JP2800726B2 - Woven cloth inspection equipment - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an inspection apparatus for automatically inspecting a woven fabric during weaving or a woven fabric or sheet (hereinafter simply referred to as "woven fabric") for abnormalities. Things.

[0002]

2. Description of the Related Art Conventionally, when inspecting the appearance of a woven fabric, an image of the surface of the woven fabric is taken by a camera, and image density data obtained from the taken image is compared with a threshold value to detect an abnormality in the appearance. There is known an inspection method or an automatic inspection method in which a woven fabric is irradiated with a laser beam, the reflected or transmitted light is received by a light receiving element, and the level of the received light amount is compared with a threshold to detect an abnormality. ing. However, the abnormalities of the woven fabric that can be detected by these inspection methods are usually limited to relatively large defects such as thread dropouts that can be easily visually determined by a person. There has been a problem that detection accuracy is greatly reduced due to disturbance or the like.

In order to improve the detection accuracy, light transmitted from the light source to the woven fabric by irradiating the woven cloth is received through an optical slit arranged in the direction of the yarn to be inspected. Has been proposed (see JP-A-4-148852). This method is based on the premise that the woven density of the woven cloth is constant and the direction of the optical slit is parallel to the yarn to be inspected. Therefore, it is necessary to replace the optical slit each time, and the actual yarn of the woven fabric, especially the warp, is curved and does not satisfy the above-mentioned conditions, so that the detection accuracy is reduced. Had. In addition, a method has been proposed in which two pairs of comb-shaped light receiving sensors are used as light receiving sensors, and an abnormality is detected by comparing a difference value between the outputs of the two and a preset threshold value (Japanese Patent Laid-Open No. 3-249243). reference). In this method, since the density information obtained by dividing the narrow processing region of the woven cloth into two is reflected on the two pairs of comb-shaped light receiving sensors, even if there is vibration or disturbance light, there is an effect that the difference value output between the two cancels out. . However, this method also has a problem that, similarly to the above method, the detection accuracy decreases if the weaving density of the woven fabric changes or if the parallelism between the direction of the comb-shaped light receiving sensor and the yarn to be inspected cannot be maintained. Was. In addition, both of the above two methods have a problem that the same sensor cannot detect the abnormality of the warp and the weft.

[0004]

As described above, in the prior art, a plurality of types of woven fabrics having different weaving densities can be accurately detected over the entire width under the same optical conditions and without distinction between warp and weft. Was difficult to detect.

SUMMARY OF THE INVENTION It is an object of the present invention to provide an automatic woven cloth inspection device capable of detecting a warp abnormality and a weft abnormality simultaneously and with high accuracy under the same optical conditions without being influenced by the weaving density. And

[0006]

To achieve the above object, the present invention provides a light projecting means for irradiating at least a woven cloth in a region to be imaged, and a collecting means for transmitting or reflecting light from the woven cloth. An imaging unit that emits light and captures an image with a CCD element, and converts an analog signal output from the imaging unit into a digital signal,
Based on this image data, image data for each of a plurality of processing areas set in the image area is automatically generated, this image data is processed into a statistical value, and the statistical value between the plurality of processing areas is compared and set in advance. By providing an image processing means for determining the presence or absence of abnormality in the woven fabric by performing comparison with a threshold value, in a woven fabric inspection device that takes an image of the woven fabric and extracts inspection information from image information, In the case of the warp abnormality inspection, the processing area is set to a rectangle in which the long axis is set in the warp direction, and in the case of the weft abnormality inspection, the long axis is set in parallel to the weft direction, and the short axis is the pitch of the warp or the weft or an integer multiple thereof. Set this rectangular processing area within the image area in the vertical direction with the warp in the case of the warp abnormality inspection, and in the vertical direction with the weft in the case of the weft abnormality inspection.
It is characterized in that a plurality of the same size are provided adjacent to each other.

In this case, the image processing means processes the image data for each processing area into a statistical value, compares the statistical value between the processing areas, compares the statistical value with a preset threshold value, and detects abnormalities in the woven cloth. In the case of the warp abnormality inspection, in the vertical direction to the warp, in the case of the weft abnormality inspection,
The processing area can be shifted sequentially in the direction perpendicular to the weft, and the same processing can be performed on the entire image area.

