JP3460541B2 - Method and apparatus for inspecting defects on inspected surface - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method and apparatus for inspecting a defect of a surface to be inspected, which optically inspects the state of the surface to be coated in the production process of an automobile, and more particularly to a defect as the coating is repeatedly applied. The present invention relates to a method and an apparatus for inspecting a defect on a surface to be inspected, which enables the user to easily know how the changes in the number of times are changed.

[0002]

2. Description of the Related Art Conventionally, various types of surface defect inspection apparatuses have been invented for optically inspecting the coating state of a vehicle. Among these, for example, JP-A-2-73139. In Japanese Patent Application Laid-Open No. 5-45142 or the like, a coating surface, which is an inspection surface, is irradiated with light or dark light in which a predetermined stripe or a predetermined change in light and dark is repeated, and the surface of the coating has irregularities In this case, a defect on the surface of the surface to be inspected is detected by differentiating the received light image having a difference in brightness (luminance) or a change in brightness due to the unevenness.

Vehicles are generally painted in the order of electrodeposition coating, intermediate coating, and topcoating. Conventionally, an operator visually judges whether or not there is a defect after the completion of electrodeposition coating. After this reworking is completed, intermediate coating is applied, and after this coating, the operator again visually judges the presence or absence of defects and corrects it, and then after the overcoating, the defect inspection using the surface defect inspection device is performed. Then, the operator corrects it based on the inspection result, and when the repair is finished, the vehicle is transported to the outfitting process.

[0004]

However, conventionally, the inspection using the surface defect inspection apparatus is performed only when the overcoating process is completed, and the inspection of the coating in the previous process is based on the experience of the operator (reworking is required). It was very difficult for the operator to judge whether the defect was a proper defect or not, and it was very difficult to judge this. Therefore, from the viewpoint of the entire painting process, the repair work performed three times is by no means efficient. It cannot be said that.

This is a defect that requires rework (a defect that is completely buried by painting in the subsequent process).
However, neglecting the repair of defects (defects that become larger by being buried in the coating of the subsequent process) that may grow in the coating of the subsequent process unless they are modified. The work of the former causes excessive work, which reduces work efficiency, and the work of the latter corrects the defect at a later step than when the defect is found. This is because it takes more time to perform, which causes a decrease in work efficiency.

In order to solve such a conventional problem to some extent, as disclosed in Japanese Unexamined Patent Publication No. 5-196444, detection of a coating defect obtained by detecting an intermediate coating state. Some are trying to utilize the data for reviewing the coating conditions for intermediate coating.

By feeding back the detection data of the coating defects to the coating process as described above, it is possible to suppress the occurrence of defects even a little, the repair work of the coating is reduced, and the work of the entire coating process is reduced. Efficiency will be improved. However, even with such a technique, there is still room for improvement in streamlining the work of the entire painting process.

The present invention has been made to solve the above-mentioned conventional problems, and it is possible to easily know how defects progress as coating is applied repeatedly. The defect inspection method of the surface to be inspected, which can contribute to the improvement of quality while determining the defects that need rework and the defects that do not The purpose is to provide a device.

[0009]

Means for Solving the Problems The present invention for achieving the above object is configured as follows. The invention according to claim 1 is a defect inspection method for a surface to be inspected, which is most suitable for a coating process in which the surface to be inspected is coated a plurality of times. It is characterized in that the degree of defect is memorized for at least two paintings for each defect, and the change in the position and degree of the memorized defect can be examined in time series to know the transition of the defect. This is a method for inspecting defects on a surface to be inspected.

A second aspect of the present invention is a defect inspection method for a surface to be inspected, which is most suitable for a coating process in which the surface to be inspected is coated a plurality of times. Each time the coating is completed, the surface to be inspected is inspected. It is characterized in that the position and the degree of the defect existing in the memory are stored for each defect, and the change of the stored position and the degree of the defect can be examined in time series to know the transition of the defect. This is a method for inspecting defects on a surface to be inspected.

