JPWO2014054528A1 - Yarn inspection method, yarn inspection device, yarn manufacturing method, yarn package and yarn module - Google Patents

Abstract

In the yarn-making process for manufacturing yarns that run continuously in the longitudinal direction, the yarns that run are imaged, and from the obtained image data, the entire length of the running yarn is inspected at high speed, and the yarns are simply swayed. Provided is a method for inspecting a yarn so as to obtain information on a yarn defect without erroneously recognizing a case where the yarn is raised or a case where the yarn is simply skewed as a yarn defect. In this yarn inspection method, a traveling yarn is imaged by an imaging unit, and image data obtained by the imaging unit is imaged by a data processing unit, and (a) a predetermined traveling direction image is obtained from the image data of the traveling yarn. Data comprising a procedure for calculating a plurality of yarn widths in a section, (b) a procedure for calculating yarn width variations from the plurality of yarn widths, and (c) a procedure for comparing the yarn width variations with a first threshold. It is characterized by performing processing.

Description

  The present invention relates to the presence or absence of defects occurring in the yarn or the state of the defect (for example, knots, constriction, etc.) with respect to the yarn continuously running in the longitudinal direction in the yarn-making process for producing the yarn. The present invention relates to a method for inspecting a yarn grasped by processing data obtained by use.

  Fibers, fibers, and yarns represented by hollow fiber membranes have been used and utilized in various fields and applications since the past.

  In the past, the production of these yarns has been required to be mass-produced at high speed and cost reduction. On the other hand, the demand for quality was not strong. However, in recent years, with the development of science and technology, combined with the enhancement of the functionality of final products that use yarn as a component and the expansion of fields that use these yarns, High quality has come to be demanded. That is, at present, in addition to the problems from the past such as mass / high-speed production and low-cost production, the quality of the yarn itself is also a problem.

  Here, the yarns that are attracting attention for use in high-functional products are used in carbon fibers used in automobile and airplane structural members, optical fibers that support the information and communication society, and high-performance clothing. Examples include irregular cross-section fibers. Similarly, examples of yarns that require high quality control include hollow fiber membranes used for pre-treatment applications in sewage treatment, clean water treatment, and seawater desalination. These are all defects that occur in the yarn (shape defects (crushed, flattened, knotted, constricted, swollen, irregularities, etc.), poor thickness (thin threads, thick threads, etc.), partial defects or tears, foreign matter contamination, fluffing, Scratches, crusts, etc.) directly affect the quality of the final product. Therefore, the quality of such yarns must be strictly controlled.

  More specifically, for example, a hollow fiber membrane is generally manufactured using a polymer as a raw material, but the membrane may become thinner or vice versa in the course of production. In addition, foreign matter may adhere to the film surface. If these drawbacks occur, the filtration performance of the hollow fiber membrane may be adversely affected. Therefore, it is necessary to inspect the surface of the hollow fiber membrane so that the hollow fiber membrane in which the defect has occurred does not flow out to the market.

  However, in general, hollow fiber membranes are produced in such a manner that the raw material is formed into a hollow shape with a die and then subjected to various treatments and finally wound up by a winder. Yes.

  It is also common to produce a plurality of hollow fiber membranes in parallel at the same time in order to realize mass / high-speed production and low-cost production.

  In such a manufacturing method, a high-performance yarn represented by a plurality of hollow fiber membranes running in parallel is simultaneously inspected, and a defect is detected for each yarn to detect each yarn. Understanding the defect information is important in the quality control of the yarn itself, the yarn package around which the produced yarn is wound, and the yarn module incorporating the yarn.

  At this time, in order to completely guarantee the quality of the yarn, it is important to inspect the entire length of the yarn without delay in the traveling speed of the yarn.

  Conventionally, as a method of constantly monitoring the condition of the yarn and detecting a defect occurring in the yarn, “the running of the yarn generated by the illumination means by providing illumination means and imaging means on the running surface of the yarn. The reflected light from the surface is imaged by the imaging means; 1. From the obtained image data, a defect included in the running yarn is extracted as extraction unit data; 2. Extract contour data of the extraction unit from the obtained extraction unit data; 3. Remove the line segment parallel to the running direction of the yarn from the obtained contour data to obtain the remaining data. By comparing the obtained remaining portion data with a preset threshold value, it is determined whether or not there is a defect ”, and a traveling yarn inspection method has been proposed (see Patent Document 1). Further, “imaging means arranged so that the direction perpendicular to the running direction of the yarn and the imaging axis coincide with each other, illumination means for irradiating light on the surface of the yarn, and image data obtained by the imaging means A yarn inspection method has been proposed that performs predetermined image processing and compares the circumscribed rectangular image of the image data with the image data to determine the presence or absence of defects (Patent Document 2).