[0008]

The woven cloth inspection device of the present invention irradiates light to the woven cloth in the imaging area by the light emitting means, and condenses and transmits light transmitted or reflected from the woven cloth by the imaging means. The analog signal output from the imaging unit is captured and converted into a digital signal by the image processing unit, and image data is automatically generated for each of a plurality of processing regions set in the image area based on the image data. By processing the image data into statistical values, comparing the statistical values among the plurality of processing regions and comparing the statistical values with a preset threshold value to determine the presence or absence of abnormality in the woven fabric, one optical system Thus, abnormalities of a plurality of types of woven fabrics having different woven densities can be detected with high accuracy over the entire width without distinction between warp and weft.

In addition, the direction of the warp or the weft is recognized in advance, and the processing area is set so that the major axis is in the warp direction in the case of the warp abnormality inspection and the major axis is in parallel with the weft direction in the case of the weft abnormality inspection. The short axis is set to a rectangle with the pitch of the warp or weft or an integer multiple thereof, and this rectangular processing area is set in the image area in the vertical direction with the warp in the case of the warp abnormality inspection, and the weft in the case of the weft abnormality inspection. In the direction perpendicular to the woven fabric, a plurality of the woven fabrics are provided adjacent to each other with the same size and follow the direction targeted for the rectangular area. Can be detected with higher accuracy.

[0010] The image processing means may be configured to process the image data for each processing area into a statistical value, compare the statistical value between the processing areas, compare it with a preset threshold value, and determine whether there is an abnormality in the woven fabric. In the case of a warp abnormality inspection,
In the case of the weft abnormality inspection in the vertical direction with the warp, the processing area is sequentially shifted in the vertical direction with the weft, and the same processing is performed on the entire image area, thereby quickly detecting the abnormality of the woven fabric. It becomes possible.

[0011]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of a woven cloth inspection device according to the present invention will be described below with reference to the drawings.

FIG. 1 is a schematic block diagram of an embodiment of a woven cloth inspection device according to the present invention, and FIG. Light emitted from the light source 1 passes through a gap in the woven fabric 2, is condensed by a lens 3 of the camera, and is imaged on a CCD element in the camera 4.

The light source 1 may be of either a transmission type or a reflection type. However, the light source 1 is used to image the gap of the woven cloth 2 so that the vertical image of the yarn intersection can be clearly captured and the feature of the defect can be observed remarkably. An easy transmission scheme is preferred. Further, in the present embodiment, since an area type CCD camera that moves along the uniaxial movement stage 40 is used as the camera 4, it is preferable that the light source 1 uses scattered light with uniform surface illuminance. On the other hand, when using a line-type CCD camera, the light source is a semiconductor laser, a light source that spreads a He-Ne laser into a slit shape using a lens, and irradiates a halogen light from the side of the rod lens, A light source configured to irradiate in a slit shape with a special slit-shaped scattering paint provided on a rod lens, or a slit-shaped optical fiber illumination can be used. Among them, particularly, the orientation characteristics in the width direction are uniform, A light source using a rod lens that can obtain high luminance is preferable. When a line-type CCD camera is used when the woven fabric is moving at a constant speed, FIG.
As shown in (1), a one-dimensional / two-dimensional converter 30 may be added between the A / D converter 5 and the frame memory 6. Woven cloth 2
There is no particular designation of the amount of light passing through the CCD, but there is no problem as long as sufficient charge can be accumulated within the update cycle of the CCD.

The magnification of the lens 3 of the camera is determined based on the level at which the weaving density of the woven fabric 2 is the finest. In general,
The higher the magnification, the easier the defect extraction tends to be. However, since the short axis size of the rectangular processing area for calculating the statistic value described later needs to be the yarn pitch in the inspection target direction or an integer multiple thereof, at least four yarns in the inspection target direction are included in the captured image. It is assumed that there are more than books.
Also, in consideration of the accuracy of the automatic calculation of the number of yarns in the inspection target direction in the captured image, which will be described later, a lens having an enlargement magnification capable of imaging in a range of 10 to 50 yarns in the inspection target direction in the camera field of view is used. Is preferred.

A / D conversion circuit 5 converts the grayscale image data consisting of analog signals captured by CCD camera 4 into 8-bit data.
After processing into image data consisting of t digital signals, the image data is stored in the frame memory 6. The stored freeze image data is subjected to preprocessing such as differential emphasis by a preprocessing circuit 7 for effectively extracting defects. Next, in order to automatically calculate the yarn pitch in the inspection target direction, the density projection circuit 9 performs density projection (density addition processing) of the target thread direction coordinate,
Process into one-dimensional density data. In addition, F
Fourier transform is performed by the FT circuit 8 to extract a periodic component. The Fourier transform does not need to be performed at all times, so that the processing by the CPU 15 is also possible. Further, these methods have an advantage that even when missing information such as thread missing is included in image data, it can be obtained with high accuracy.