According to a third aspect of the present invention, in the defect inspection method for a surface to be inspected according to the first or second aspect, the positions of the defects existing on the surface to be inspected are three-dimensional (X, Y, Z). Given as coordinates, the degree of defect is characterized by a rank assigned by the size of the defect.

According to a fourth aspect of the present invention, there is provided a defect inspection apparatus for a surface to be inspected, which is applied to a coating process of coating the surface to be inspected a plurality of times, wherein the surface to be inspected is coated every time coating is completed. Defect detecting means for detecting the position and the size of the defect existing in the, the storage means for storing the position and the size of the defect detected by the defect detecting means, the defect of the same inspected surface from the storing means. A defect inspection apparatus for a surface to be inspected, comprising: a display unit for displaying a transition of a defect by extracting a position and a size.

According to a fifth aspect of the present invention, in the defect inspection apparatus for an inspected surface according to the fourth aspect, the position of a defect existing on the inspected surface is expressed as a three-dimensional coordinate of X, Y, Z. Given and also the degree of defect is characterized by a rank assigned by the size of the defect.

[0014]

As described above, according to the present invention, the following effects can be obtained by the constitution for each claim. According to the inventions of claims 1 to 3, the transition of defects on the same surface to be inspected can be known based on the position and size of the defects stored in time series at each coating. Therefore, it is possible to easily know the defects that must be reworked and the defects that are not, and based on this, it becomes possible to improve the efficiency of the painting work.

According to the fourth and fifth aspects of the present invention, the result of transition of the defect on the same surface to be inspected is displayed on the basis of the position and size of the defect stored in time series for each coating. Since it can be displayed on the screen, it is possible to easily know the defects that must be reworked and the defects that are not, and based on this, the efficiency of the painting work can be improved.

[0016]

BEST MODE FOR CARRYING OUT THE INVENTION An embodiment of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing a schematic configuration of a defect inspection apparatus for carrying out a defect inspection method for an inspection surface according to the present invention. In the figure, the surface 1 to be inspected corresponds to, for example, the coating surface of a vehicle body conveyed by a conveyor from a coating booth. The properties of the coated surface are slightly different depending on factors such as the concentration of the coating and the coating amount, but the apparatus shown in FIG. 1 is capable of quantifying and measuring it.

The coated surface 1 is irradiated with a stripe-shaped light-dark pattern (bright-dark pattern), and the light-dark pattern is formed by the stripe grating 3 provided in the lighting device 2. The illumination device 2 and the stripe grating 3 constitute a stripe pattern irradiation device (see FIG. 2) described later.

The area irradiated with this stripe-shaped light-dark pattern, that is, the imaged site A is displayed by the CCD color camera 5. The CCD color camera 5 is capable of capturing a color image. For example, the stripe image of the imaged site A is transferred to the image processing device 9 via the camera control unit 7 at regular intervals of about 1/30 second. I am supposed to send it. The image processing device 9 is provided with a storage device that stores the stripe image (also referred to as a light-dark pattern image or a light-receiving image) captured at regular intervals. This storage device can naturally store color images. That is, R
It has a function of storing an image for each GB.

In this embodiment, the surface 1 to be inspected is designed to move in the direction of the arrow shown in the figure (C
Since the CD color camera 5 is provided), the stripe image captured by the CCD color camera 5 at regular intervals is an image in which the imaged site A on the surface 1 to be inspected is displaced at regular intervals. When one still image picked up by the CCD color camera 5 is processed by the image processing device 9 and displayed on the color monitor 10 which is a display means, an image as shown in the drawing is obtained, which is a convex shape existing on the painted surface 1. The defect B is detected. Since the color of the defect B can also be determined as a matter of course, the cause of the defect can be determined to some extent.

Although the surface to be inspected 1 is moved in this embodiment, the CCD color camera 5 may be moved to change the imaged site A on the surface to be coated 1 with time. When moving the inspected surface 1,
Although not shown, a conveyor such as a belt conveyer serves as a moving unit, and when the CCD color camera 5 is moved, a loader or a robot to which the CCD color camera 5 is attached serves as a moving unit.