However, in these methods, these are normal when the normal yarn is simply swaying due to external factors such as vibration of the equipment, or when the normal yarn is simply skewed. Despite being a yarn, it may be misrecognized as a “node” defect in which the yarn width is locally increased or a “necked” defect in which the yarn width is locally reduced. For example, when the inspection method described in Patent Document 2 is applied to some image data shown in FIG. 5, the width of the circumscribed rectangle of the yarn YT ₆ is increased although the yarn is simply skewed. It may be judged as a defect. Further, although the yarn YT ₇ is merely causing the yarn to sway, the circumscribed rectangular width becomes large and may be judged as a defect.

  Also, by calculating the yarn width for each pixel in the running direction from the image data for all the yarns, whether the normal yarn is distorted or skewed, or is a “node” defect? It is possible to determine whether it is a “neck” defect, but it takes a long time to process the data, and there is a risk of delay in reflecting the inspection result, which increases the cost for improving the data processing performance. It becomes a problem.

Japanese Unexamined Patent Application Publication No. 2012-092477 International Publication No. 2012/039298

  The object of the present invention is to produce a yarn that travels continuously in the longitudinal direction by imaging the traveling yarn, and from the obtained image data, the entire length of the traveling yarn is inspected at high speed. Threads and yarn packages can be obtained by obtaining information on yarn defects without misrecognizing that the yarn is simply swaying or being skewed as a yarn defect. It is to provide a yarn inspection method for quality control of a yarn module.

  In order to achieve the above object, the present invention adopts the following method.

That is, the present invention is a yarn inspection method in which a traveling yarn is imaged by an imaging unit, and image data obtained by the imaging unit is processed by a data processing unit, and the data processing includes:
(A) a procedure for calculating a plurality of yarn widths in a predetermined section in the running direction from the image data of the running yarn; (b) a procedure for calculating a variation in yarn width from the plurality of yarn widths; and (c). And a step of comparing the variation in the yarn width with a first threshold value.

  The variation in the yarn width can be calculated from a plurality of yarn widths measured at measurement points designated by a predetermined number of divisions in the predetermined section.

Further, in the yarn inspection method of the present invention, the data processing is performed in addition to (a), (b), and (c), and (d) circumscribing the traveling yarn in a predetermined section in the traveling direction. A procedure for calculating a rectangular width and / or an inscribed rectangle width; (e) a procedure for calculating a representative value of the yarn width from the plurality of yarn widths; and (f) a representative value of the yarn width and the circumscribed rectangle width and / or Alternatively, a procedure for comparing the width of the inscribed rectangle may be included.

In the yarn inspection method of the present invention, the data processing may include (g) the yarn in addition to (a), (b), (c), (d), (e), and (f). A procedure for comparing the difference between the representative value of the width and the circumscribed rectangle width with the second threshold and / or (h) comparing the difference between the representative value of the yarn width and the inscribed rectangle width with the third threshold. It should include procedures.

  In the yarn inspection method of the present invention, the representative value of the yarn width may be an average value, a median value, a maximum value or a minimum value, or a yarn width in ascending order of the image data of the traveling yarn. The thread widths of the ranks specified in advance can be sorted.

In the yarn inspection method according to the present invention, in addition to (a), (b), and (c), the data processing includes (d) a circumscribed rectangular width of the yarn in a predetermined section in the traveling direction, and It is preferable to include a procedure for calculating the inscribed rectangle width and / or (i) a procedure for comparing the thread width designed in advance with the circumscribed rectangle width and / or the inscribed rectangle width.

In the yarn inspection method of the present invention, the data processing is performed in addition to (a), (b), (c), (d), and (i), and (j) the previously designed yarn. A procedure for comparing the difference between the width and the circumscribed rectangle width with a fourth threshold and / or (k) a procedure for comparing the difference between the predesigned yarn width and the inscribed rectangle width with a fifth threshold. It is good to include.

In the yarn inspection method of the present invention, the data processing may be performed in addition to (a), (b), and (c),
(E) a procedure for calculating a representative value of the yarn width from the plurality of yarn widths; and (l) a procedure for comparing a difference between the designed yarn width and the representative value of the yarn width with a sixth threshold value. It is good to include.

  The yarn inspection apparatus according to the present invention includes an imaging unit that images a traveling yarn, and a data processing unit that performs data processing on image data obtained by the imaging unit. The running yarn can be inspected using either one.