Next, the image data is converted into two
A binarization process is performed, and the integration information integration circuit 11 performs a data integration process based on the binarized image data. Based on this data, the main shaft angle calculation circuit 12 calculates the main shaft angle. In order to accurately obtain the principal axis angle, it is desirable that the processing in the pre-processing circuit 7 performed in advance is differential enhancement processing in the direction perpendicular to the yarn direction in the inspection target direction. As a method for obtaining the principal axis angle, there is a known Hough transform, but the method is not particularly specified.

A rectangular processing area for statistical value calculation is automatically generated from the determined yarn pitch and yarn direction in the inspection target direction. An example is shown in FIG. Although the size of the rectangular processing region in the long axis direction is not specified, the accuracy of defect detection tends to be improved as the length is set longer for continuously occurring defects such as thread dropout. However, it is preferable that the defect be short for a locally generated defect such as fluff. Therefore, the size in the long axis direction may be determined according to the feature of the inspection object, and the same process may be performed a plurality of times while varying the length during measurement. The setting method of the processing area is shown in FIG.
As shown in FIGS. 3A and 3B, the present invention is not limited to a pair of adjacent rectangular regions, and regions to be compared may be alternately provided as shown in FIG. However, it is assumed that the size (the number of pixels) in the short axis direction of the processing region is the yarn pitch in the inspection target direction or an integral multiple thereof. By setting the processing area in this way, for example, when comparing the density addition values of the processing area, when there is no defect, the difference between the absolute values of the comparison values is the smallest, and when there is a defect, the difference of the comparison value is small. The difference between the absolute values appears largest. However, if the phase of the long axis direction of the rectangle is out of phase with the yarn direction of the inspection target, the accuracy of defect detection is reduced. In order to avoid this problem, as described above, the yarn direction of the inspection target is automatically calculated, and the long axis of the rectangular processing area is made to follow the yarn direction of the inspection target. Thereby, for example, it is possible to avoid a decrease in the detection accuracy due to an inclination of the warp that occurs on both sides of the woven fabric during weaving and an error in centering when the camera is fixed. In addition, by calculating the average density of the yarn to be inspected and automatically optimizing the rectangular processing area for calculating the statistic, even when inspecting woven fabrics having different yarn densities, any adjustment of the optical conditions is performed. Can be inspected without the need. Further, by performing the comparison processing of the statistical values between the adjacent processing regions, for example, even when the light amount of the light source relatively decreases or increases during the inspection, the influence thereof can be canceled. If stray light causing halation exists nearby, the shielding plate 20
Should be installed.

The statistical values of the processing area include the standard deviation value of the density, the average value, the middle position, the mode value, the maximum value, the minimum value, the variance value, the interquartile range, the added value, the skewness of the distribution, and the kurtosis. , A variation count, and the like, and the defect is extracted by comparing the statistical value with a difference value, a correlation coefficient, and a threshold value. The calculation of these statistical values and the extraction of defects are performed by the CPU 15. The calculation result is output through the input / output circuit 18.

When the woven fabric being woven is inspected in-line, foreign matter such as fly cotton may adhere to the surface of the woven fabric. As pointed out in the prior art, if a defect is simply extracted by comparing the density value of an image with a threshold value or by comparing the density addition values in two pairs of neighboring areas, these foreign substances are regarded as defects. It will be judged incorrectly. In order to avoid this problem, comprehensive comparison of statistical values and comparison with threshold values are performed. For example, in the case of the transmission type inspection, if there is a foreign substance, a yarn defect, for example, a warp defect such as a wrong heald or a wrong lead, and the foreign substance are compared between the above-described rectangular processing areas. The distribution shape is obviously different. Therefore, by adding such a statistical comparison operation to the determination in addition to the conventional calculation method, it is possible to separate a defect from a disturbance element such as a foreign matter. In addition, the statistical value used as a parameter at the time of the determination shown here is not particularly limited, and a statistical value indicating a unique feature in the target defect may be obtained in advance by an experiment or the like, and may be processed by combining them. . Further, since the present method can simultaneously extract abundant statistical values, it is also possible to identify defects by, for example, fuzzy inference or multiple regression analysis.