The image processing apparatus 9 includes a host computer 1
2 is connected, the final recognition of the presence of defects on the surface 1 to be painted is done by this host computer 12. That is, the number of pulses (corresponding to the movement amount) from the pulse generator 14 for recognizing the movement amount of the surface 1 to be inspected conveyed by the above-mentioned conveyor, and the image processing device 9
Based on the defect candidate points obtained from a plurality of images arranged in time series detected by, the moving amount of the defect candidate points detected in the still image is the actual movement of the surface 1 to be painted, in other words For example, it is calculated whether or not it is proportional to the movement amount of the imaging region A, and if it is proportionally moved, it is determined that the detected defect candidate point is the defect B existing on the surface to be inspected. Will be done.

Further, the defects are comprehensively ranked according to the color, area, and size (aspect ratio) of the determined defects. That is, the operator can immediately determine the degree of the defect.
In order to perform this ranking, it is necessary to create a database by classifying the characteristics of color, size (area), and shape (aspect ratio) for each defect type. Therefore,
This database is stored in the storage device in the host computer 12.

In the storage device of the host computer 12, the size and rank of the defects determined as described above are provided for each defect, and after the electrodeposition coating, the intermediate coating and the top coating. Memorized about the painted surface. Further, the stored contents can be displayed on the color monitor 10. Although what kind of display will be made concretely will be described later, what rank of defect should be repaired can be easily discriminated from this display, and the work standard regarding the repair work of the painting process can be defined. It becomes possible to make.

In FIG. 2, the stripe pattern is applied to the surface 1 to be inspected.
It is a figure which shows the structure of the striped pattern irradiation apparatus for irradiating to. The lighting device 2 includes a straight tube fluorescent lamp 2
As shown in FIG.
A diffusing plate 2b that scatters and diffuses the light of the fluorescent lamp 2a is attached to the front side of a. The diffusion plate 2b is for scattering the light from the fluorescent lamp 2a to create a light source similar to a surface light source, and is made of, for example, frosted glass. A stripe plate 3 for forming a stripe pattern is attached to the front side of the diffusion plate 2b.
The stripe plate 2c is a transparent or diffusing plate having black stripes at predetermined intervals.

Therefore, the light from the fluorescent lamp 2a is diffused by the diffusing plate 2b, and the light made planar by the diffusing plate 2b is irradiated onto the surface 1 to be inspected through the stripe pattern 2c. Therefore, a bright-dark pattern similar to the stripe pattern 2c is projected on the surface 1 to be inspected.

FIG. 3 shows a stripe pattern irradiation device for forming a stripe pattern without using the diffusion plate 1b. In this irradiation device, a light source 2d for generating diffused light is arranged as shown in the drawing, and its back surface 2e is painted black. Even if such an irradiation device is used, it is possible to project the same bright and dark pattern as the irradiation device shown in FIG.

FIG. 4 is a block diagram showing the internal structure of the image processing apparatus 9 shown in FIG. The buffer amplifier 20 provided in the image processing device 9 has a function of temporarily storing the image signal from the camera control unit 7. In addition, the A / D converter 22
Has a function of converting the image signal stored in the buffer amplifier 20 into digital data. Therefore, the striped light-and-dark image projected on the surface to be coated 1 captured by the CCD color camera 5 is finally converted into a digital value. For example,
This digital value is converted into a brightness level of 8 bits for each color of RGB, and one screen is captured with a resolution of 512 × 512 pixels.

Further, the microprocessor unit 24
Has a function of storing the brightness value of each pixel output from the A / D converter 22 in the memory 26 for each color of RGB, and outputting to the host computer 12. In the present embodiment, the memory 26 stores images of three coated surfaces, that is, a coated surface after electrodeposition coating, a coated surface after intermediate coating, and a coated surface after top coating. The D / A converter 28 has a function of returning the digitized image signal output from the microprocessor unit 24 to an analog value and outputting the analog value to the color monitor 10.

The detection of defect candidate points by the image processing device 9 thus configured will be described in detail with reference to FIG.