  In addition, the yarn manufacturing method of the present invention includes an inspection step of inspecting the traveling yarn using any one of the yarn inspection methods. Furthermore, it is preferable to include an operation procedure for identifying an abnormality occurring in the manufacturing process based on the inspection result obtained in the inspection process and changing the conditions of the manufacturing process.

  According to the present invention, in the yarn-making process for producing a yarn product that continuously runs in the longitudinal direction, the running yarn is imaged, and the total length of the running yarn is inspected from the obtained image data. It is possible to prevent the yarn that should be recognized as normal from being mistakenly recognized as a defect due to running yarn skew or skew. In addition, by obtaining information on defects for each yarn, process abnormalities such as process condition fluctuations can be detected at an early stage, yield can be improved, and quality control of yarns, yarn packages, and yarn modules can be performed. Can do.

  In addition, according to the yarn inspection method of the present invention, in particular, the yarn width is not calculated from all the lines in the running direction from the image data, but is calculated by sampling only a plurality in a predetermined section. Therefore, the yarn can be inspected in a short time. Therefore, even when the yarn runs at a high speed, for example, at a speed exceeding 50 m / min, the device used for the data processing means for processing the captured image data is an inexpensive data processing device such as a general-purpose personal computer. However, it is possible to inspect the entire length of a plurality of yarns at the same time without delaying the traveling speed and to grasp the presence or absence of defects or the state of defects on each yarn online.

  Furthermore, by using the yarn inspection method of the present invention, it is possible to appropriately and quickly implement quality control of each of the yarns produced by the yarn making process of yarns that produce a plurality of yarns simultaneously. It becomes possible.

FIG. 1 is a schematic side view showing an example of an inspection apparatus used for carrying out the yarn inspection method of the present invention. FIG. 2 is a schematic bird's-eye view showing an example of an inspection apparatus used for carrying out the yarn inspection method of the present invention. FIG. 3 is a schematic diagram of data processing means for processing image data after obtaining the image data, which is used in the implementation of the yarn inspection method of the present invention. FIG. 4 is a schematic diagram illustrating image data of a plurality of running yarns obtained by imaging (all normal yarns). FIG. 5 is a schematic view illustrating another image data of a plurality of running yarns obtained by imaging (including yarns that are considered abnormal). FIG. 6 is a diagram showing a procedure for calculating a plurality of yarn widths of each yarn for the image data of FIG. FIG. 7 is a diagram showing a procedure for calculating the circumscribed rectangular width of each yarn for the image data of FIG. FIG. 8 is a diagram showing a procedure for calculating the inscribed rectangular width of each yarn for the image data in FIG.

  In the yarn inspection method of the present invention, the yarns to be inspected include hollow fiber membranes, clothing fibers, carbon fibers, optical fibers, steel wires, medical catheters, and the like, which are substantially cylindrical or tubular structures. As long as the product is a yarn product having any of the above, any object can be inspected. Further, the yarn to which the yarn inspection method of the present invention is applied may be a single fiber such as a hollow fiber membrane, or may be a group of a number of single fibers such as carbon fibers.

  Examples of the hollow fiber membrane to which the yarn inspection method of the present invention is applied include, for example, polycarbonate, polyolefin, polyamide, polyimide, cellulose, polysulfone, polyethersulfone, polymethacrylic acid, polyacrylonitrile, polyfluoride. Examples thereof include hollow fiber membranes made of organic polymers such as vinylidene and polyether ketone, and ceramics such as alumina, zirconia, titania and silicon carbide.

  The inspection method of the present invention can be applied to any inspection of hollow fiber membranes employed as ultrafiltration membranes, microfiltration membranes, gas separation membranes, pervaporation membranes, dialysis membranes, and the like. These hollow fiber membrane modules are used for water treatment and artificial kidneys.

  The inspection apparatus used for carrying out the yarn inspection method of the present invention has an image pickup means for picking up a traveling yarn and a data processing means for data processing of image data obtained by the image pickup means.

  The image pickup means refers to a sensor in which image pickup elements (pixels) that receive light, such as CCDs and CMOSs, are linearly or two-dimensionally arranged and light and dark data received by each pixel is configured as an image.

  The imaging means can obtain image data for each predetermined section L to be described later over the entire length of the traveling yarn. That is, by connecting the captured image data, the image data of the full length of the running yarn can be obtained without duplication or omission. For this reason, the timing at which image data is captured can be appropriately adjusted based on the running speed of the yarn and the length of the predetermined section L.

  When multiple yarns run in parallel, the length in the width direction of the required inspection area becomes longer depending on the number of running yarns. Therefore, in order to image this with high resolution, the light receiving element is a straight line. A line sensor camera arranged in a line is more preferable. The number of pixels of the line sensor camera is preferably 2,000 pixels or more. Manufacturers such as Nippon Electro Sensor Device Co., Ltd., Takenaka System Equipment Co., Ltd., Basler, DALSA, etc. can be used for the line sensor camera corresponding to the above.