FIG. 4 is a flowchart for explaining the operation of one embodiment of the present invention. In order to inspect the entire captured image, at the stage when a series of processing is completed, the same processing is repeated by shifting the processing area by the number of pixels within a range that does not hinder defect extraction in the yarn direction to be inspected and the vertical axis. .
In the case of simultaneously inspecting for warp and weft abnormalities, after completing the above series of processing, the same processing is performed by adjusting the rectangular processing area to the next target yarn direction. In this case, the statistical value and the threshold value to be compared are not always the same as the former case, so that each time the statistical value and the threshold value to be compared are set and the same processing is performed. The program for controlling the whole is stored in the ROM 16
In addition, the statistic and the threshold are stored in the RAM 17. When inspecting the entire woven fabric width, as shown in this embodiment, the camera 4 may be traversed in the woven fabric width direction or a plurality of cameras may be fixed at uniform intervals in the woven fabric width direction.
In this embodiment, the in-line inspection of the woven fabric during weaving was shown. However, the present invention is not limited to the woven fabric during weaving, but also a woven fabric or a sheet having regular characteristics other than the woven fabric. Can be applied to automatic inspection.

[0021]

According to the first aspect of the present invention, it is possible to simultaneously detect the abnormality of a plurality of types of woven fabrics having different weaving densities without changing optical conditions, for the warp and the weft. With a wealth of extracted information, it is possible to separate defects from surface disturbances and other disturbance elements and defects, and to identify defects, as well as to inspect the side of the woven fabric where the yarn direction is not necessarily the same as the center of the woven fabric. In addition, abnormalities of the woven fabric can be detected with high accuracy.

According to the second aspect of the present invention, the abnormality of the woven fabric can be quickly detected.

[Brief description of the drawings]

FIG. 1 is a schematic block diagram of one embodiment of the present invention.

FIG. 2 is a perspective view showing an appearance of one embodiment of the present invention.

FIG. 3 is a diagram for explaining a rectangular processing area for calculating a statistical value according to one embodiment of the present invention;

FIG. 4 is a flowchart for explaining the operation of one embodiment of the present invention.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Light source 2 Woven cloth 3 Lens 4 CCD camera 5 A / D conversion circuit 6 Frame memory 7 Image preprocessing circuit 8 FFT circuit 9 Image density projection circuit 10 Image binarization circuit 11 Image combination information integration circuit 12 Main axis angle calculation circuit Reference Signs List 13 image bus 14 CPU bus 15 CPU 16 ROM 17 RAM 18 input / output circuit 20 shielding plate 30 one-dimensional / two-dimensional converter 40 one-axis moving stage

Continuation of the front page (58) Field surveyed (Int.Cl. ⁶ , DB name) G01N 21/84-21/90 D06H 3/08 D06H 3/12

Claims (2)

(57) [Claims] 1. A light projecting means for irradiating light to at least a woven cloth in a region to be imaged, an imaging means for condensing light transmitted or reflected from the woven cloth, and imaging with a CCD element; Convert the output analog signal to a digital signal,
Based on this image data, image data for each of a plurality of processing areas set in the image area is automatically generated, this image data is processed into a statistical value, and the statistical value between the plurality of processing areas is compared and set in advance. By providing an image processing means for determining the presence or absence of abnormality in the woven fabric by performing comparison with a threshold value, in a woven fabric inspection device that takes an image of the woven fabric and extracts inspection information from image information, In the case of the warp abnormality inspection, the processing area is set to a rectangle in which the long axis is set in the warp direction, and in the case of the weft abnormality inspection, the long axis is set in parallel to the weft direction, and the short axis is the pitch of the warp or the weft or an integer multiple thereof. Set this rectangular processing area within the image area in the vertical direction with the warp in the case of the warp abnormality inspection, and in the vertical direction with the weft in the case of the weft abnormality inspection.
A woven cloth inspection device, wherein a plurality of woven cloth inspection devices are provided adjacent to each other with the same size. 2. The image processing means according to claim 1, wherein the processing of the image data for each processing area into a statistical value, a comparison of the statistical value between the processing areas, a comparison with a preset threshold value, and an abnormality of the woven fabric. The presence / absence determination is one cycle, and in the case of a warp abnormality inspection,
2. The woven fabric according to claim 1, wherein the processing area is sequentially shifted in a direction perpendicular to the warp and in a direction perpendicular to the weft in the case of the weft abnormality inspection, and the same processing is performed on the entire image area. Inspection equipment.