FIG. 5A is a diagram showing a moving state of the defect B on the surface 1 to be inspected, which moves with the passage of time.

Bright and dark stripes are radiated on the surface 1 to be inspected through the stripe plate 3, but in the case where there are irregularities B as shown in the drawing in the white stripes, Since the irradiation light is diffusely reflected at the defect B portion, the luminance of the defect portion becomes smaller than that of the other portions.

FIG. 5B is an example of an image of the imaged site B imaged by the CCD color camera 5 when the defect B exists in the white stripe. Since the stripe-shaped bright and dark pattern is irradiated on the imaging region A, the image displayed by the color monitor 10 is as shown in the figure. Such a light-receiving image is captured as an original image in the image processing apparatus 9. However, since the resolution of one screen is 512 × 512 as described above, the vertical axis and the horizontal axis each have 512 pixels.

When the coordinate axes x and y are taken with the upper left corner of the screen in FIG. 5B as the origin and one line in this image is represented by the brightness level, it corresponds to the brightness value as shown in FIG. 5C. A waveform signal is obtained. That is, the brightness value of the portion corresponding to the bright portion is large, and conversely, the brightness value of the portion corresponding to the dark portion is small. In the illustrated image, a defect candidate point exists in the bright portion, but the defect candidate point appears as a portion having a small brightness value in a part of the area detected as the bright portion. If the area with a small brightness value existing in the bright area is larger than a certain size, it is determined that this is a defect existing on the surface to be inspected.

However, in the present embodiment, it is determined that the defect is the final defect by also judging such "whether the defect moves according to the movement of the image pickup area".
In the unlikely event that the defect candidate point recognized in only one still image captured as shown in FIG. 5B is noise, the imaged part in the subsequent time-series images is captured. This is because it is considered that the defect candidate point is not recognized in the form in which the defect candidate point moves along with the movement of.

FIG. 6 is a flow chart showing the processing sequence and processing contents of the defect inspection method for the surface to be inspected or the apparatus therefor according to the present invention. First, in detecting a defect, an image of the imaging portion B of the surface to be inspected is captured from the CCD color camera 5. The captured image is the image processing device 9
Are stored in the memory 26 (S1). The stored image is subjected to an emphasis process in order to easily extract a defective portion. As this emphasis processing, known emphasis processing such as area determination is used (S2). The image processing apparatus 4 performs the above-described enhancement processing and defect candidate point extraction processing on all of the stripe images stored in the memory 26 in time series. The image after these processes is stored in another address of the memory 26 again.

The host computer 12 inputs the image after the image processing, and moves in time series in each image based on the position and size of the defect candidate points extracted from each image. If it is determined that this movement amount is synchronized with the movement of the imaging region obtained from the pulse generator 14, the defect candidate point is the defect actually existing on the surface to be inspected for the first time. To decide. Then, the area and shape of the defect candidate points, the ratio of the vertical and horizontal dimensions of the shape, and the color are input for each of the input images.The average of these values is calculated, and finally the defect area, aspect ratio, and color are specified. , This is compared with the data stored in the ranking database to rank defects (S3). The above processing is continuously performed until the end command is issued from the outside (S4). Also,
This treatment is performed on each of the three coated surfaces, that is, the coated surface after the electrodeposition coating, the coated surface after the intermediate coating, and the coated surface after the top coating.

Next, the operation of the method and apparatus of the present invention will be described in detail based on the flowcharts of FIGS. 7 to 9 and with reference to the drawings of FIGS. S11 First, the CCD color camera 5 inputs the stripe image at time TN and stores the stripe image in the memory 26 of the image processing device 9 as a color image. At this time, the count of the number of pulses from the pulse generator 14 that indicates the position of the imaged region A of the CCD color camera 5 is reset to zero. This reset is performed by the host computer 12 that operates in synchronization with the image processing apparatus 9.

S12 Next, the image processing device 9 detects the stored stripe image,
That is, the enhancement process for facilitating the extraction of the defective portion is performed on the original image. By this emphasis processing, only the portion considered to be a defect included in the original image is extracted.