  When a line sensor camera is used as the imaging means, it is preferable to set the number of acquired lines per frame of the captured image in a predetermined section of the traveling yarn. Further, when an area sensor camera in which light receiving elements are arranged in a plane is used as the image pickup means, the size of one frame of an image is determined by the model used. Therefore, when the size of the captured image is not suitable for the predetermined section of the running yarn, the captured image may be divided or combined with the preceding and subsequent captured images before the data processing of the present invention.

  The illumination means in the present invention is not limited as long as it can illuminate uniformly in a direction parallel to the running surface of the yarn and perpendicular to the running direction of the yarn. Even when a plurality of yarns travel in parallel, it is only necessary to illuminate each yarn uniformly in the width direction. The difference in the amount of illumination light in the width direction is preferably within 20%. Moreover, the intensity | strength and wavelength of illumination light will not be limited if the illumination intensity of an illumination means can ensure sufficient reflected light quantity from the defect of a thread | yarn and a thread | yarn.

  In the present invention, the “running surface of the yarn” is as described below. That is, when one yarn is traveling in contact with two yarn conveyance rolls installed in parallel, the surface including the yarn and parallel to the axis of the yarn conveyance roll is provided. The running surface of the yarn. Also, when two or more yarns run in parallel, the yarn running surface forms a yarn running surface including a plurality of yarns, as in the case of one yarn. Thus, the yarn is produced through the yarn production process.

  In the present invention, the illumination means may be provided at the same position as the imaging means with respect to the running surface of the yarn, or may be provided at a different position. When provided at “position on the same side as the imaging unit”, the imaging unit receives light reflected or scattered by the yarn illuminated by the illumination unit. In this case, the yarn portion is imaged as a bright portion and the background portion as a dark portion. Further, when provided at “a position different from the image pickup means”, the image pickup means receives light transmitted through the gap between the yarns. In this case, the yarn portion is a dark portion and the background portion is a bright portion. Therefore, image processing may be performed in consideration of this point.

  Moreover, as an illumination means, the high frequency lighting type fluorescent lamp with which the irradiation part is line shape, LED line illumination, etc. can be used. In addition, illumination means for guiding and illuminating light from a light source such as a halogen lamp, a metal halide lamp, and an LED with a light guide in which a plurality of optical fibers are arranged in a line, and illumination means for illuminating the end face of a cylindrical rod lens Alternatively, it is possible to use an illumination means provided with a cylindrical lens on the front surface. From the viewpoint of cost and maintainability, a high-frequency lighting fluorescent lamp is preferable. However, when the traveling speed is high, for example, when it is necessary to detect at a speed exceeding 50 m / min, it is preferable to use a high-luminance illumination means such as an LED or a metal halide lamp.

<First Embodiment of the Present Invention>
A first embodiment of the present invention will be described.

  In the yarn inspection method of the present invention, the traveling yarn is imaged by the imaging means, and the obtained image data is processed by the data processing means. In this data processing, (a) a procedure for calculating a plurality of yarn widths (hereinafter also referred to as “yarn width data group”) in a predetermined section in the traveling direction from image data of the traveling yarn (hereinafter referred to as “thread width data group”). A), (b) a procedure for calculating variations in yarn width from the obtained yarn width data group (hereinafter referred to as procedure B), and (c) comparing this variation in yarn width with a first threshold value. Procedure (hereinafter referred to as procedure C).

  The yarn portion and the background portion of the periphery of the yarn are imaged in the image data obtained by the imaging means. First, the yarn portion in a predetermined section in the traveling direction is extracted. For example, the yarn portion can be separated from the background portion around the yarn by adding a binarization process by comparing the luminance value of each pixel included in the image with a certain threshold value. In addition, when image noise is included in the image data, it is preferable to reduce the image noise by performing filter processing such as an averaging filter, a Gaussian filter, and a median filter before performing the above extraction processing. In the procedure A, the yarn width of each yarn in a predetermined section in the running direction is measured a plurality of times from the yarn portion of the image data obtained in this way, and the result is used as a yarn width data group. Yarn width measurement is performed by designating measurement points by dividing a predetermined section by a predetermined number of divisions, and calculating yarn widths at the plurality of measurement points to obtain a yarn width data group for each yarn. It is good to form.

  In the procedure B, the variation in the yarn width is calculated for each yarn from the yarn width data group calculated in the procedure A. As an index representing variation, any of standard deviation, variance, a range from the minimum value to the maximum value (difference between the maximum value and the minimum value), and the like may be used.

