint temperature k ₁ , k ₂ : Temperature correction coefficient k ₃ : t ² correction coefficient Therefore, the coating viscosity η of the lower layer by the first spraying
_s (t) is represented by the following (Equation 14). η _s (t) = (η ₀ + k ₁ T) + (η ₁ + k ₂ T) t + k ₃ t ² (Equation 14) Further, the second spraying start time is set to t _{0 with} respect to the first time.
After a lapse of seconds, the coating viscosity η _d (t−t ₀ ) of the upper layer is expressed by the following (Equation 15). η _d (t−t ₀ ) = (η ₀ + k ₁ T) + (η ₁ + k ₂ T) (t−t ₀ ) + k ₃ (t−t ₀ ) ² (Equation 15) The synthetic coating viscosity η _g is
Assuming that the second time t ₀ is a reference time point (t ₀ = 0) and that the lower layer and the upper layer have the same film thickness, the following equation (16) is used. η _g (t) ≒ [η _s (t + t ₀ ) + η _d (t)] / 2 (Equation 16) However, by using the second time t ₀ as a reference time, η _s
And η _d are as follows. η _s (t + t ₀ ) = (η ₀ + k ₁ T) + (η ₁ + k ₂ T) (t + t ₀ )
+ K ₃ (t + t ₀ ) ² η _d (t) = (η ₀ + k ₁ T) + (η ₁ + k ₂ T) t + k ₃ t ² As described above, the value of η (t _i ) in equation (8) By using η _g (t) shown in Expression (16),
Measurement accuracy of the coating film thickness in twice spraying can be improved. Specifically, for example, when the coating film thickness is 50 to 6
In the case of about 0 μm, the measurement accuracy can be improved by about 3 to 5 μm. In the case of performing such a double spray measurement, for example, in the embodiment of FIG. 2, the coating condition input from the coating condition input unit 8 includes a distinction between the single spray and the double spray. In the case of spraying twice, the calculation may be performed using the value of the above equation (16).

[0052]

As described above, in the present invention,
A plurality of image pickup units and a calculation unit for calculating and processing the image information picked up by each of them are provided. By determining the degree and determining the quality of the coating using the average value of them, it is possible to take images of many places in a short time,
Many parts having different coating conditions can be observed at the same time under the same conditions to determine the quality of the coating. Therefore, it is possible to obtain an effect that it is possible to immediately feed back the quality of the coating state to improve the next coating condition and to always maintain the best coating state. Further, in the case of inputting the condition of the double spraying, the effect that the coating film thickness can be accurately measured even when the spraying with good coating efficiency is performed is obtained. Improvement can be achieved.

[Brief description of the drawings]

FIG. 1 is a functional block diagram of the present invention.

FIG. 2 is a block diagram of a first embodiment of the present invention.

FIG. 3 is a sectional view showing a state of a coating film after painting.

FIG. 4 is a cross-sectional view illustrating an example of an imaging unit 2.

FIG. 5 is a frequency characteristic diagram of a power spectrum PS.

FIG. 6 shows a surface roughness R corresponding to an area average value of surface irregularities.
FIG. 4 is a characteristic diagram showing a relationship between _a and a power spectrum integrated value P.

FIG. 7 is a characteristic diagram showing a wet smoothing dynamic characteristic obtained by comparing a measured value and a theoretical value of smoothing using Expression (7).

FIG. 8 is a cross-sectional view showing a state of a wet coating film surface with and without sagging.

FIG. 9 is a power spectrum integral value P representing the roughness of a painted surface.
FIG. 4 is a characteristic diagram showing a time change characteristic of FIG.

FIG. 10 is an example of a flowchart of a sag determination.

FIG. 11 is an example of a flowchart showing a sharpness calculation.

FIG. 12 is a diagram illustrating an example of a stripe image read by an imaging unit.

FIG. 13 is a diagram showing image processing in smoothness calculation.

FIG. 14 is a characteristic diagram showing a relationship between elapsed time after painting and smoothness H.

FIG. 15 is a characteristic diagram showing the relationship between the elapsed time after painting and the degree of durability N.

FIG. 16 is a characteristic diagram showing a relationship between elapsed time after coating and glossiness T.

FIG. 17 is a characteristic diagram showing a relationship between a wet film thickness h and a wet smoothness H.

FIG. 18 is a characteristic diagram showing a relationship between elapsed time after painting and wet smoothness H.

FIG. 19 is a block diagram of a second embodiment of the present invention.

FIG. 20 is a block diagram of a third embodiment of the present invention.

FIG. 21 is a block diagram of a fourth embodiment of the present invention.

FIG. 22 is a characteristic diagram showing a relationship between elapsed time and coating viscosity in twice spray coating.

FIG. 23 is a cross-sectional view of an example of a conventional device.