As a concrete example of this emphasizing process, for example, two types shown in FIG. 10 are illustrated.

The emphasizing process shown in FIG. 9A is to detect a defective portion by area determination. When an original image as shown in the figure is taken, it is converted into a video waveform with the luminance as the vertical axis, and the waveform becomes as shown on the right side. This waveform is the average luminance value and the threshold level. Is binarized by the signal (FIG. 2), and only the signal within a predetermined width of this binarized signal is extracted (FIG. 2) and made into a defective portion.

Next, the emphasizing process shown in FIG. 10B is to detect a defective portion by smoothing. When an original image as shown in the figure is taken and converted into a video waveform with luminance as the vertical axis, the waveform becomes as shown on the right side, but this waveform must be smoothed. Smoothing (see Fig.), Subtracting the video waveform from the video waveform of to obtain the absolute value (see Fig.), Binarizing this waveform at a specified threshold level, and binarizing the signal. (The same figure) is made a defective part.

As an example, the defective portion is extracted from the original image by performing the above processing. The detection of the defective portion can be performed by any other known method.

S13 : The counter value i for counting the number of original images is set to 1. In step S14, the N-1th defective portion processed as described above and the defective portion detected in the Nth original image are compared.
In the above processing, since only one original image has been captured yet, this comparison cannot be actually performed. However, when two or more original images have been captured, the image capturing is performed immediately before. The comparison with the original image that has been performed will be performed.

The S15 host computer 12 counts the pulses output from the pulse generator 14, calculates the position of the imaging region A based on the counted number of pulses, and calculates the Nth original image and the Nth image. The amount of movement D of the imaged part of the original image taken as the -1st sheet is calculated. The S16 host computer 12 calculates the distance between each of the defect parts extracted from the original image in S12 and the defect point extracted from the (N-1) th original image, and sets the distance to d.
And

The moving distance d of each defect point calculated in S17 and S18 is the imaging region A.
It is judged whether or not the distance is substantially equal to the moving distance D of all defect points extracted from the original image. If each of the extracted S19 defect points exhibits a movement amount substantially equal to the movement amount D of the imaging region, this defect point is registered as a defect candidate point. After this registration, the area of this defect candidate point, the aspect ratio of the shape, the color of the defect point, and the background color are detected, and these are also registered.

The processing of S20, S21, S22 and above is performed for all the defective portions of the image up to N screens before the newly captured original image. For example, when N = 5 is set, the time points TN-1, TN-2, TN-3, and TN- are set for all the defective portions extracted from the original image captured at the time TN.
4 and TN-5 are collated with the defective portions extracted from the original images captured, and the movement amount of the defective portion, which is a defect candidate point, is captured for each defective portion. It is determined whether or not the movement amount is substantially equal to the movement amount.

In this embodiment, it is calculated whether or not the relation of D = d is established for all the defect points imaged in the past and extracted from the image. It is also possible to detect a defect candidate point by performing the above-described processing on one image. At first glance, this kind of processing seems to reduce the recognition accuracy,
Even if only one sheet is to be extracted as a defect portion, it will be picked up as a defect candidate point even if it has not been extracted. Is a defect candidate point.

By the processing of S23 and above, the number of times registration is performed for the same defect candidate point is counted. S24, S25 When the count number is equal to or larger than the preset count number, the defect candidate point is determined to be a defect existing on the surface to be inspected. Then, the three-dimensional position (X, Y, Z) of this defect point is recognized and stored. The processing from S26 onward is continued until a work end command is issued.

The flowchart shown in FIG. 9 is a subroutine flowchart of step 25 shown in FIG.
In the process of step 25, in addition to determining that the defect is a defect, a process for displaying the extent of the defect detected by the color monitor 10 is also performed.

As described above, the area of the defect candidate point, the aspect ratio of the shape, the color of the defect candidate point, and the background color are calculated for each color image and stored in the storage device of the microprocessor unit 24. , The microprocessor unit 24 calculates the average from the area of each defect candidate point (S
25a), the degree of variation in the area is also calculated. The area average of the defect candidate points is set as the area of the defect, and the rank of the size of the area is determined based on the data of the stored database.