  In procedure C, the variation in the yarn width data group calculated in procedure B is compared with a first threshold value set in advance. The first threshold value is appropriately set according to an index that represents variation in the yarn width.

  If the variation of the yarn width data group in a certain yarn is larger than the preset first threshold value, it is determined that the yarn is defective.

  Here, the “thread width” is as described below. That is, it is preferable to set the width in the direction perpendicular to the traveling direction with reference to the traveling direction of the yarn in the obtained image data. Alternatively, the width in an arbitrary direction predetermined with respect to the traveling direction may be used as the yarn width.

  Further, the “predetermined section” corresponds to the length in the running direction of the yarn to be inspected in one data processing, and is appropriately set in consideration of the situation (size, frequency, etc.) in which a defect appears. . In the present invention, since the variation in the yarn width before and after the defect is used as an index, the predetermined section needs to be larger than the influence range of the defect, and specifically, when set to about 1 to 10 times the influence range of the defect. good.

  Hereinafter, the yarn inspection method of the present invention will be described with reference to the drawings.

  FIG. 1 is a schematic side view of an inspection apparatus that acquires and processes image data used in the implementation of the yarn inspection method of the present invention, that is, an image data acquisition processing apparatus ID. FIG. 2 is a schematic bird's-eye view of the image data acquisition processing device ID of FIG.

In FIG. 1 and FIG. 2, the image data acquisition processing device ID has two yarn conveying rolls R1 and R2 that are parallel to each other and spaced from each other. A plurality of yarns YT ₁ -YT _n are juxtaposed at intervals B ₂ -B _n , are in contact with the yarn conveying rolls R 1 and R 2, and travel in the direction indicated by the arrow YCD. Moreover, the running surface YCP (illustrated by dotted lines) of the yarn is formed by the plurality of running yarns YT ₁ -YT _n . Each yarn is located on the running surface YCP of this yarn.

  The illumination means 2 and the imaging means 1 are provided on the first side P1 across the yarn running surface YCP. The imaging unit 1 is provided at a position where the yarn is illuminated by the illumination unit 2 and the scattered reflected light generated on the running surface of the yarn is received.

  The image data picked up by the image pickup means 1 is guided to the data processing means 3, and the data processing means 3 determines the presence or absence and state of the running yarn defect.

  FIG. 3 is a schematic view of a data processing means for processing image data after obtaining the image data used for carrying out the yarn inspection method of the present invention.

  In FIG. 3, the data processing means 3 calculates a yarn width data group in a predetermined section in the traveling direction for each yarn from the image data of each traveling yarn in the procedure A for the obtained image data. Next, in procedure B, a variation in yarn width is calculated for each yarn from the calculated yarn width data group. Next, in procedure C, the quality of the yarn is determined by comparing the calculated variation in the yarn width with a preset first threshold value. If the variation in the yarn width of a certain yarn is larger than the first threshold value, it is determined that the yarn has a quality defect. Also, if there is no defect in the yarn and the yarn is simply swaying or if the yarn is simply skewed, the yarn width variation is small. Can be prevented.

FIG. 4 is a schematic view illustrating image data obtained by the imaging unit 1. In FIG. 4, a plurality of yarns (YT ₁ , YT ₂ ,... YT _n ) running in the direction of arrow YCD and background portions B ₁ , B ₂ ,. _Bn and _{Bn + 1} are binarized. The yarns (YT ₁ , YT ₂ ,... YT _n ) in FIG. 4 indicate cases where each is a normal yarn. In the manufacturing process, it is necessary to inspect each of the normal yarns at a high speed.

FIG. 5 shows image data in which a plurality of yarns (YT ₁ , YT ₂ ,... YT _n ) that run in the direction of the arrow YCD include yarns that appear to have various abnormalities. It is a schematic diagram which illustrates this.

  In FIG. 5, the running direction of the yarn is indicated by an arrow YCD, and a plurality of yarns are arranged in a predetermined section L (for example, 60 mm / one image frame) for each yarn (for example, designed yarn width 1.5 mm). The yarn width is calculated (procedure A). Here, as shown in FIG. 6, the section L is divided into equal intervals by a predetermined number of divisions (5 in the case of FIG. 6), and the yarn width of each yarn is calculated five times at the measurement points indicated by dotted lines. (Both ends of the section L are calculated by either the start point or the end point in consideration of overlap with the preceding and succeeding images). From this calculated yarn width, for each yarn, a variation in the calculated value of the yarn width five times (here, standard deviation) is further calculated (procedure B). This variation in yarn width is compared with a preset first threshold value (for example, 15 μm) (procedure C). If the calculated variation in the yarn width is greater than the first threshold value, it is determined that there is some abnormality in the quality.