[Explanation of symbols]

Reference Signs List 1: Body to be coated (body) 2-1, 2-2, 2-3, 2-4 ... Imaging unit 3-1, 3-2, 3-3, 3-4 ... Image processing unit 4-1 and 4 -2, 4-3, 4-4 ... first operation unit (roughness measurement) 5-1, 5-2, 5-3, 5-4 ... second operation unit (dripping judgment) 6-1, 6- 2, 6-3, 6-4: third calculation unit (film thickness calculation) 7: fourth calculation unit (average film thickness calculation) 8: coating condition input unit 9-1, 9-2, 9-3, 9 -4: Fifth calculation unit (definition calculation) 10 ... Definition averaging processing unit 11 ... Coating quality judgment unit 13 ... Coating condition control system 12 ... Display 14 ... Coating gun 100 ... Imaging means 105 ... Average film Thickness calculating means 101 image processing means 106 dripping determining means 102 roughness calculating means 107 coating quality determining means 103 coating condition inputting means 108 sharpness calculating means 104 film thickness calculating means Step 109: Mean sharpness calculating means

Continuation of the front page (56) References JP-A-6-160071 (JP, A) JP-A-6-160029 (JP, A) JP-A-6-265316 (JP, A) JP-A-6-160300 (JP JP-A-7-83852 (JP, A) JP-A-5-256773 (JP, A) JP-A-5-90371 (JP, A) JP-A-1-164463 (JP, A) 4-50714 (JP, A) JP-A-5-141941 (JP, A) (58) Fields investigated (Int. Cl. ⁷ , DB name) G01B 11/00-11/30 B05C ⁷ /00-21 / 00 G01N 21/84-21/958 G06T 1/00

Claims (6)

(57) [Claims] 1. A plurality of image pickup means for picking up the roughness of an undried coating surface immediately after application of a paint on different portions of a coating surface, and image information from the plurality of image pickup means are respectively image-processed. Image processing means, based on the image processing data processed by the image processing means, the roughness degree of the coating surface, and a roughness calculating means for calculating the wavelength of the uneven waveform of the coating surface for each of the locations, A coating condition input means for inputting coating conditions including at least the viscosity of the paint; a time change amount and a wavelength of the roughness obtained from the roughness calculated by the roughness calculating means; and the coating condition input means. A film thickness calculating means for calculating the coating film thickness for each of the above-mentioned locations based on the coating conditions, and an average film for calculating an average film thickness of the coated surface based on the calculation result of the film thickness calculating means. Thickness calculation means , Paint film thickness measuring device characterized by comprising a. 2. A plurality of image pickup means for picking up the roughness of the undried coating surface immediately after the application of the paint at different points on the coating surface, and image information from the plurality of image pickup means are image-processed respectively. Image processing means, based on the image processing data processed by the image processing means, the roughness degree of the coating surface, and a roughness calculating means for calculating the wavelength of the uneven waveform of the coating surface for each of the locations, A coating condition input means for inputting coating conditions including at least the viscosity of the paint; a roughness calculated by the roughness calculating means; a time change amount of the roughness calculated from the roughness, and the wavelength And based on
Sagging determining means for judging the presence or absence of sagging of the painted surface for each of the above-mentioned portions, and the time change amount and the wavelength of the roughness obtained from the roughness calculated by the roughness calculating means, and the coating conditions A film thickness calculating means for calculating the coating film thickness for each of the above-described locations based on the coating conditions from the input means; and calculating an average film thickness of the coating surface based on the calculation result of the film thickness calculating means. Average film thickness calculating means to perform, the average film thickness calculated by the average film thickness calculating means, and the quality judgment according to the quality judgment level of the predetermined coating quality according to the judgment result of the sagging judgment means. And a coating quality determining means for calculating an optimum film thickness in accordance with the quality determination level. 3. A plurality of image pickup means for picking up the roughness of the undried coating surface immediately after the application of the paint at different locations on the coating surface, and image information from the plurality of image pickup means is image-processed. Image processing means, based on the image processing data processed by the image processing means, the roughness degree of the coating surface, and a roughness calculating means for calculating the wavelength of the uneven waveform of the coating surface for each of the locations, A coating condition input means for inputting coating conditions including at least the viscosity of the paint; a roughness calculated by the roughness calculating means; a time change amount of the roughness calculated from the roughness, and the wavelength And based on
Sagging determining means for judging the presence or absence of sagging of the painted surface for each of the above-mentioned portions, and the time change amount and the wavelength of the roughness obtained from the roughness calculated by the roughness calculating means, and the coating conditions A film thickness calculating means for calculating the coating film thickness for each of the above-described locations based on the coating conditions from the input means; and calculating an average film thickness of the coating surface based on the calculation result of the film thickness calculating means. Average film thickness calculating means for performing; sharpness calculating means for calculating the sharpness of the painted surface for each of the locations based on the image processing data processed by the image processing means; and sharpness calculating An average sharpness calculating means for calculating an average sharpness of the painted surface based on a calculation result of the means; an average film thickness calculated by the average film thickness calculating means; a determination result of the sagging determining means; With the average definition calculated by the average definition calculation means Coating quality determination means for performing quality determination according to a predetermined quality determination level of coating quality, and calculating an optimal film thickness in accordance with the quality determination level. Paint film thickness measuring device. 4. The image pickup means includes an image pickup means for picking up an image of a non-horizontal surface of the object to be coated, and an image pickup means for picking up an image of a horizontal surface. 4. The coating film thickness measuring device according to claim 1, wherein the determination of the presence or absence of dripping is performed only for the image information. 5. The spray condition input means includes a first spray coating in which the coating is performed only by one spray, and a second spray coating in which the second spray is performed in a state where the first coating is incompletely dried. The film thickness calculating means calculates the film thickness using different paint viscosity values in the first spray coating and the second spray coating. Claims 1 to 4 characterized in that:
The coating film thickness measuring device according to any one of the above. 6. The coating viscosity in the second spray coating is defined as an average value of the lower layer coating viscosity by the first spraying and the upper layer coating viscosity by the second spraying. The coating film thickness measuring device according to claim 5, wherein the calculation is performed.