Further, when the variation in area is large,
It is possible to determine whether the defect is a crater, dust, or crap. The reason why such a judgment can be made is that there is a correlation in the variation of the area depending on the type of defect. For example, if it is a crater. Since the surface angle of the defect is close to the normal surface, the area tends to be small near the center of the stripe. By investigating such a variation in the area of the defect, it is possible to determine whether the defect is caused by a crater, dust, or lumps (S25b).

Further, the microprocessor unit 24
Calculates the ratio of the vertical and horizontal dimensions of the shape of each defect candidate point and obtains the average value as the aspect ratio of the defect (S25c). When the aspect ratio of the defect is obtained in this manner, it is possible to easily determine whether the defect is caused by a thread dust, a line flaw, or a dust spot. For example, those having a large aspect ratio are determined to be thread dust and line scratches. In some cases, it may be difficult to accurately determine the type of defect based only on the aspect ratio, and in such a case, the type of defect may be determined in relation to the area of the defect. For example, the aspect ratio (large /
If (small) is 2 or more and the area thereof is 1/3 or less of the vertical × horizontal value, it is determined to be thread dust or line scratch (S25d).

Further, the microprocessor 24 recognizes the color of each defect candidate point and the background color thereof and obtains the average value thereof as the defect color. At the same time, the color variation is also obtained (S25e). As a result of this color recognition, it is determined whether the dust is buried dust or exposed dust depending on the difference between the background color and the defect color. This determination is based on the fact that the color of the defect is close to the background color in the case of buried dust, and the color peculiar to the material appears in the case of exposed dust.

As described above, in the case of exposed dust, the defective material can be determined by the color of the defect. For example, when the color of the defect is black, soot of the boiler adheres or welding occurs in the coating process. It can be judged that a defect has occurred due to the lack of spatter in the process, and in the case of gray or yellow, it can be judged that aluminum powder, brass or copper powder has adhered. . In this way, if the adhered object is known, it can be useful for investigating the cause of the defect. For example, when it is determined that the soot of the boiler is attached, it is possible to reduce the occurrence of defects by taking measures to prevent the soot of the boiler from flying (25f).

The area of the defect calculated as described above,
The aspect ratio of the defect shape, the background color, and the defect color are displayed on the color monitor 10. Finally, the results of these operations are combined to rank how defective the defect is. This ranking is performed by comprehensively determining the defect area, the aspect ratio of the defect shape, the background color, and the defect color. This judgment is made based on the data stored in the above-mentioned database. For example, if the background color is green, the defect color is black, the average area is very small, and the aspect ratio is very large, it can be determined that the yarn scratches are inconspicuous, so the overall rank of defects is low (for example, 10). On the other hand, even in the case described above, when the background color is white, it is an exposed defect and is conspicuous, and therefore the overall rank of the defect is higher than that in the case described above (for example, 15).

The worker will make a repair by looking at this comprehensive rank, but uniform repair work becomes possible by standardizing what kind of repair is required according to the rank (S25g). . It should be noted that the database is assigned an optimum value based on the data obtained as a result of the accumulation and the experience so that the database is appropriately ranked.

In the same figure in which the above-mentioned processing is arranged and explained again based on FIG. 11, each image from time t1 to time t8 is an image taken by the CCD color camera 5 at each time, and on the right side thereof. Image is an image after defect enhancement processing is performed on these original images. That is, it is an image in which a defective portion is extracted from each original image.