In addition, when the yarn is simply swaying as in the yarn YT ₇ shown in FIG. 6 or when the yarn is simply skewed as in the yarn YT ₆ , there is a variation in the yarn width. It becomes smaller than the first threshold and it is not determined that there is a quality defect. On the other hand, when the yarn has a “node” like the yarn YT ₄ shown in FIG. 6 or the yarn has a “neck” like the yarn YT ₅ , the yarn width Is larger than the first threshold value, and it is determined that there is a quality defect.

  Here, the number of times of calculation of the yarn width of the yarn in the section L 60 mm (that is, the length of the yarn to be inspected once per data processing) is set to five. However, the assumed defect size and the yarn traveling speed are assumed. It is possible to set appropriately in view of the data processing speed and the performance of the data processing apparatus.

<Second Embodiment of the Present Invention>
The second embodiment of the inspection method of the present invention can inspect the condition of the yarn defect in addition to the inspection of the presence or absence of the yarn defect based on the above-described first embodiment of the present invention. In the second embodiment, in addition to the above-described data processing, the data processing calculates a circumscribed rectangular width and / or an inscribed rectangular width of the traveling yarn in a predetermined section in the traveling direction of the traveling yarn (hereinafter referred to as “infrared rectangular width”). Procedure D) and / or a procedure for calculating a representative value of the yarn width from the yarn width data group (hereinafter referred to as Procedure E), a representative value of the yarn width and the circumscribed rectangular width and / or the inscribed rectangular width. And a procedure for comparison (hereinafter referred to as procedure F).

In step D, two virtual parallel lines circumscribing the yarns (YT ₁ , YT ₂ ,... YT _n ) of the image data are drawn on the basis of the yarn running direction YCD. The interval is calculated as the circumscribed rectangle width. Similarly, two virtual parallel lines inscribed in the yarn (YT ₁ , YT ₂ ,... YT _n ) of the image data are drawn, and the interval between the virtual parallel lines is calculated as the inscribed rectangle width. Moreover, it is good also as the width | variety of the arbitrary directions decided previously similarly to the above-mentioned "thread width."

  In procedure E, a representative value of the yarn width is calculated from a yarn width data group for each yarn obtained from the image data.

  In the procedure F, the representative value of the yarn width and the circumscribed rectangular width are compared and / or the representative value of the yarn width and the inscribed rectangular width are compared.

  Then, comparing the difference between the circumscribed rectangular width of the traveling yarn and the representative value of the yarn width with a preset second threshold (procedure G), and / or the inscribed rectangular width of the traveling yarn, The difference from the representative value of the yarn width can be compared with a preset third threshold value (procedure H).

  Here, the representative value of the yarn width is an average value of the yarn width data group, a median value, a minimum value or a maximum value, or a yarn width in a predetermined order by sorting the yarn width data group in ascending order. Can be set to

  If the difference between the circumscribed rectangle width and the representative value of the yarn width is larger than the second threshold value, it is determined that the yarn has a defect of “node”, for example. Further, if the difference between the inscribed rectangle width and the representative value of the yarn width is larger than the third threshold value, for example, it is determined that the yarn has a “neck” defect.

  For the image data of the yarn shown in FIG. 5, a plurality of yarn widths of each yarn are calculated in the section L in the same manner as in the first embodiment, and the calculated plurality of yarn width values. From this, the representative value of the yarn width is calculated. For example, when the average value is a representative value, for example, as shown in FIG. 6, the average value of the yarn width is calculated from the yarn width value calculated five times during the section L for each yarn. (Procedure E).

For the image data shown in FIG. 5, the circumscribed rectangular width of each yarn is as shown in FIG. 7 for each yarn (YT ₁ , YT ₂ ,... YT _n) of the image data in the section L. ) The interval between two virtual parallel lines (shown by white dotted lines) circumscribing the portion and parallel to the yarn running direction YCD is defined as the circumscribed rectangular width (procedure D).

Similarly, for the image data shown in FIG. 5, the inscribed rectangle width of each yarn is as shown in FIG. 8 for each yarn (YT ₁ , YT ₂ ,... The interval between virtual parallel lines (shown by dotted lines) inscribed in the YT _n ) portion and parallel to the yarn running direction YCD is defined as the inscribed rectangular width (procedure D).