Now, the processing when the image at the time t6 is picked up by the CCD color camera 2 will be described. If defect enhancement processing is performed on the original image at this time, as a defective portion,
Six of a, b, c, d, e and f are extracted. First, it is determined whether or not the extracted defect point a is detected at points separated by a constant distance from each of the 5 images (N = 5) from t5 to t1. As a result of this determination, the defect point a and the defect point b are detected with a certain distance apart, so both of these points are registered as defect candidate points. Then, the area of this defect candidate point, the aspect ratio, the defect color, and the background color are detected. It should be noted that the defect points from c to f do not show any movement and are therefore treated as simple noise.
It is not registered as a defect candidate point. Such processing is
The same applies to the four images t4, t3, t2, and t1. Note that, as shown in the figure, the defect point a disappears (not extracted) in the image at t3. Therefore, in the image comparison process between t6 and t3, the defect portion a is not registered as a defect candidate point.
In the above process, the defective portion a will be registered four times, and the defective portion b will be registered three times. In this processing, if only defects that have been registered three times or more (count M = 3) are determined to be defects, both points a and b are determined to be defects existing on the surface to be inspected. It will be.

In this embodiment, since the defect is extracted from the stripe-shaped light-dark image, the portion located at the light-dark boundary may be extracted as a defect point. If this is moved and extracted along with the movement of the imaging region, it will be erroneously detected as a defect, so in order to prevent this, for areas other than the boundary,
Alternatively, if the defect extraction process is performed only on the bright pattern region, it is possible to realize more accurate defect detection.

The defect inspecting apparatus which recognizes the existence of a defect by the above-described processing, and in which the three-dimensional position and size of the defect are stored in a storage device (not shown) in the host computer 12 for each defect, , The electrodeposition coating process, the intermediate coating process and the top coating process are provided in the inspection departments, and the data sent from these departments are collected in one defect inspection device and the total data of the defect inspection results is collected. Will be created.

Hereinafter, this state will be described in detail with reference to the drawings. FIG. 12 is a diagram showing how the defect inspection method and the defect inspection apparatus of the present invention are applied to a coating process.

As shown in this figure, first, when the electrodeposition coating of the vehicle body is completed, it is inspected by the defect inspection apparatus of the present invention whether or not there is a defect on the coated surface. If it is determined as a result of this inspection that there is a defect, the worker is shown where the defect exists, and the worker repairs accordingly. Further, the data regarding the defect detected in this step (where the defect exists and what rank the defect is) is stored in the host computer 12.
Sent to.

Next, when the intermediate coating is completed, the same inspection as in the case of electrodeposition coating is performed and the repair is performed. Data regarding defects in this step are also sent to the host computer 12. The rework in this case is performed by a specific instruction given by the host computer 12. Finally, when the overcoating is finished, the inspection and repairs are performed as in the case of electrodeposition coating. Data regarding defects in this step are also sent to the host computer 12. The rework in this case is also performed by a specific instruction given by the host computer 12.

As shown in FIG. 13, in each of the electrodeposition coating process, the intermediate coating process, and the top coating process, the host computer 12 can determine the location of the defect existing on the same coated surface of the same vehicle body and its rank. The data is collected, but if one example is shown, the data will be as shown in FIG. The data shown in this figure is the data actually displayed on the color monitor 10, and is the result of painting in the subsequent steps without any modification in each step.

Calculating how such defects on the same coated surface change from after electrodeposition coating to after top coating, there is no need to rework as shown in the lower table of FIG. Things that disappear, and things that grow in size every time you paint will be clearly visible.

For example, the defect N found after electrodeposition coating
Regarding O1 and NO2, it can be seen that they disappeared after the intermediate coating, but from this, it can be seen that those with a defect rank up to 8 after electrodeposition coating are defects that need not be reworked. . Similarly, the defects NO6 to NO9 found after the intermediate coating have disappeared after the top coating, but those having a defect rank of up to 10 after the intermediate coating do not need to be reworked. . In this way, it is possible to investigate how defects at the same position on the same painting surface change with each painting, and to feed back the results to the rework work of each painting process. It is possible to clearly distinguish which defect is found and which one does not need to be corrected, and the defect inspection device is made to make this distinction. If it can be put out, useless work can be eliminated, efficiency of rework work can be improved, and coating quality can be improved.