The representative value (here, the average value) of the yarn widths calculated in this way is compared with the circumscribed rectangular width and / or inscribed rectangular width (procedure F). For example, as the yarn YT ₄ in FIG. 7, if the difference between the representative value (average value here) of the circumscribing rectangular width and the yarn width is greater than the second threshold value (e.g. 150 [mu] m), the said yarn for example yarns It can be determined that there is a “node” defect whose width is locally increased. If the difference between the representative value of the yarn width (here, the average value) and the inscribed rectangle width is larger than the third threshold value (for example, 150 μm), as in the case of the yarn YT _{5 in} FIG. For example, it can be determined that the strip has a “neck” defect in which the yarn width is locally reduced.

<Third Embodiment of the Present Invention>
In the third embodiment of the present invention, in addition to the first embodiment of the present invention described above, the data processing is performed so that the circumscribed rectangular width of the traveling yarn in a predetermined section in the traveling direction of the traveling yarn and / or A procedure (procedure D) for calculating the inscribed rectangle width and a procedure (procedure I) for comparing the yarn width designed in advance with the circumscribed rectangle width and / or the inscribed rectangle width are included.

  As described above, in step D, two virtual parallel lines circumscribing the yarn portion of the image data are drawn on the basis of the yarn running direction YCD in the obtained image data, and the width of the virtual line is circumscribed. Calculated as rectangular width. Similarly, two virtual parallel lines inscribed in the yarn portion of the image data are drawn, and the width of the virtual line is calculated as the inscribed rectangular width.

  In procedure I, a comparison is made between the yarn width designed in advance and the circumscribed rectangular width and / or inscribed rectangular width.

  Then, the difference between the predesigned yarn width and the circumscribed rectangle width is compared with a fourth threshold (hereinafter referred to as procedure J), and / or the difference between the predesigned yarn width and the inscribed rectangle width Is compared with the fifth threshold value (hereinafter referred to as procedure K).

  If the difference between the predesigned yarn width and the circumscribed rectangle width is larger than a fourth threshold value (for example, 150 μm), it is determined that the yarn has a defect of “node”, for example. Further, if the difference between the predesigned yarn width and the inscribed rectangle width is larger than a fifth threshold (for example, 150 μm), it is determined that the yarn has a “neck” defect, for example.

  In any one of the above embodiments, a procedure (hereinafter referred to as procedure L) for comparing the difference between the pre-designed yarn width and the representative value (here, the average value) of the yarn width with the sixth threshold is added. This makes it possible to check whether the yarn is manufactured with the designed yarn width. If the difference between the yarn width designed in advance and the representative value of the yarn width is smaller than a sixth threshold (for example, 50 μm), it can be determined that the yarn is manufactured with the designed yarn width.

  Further, in the yarn manufacturing method including the inspection apparatus incorporating the yarn inspection method of the present invention in the inspection process, the abnormality in the manufacturing process is identified from the number and location of defects detected in the inspection process. An operation procedure for changing the condition may be included.

  In the yarn manufacturing process, if the surface of the roll for running the yarn or the guide roll that keeps the running position of the yarn tidy is damaged, and the yarn is in contact with the damaged part, the number of defects in the yarn increases. Tend to. Therefore, when the number of defects detected using the yarn inspection method of the present invention is counted as a change over time for each running yarn per unit time, for example, per hour, A characteristic increasing trend also appears with time. For example, when the number of defects per unit time exceeds a predetermined threshold, a warning is given to notify the manufacturing process when the number of defects exceeds a predetermined threshold. However, it is possible to inspect the manufacturing process of the yarn and repair the abnormal part. By doing in this way, it becomes possible to remove the cause of the defect at an early stage, and it is possible to manufacture more yarns with no or fewer defects than before the operation for the operation time of the yarn manufacturing process. It becomes. Therefore, in the yarn manufacturing method including the yarn inspection method of the present invention in the inspection process, an operation procedure for specifying an abnormality occurring in the manufacturing process based on the number of defects and changing the conditions of the manufacturing process is included. It is desirable.

  The yarn package or yarn module obtained by using the yarn manufactured by such a method can be obtained by the number of defects contained in the yarn in the package or the yarn module by the yarn inspection method of the present invention. The position information of the defect with respect to the total length can be grasped in advance. For this reason, for example, when the yarn package is unwound and used in a later process, only a yarn having no defect and having a good quality can be used. Thus, troubles in the subsequent process that have conventionally occurred due to defects can be prevented in advance, and the yield can be improved compared to before using the yarn inspection method of the present invention.

  In addition, the “yarn package” in the present invention refers to a state in which yarns that have been produced are grouped together. For example, one or a plurality of yarns are wound around a bobbin or a cassette, or the yarns are folded or bundled by cutting to a certain length, but the form is not limited.