If the results of the above-described defect transition (defect tracking) are accumulated in the actual work as shown in FIG. 13 and learned by the host computer 12, the defect rank to be corrected can be determined. The accuracy of judgment will be improved, and it will be possible to contribute to more efficient repair work and provision of higher quality painted surfaces. Since the defect inspection device of the present invention can detect the color and background color of the defect, the result of the transition of the defect as described above can be obtained by vehicle type,
By accumulating each paint color, it will be possible to apply it to the body of every car. In the above embodiment, the defect inspection device is provided for each painting process.However, only the device for inputting the image of the painting surface is provided for each process, and the collected data is provided separately. It may be configured to accumulate or analyze by a computer that is installed, and to give a specific instruction of the rework operation to the operator from the analysis result.

[Brief description of drawings]

FIG. 1 is a block diagram showing a schematic configuration of a defect inspection apparatus for carrying out a defect inspection method for an inspection surface according to the present invention.

FIG. 2 is a schematic configuration diagram of an illumination device used in the device shown in FIG.

FIG. 3 is a diagram showing another form of the illumination device used in the device shown in FIG.

FIG. 4 is a block diagram showing an internal configuration of the image processing apparatus shown in FIG.

5A is a diagram showing an imaging state of a surface to be inspected, FIG. 5B is an example of an image of an imaging region imaged by a CCD color camera at a certain time, and FIG.
[Fig. 4] is a diagram in which the image in (B) is replaced with a graph showing the relationship between position and luminance value.

FIG. 6 is a flowchart showing a processing order or processing contents of a method of inspecting a defect on a surface to be inspected or an apparatus therefor according to the present invention.

FIG. 7 is a flowchart showing a process of the present invention.

FIG. 8 is a flowchart showing a process of the present invention.

9 is a flowchart of a subroutine of step 25 shown in FIG.

FIG. 10A is an explanatory diagram of a method of extracting a defective portion by area determination, and FIG. 10B is an explanatory diagram of a method of extracting a defective portion by smoothing.

FIG. 11 is an explanatory diagram of a process of defect extraction according to the present invention.

FIG. 12 is a flow chart showing a procedure of work in a coating process to which the device of the present invention is applied.

FIG. 13 is a flowchart showing a procedure for checking the transition of defects.

FIG. 14 is a diagram showing a processing result of the present invention.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 ... Inspected surface, 2 ... Illumination device 3 ... Stripe plate, 5 ... CCD color camera, 7 ... Camera control unit, 9 ... Image processing device 10
... monitor, 12 ... host computer, 14 ... pulse generator, 24 ... microprocessor unit, 26
…memory.

Claims (5)

(57) [Claims] 1. A defect inspection method for a surface to be inspected, which is most suitable for a coating process of coating the surface to be inspected a plurality of times, wherein the position of a defect existing on the surface to be inspected after coating and the degree of the defect. Is stored for at least two coatings for each defect, and changes in the position and degree of the stored defect can be examined in time series so that the transition of the defect can be known. Defect inspection method. 2. A defect inspection method for a surface to be inspected, which is most suitable for a coating process of coating the surface to be inspected a plurality of times, wherein the position of the defect existing on the surface to be inspected each time the coating is completed, A defect inspection method for a surface to be inspected, characterized in that the degree of defect is stored for each defect, and the change in the position and degree of the stored defect can be checked in time series to know the transition of the defect. . 3. The position of the defect existing on the surface to be inspected is
The surface to be inspected according to claim 1 or 2, which is given as a three-dimensional coordinate of X, Y, and Z, and the degree of the defect is a rank assigned by the size of the defect. Defect inspection method. 4. A defect inspection apparatus for a surface to be inspected, which is applied to a coating process for coating the surface to be inspected a plurality of times, wherein a position of a defect existing on the surface to be inspected and Defect detecting means (24) for detecting the size, storage means (26) for storing the position and the size of the defect detected by the defect detecting means (24), and the same target from the storage means (26). Display means (1 to display the transition of defects by extracting the position and size of defects on the inspection surface
0) and a defect inspection device for an inspected surface. 5. The position of the defect existing on the inspection surface is
The defect inspection apparatus for an inspected surface according to claim 4, wherein the defect degree is given as a three-dimensional coordinate of X, Y, Z, and the degree of the defect is a rank assigned according to the size of the defect. .