  The “yarn module” is a product incorporating the above-described yarn package. For example, when the yarn is a hollow fiber membrane, a dialyzer used for artificial dialysis and a cartridge used for water purification can be used. Alternatively, when the yarn is an optical fiber, examples thereof include an optical cable used for information communication and an endoscope used for various uses including medical use, but the form is not limited.

  Hereinafter, based on an Example, this invention is demonstrated concretely.

Based on the image data acquisition processing device ID of FIG. 1 or FIG. 2, the configuration of the traveling yarn inspection device used in the examples is shown below.
Illumination means: LED bar type illumination (output 100W, length 200mm, LS II200 manufactured by Nissei Electric)
Imaging means: line sensor camera (4096 pixels, Spler 4096-20 km manufactured by Basler)
Yarn running speed: 10m / min

With the above configuration, five hollow fiber membranes (designed yarn width 1.5 mm) that are run in parallel on the same plane at a speed of 10 m / min are imaged, and the data processing content of the obtained image data is changed. The running yarn was inspected. The data processing means used here has the following configuration and specifications.
Arithmetic unit used for data processing means: 1 personal computer CPU: Intel (registered trademark) Core i7-950
Memory: 6GB
OS: Windows (registered trademark) 7 Professional
Image processing library software: HALCON (Ver. 9.0, manufactured by MVTec)
Size of image data used for the test: 4096 × 3000 pixels.

[Example 1]
The yarn was allowed to run for 30 minutes, during which time image data was acquired for each section L (60 mm). Next, the number of calculation of the yarn width of each yarn in the section L (60 mm) was set to 20 times, and the standard deviation of the 20 times yarn width was calculated. The standard deviation value was compared with the first threshold value (15 μm), and if the standard deviation was smaller than the threshold value, there was no quality abnormality.

[Example 2]
For the same image data group as in Example 1, in addition to the data processing in Example 1, an average value of the yarn width was calculated from the calculated values of 20 yarn widths, and this was used as the representative value of the yarn width. Further, the circumscribed rectangle width and the inscribed rectangle width of each yarn were calculated from the image data. When the difference between the circumscribed rectangle width and the representative value (average value) of the yarn width is larger than the second threshold value (150 μm), the “node” defect, the difference between the inscribed rectangle width and the average value of the yarn width is the third value When it was larger than the threshold (150 μm), it was regarded as a “neck” defect.

[Comparative example]
As described in Patent Document 2, the traveling yarn was inspected by comparing the acquired image with a circumscribed rectangular image and an inscribed rectangular image obtained by image processing from the acquired image.

  In the above-described Examples 1 and 2 and the comparative example, the image data is individually analyzed for those detected as quality abnormalities, and the number of quality abnormalities actually detected is the number of quality abnormality positive detections. The numbers that were not quality abnormal are shown in Table 1 as the number of quality abnormality false detections.

  From the results of Table 1, it can be seen that Example 1 and Example 2 have a lower number of quality abnormality false detections than the comparative example. When analyzing the image data individually, some of the number of false detections of quality abnormalities in the comparative example were detected as quality abnormalities due to yarn swaying, or were detected as quality abnormalities simply by skewing. Most of the things.

  In Example 1, the standard deviation of the yarn width exceeds the first threshold, but the difference between the circumscribed rectangle width or the inscribed rectangle width and the average value of the yarn width is small, and it is not a defect that is a slight defect. In Example 2, the difference between the circumscribed rectangle width and the average value of the yarn width is the second threshold value, and the difference between the inscribed rectangle width and the average value of the yarn width is the third value. By comparing with the threshold value, it can be seen that the erroneous detection of the quality abnormality is further reduced.

  From the results shown in Table 1, the yarn inspection method of the present invention is less expensive than the conventional inspection method and is also erroneously detected due to yarn wobbling and skewing even when inspecting yarns traveling at high speed online. It has become clear that detection can be performed with higher accuracy.

  Furthermore, using the quality data obtained for each yarn, it was possible to manage the quality of the yarn, the yarn package around which the yarn was wound, and the yarn module. Moreover, by controlling the production process of the yarn using the quality data, it was possible to produce the yarn with a high yield.

  According to the present invention, quality control of yarns, yarn packages, and yarn modules is performed by simultaneously inspecting traveling yarns online, detecting defects accurately, and obtaining information on defects for each yarn. It can be performed. Therefore, the present invention is suitably used in the yarn manufacturing process and the yarn processing / processing step, but the application range is not limited thereto.

1: Imaging means 2: Illuminating means 3: Data processing means B {B _{1 to} B _{n + 1} }: Background portions formed between the running yarns and at both ends ID: Image data acquisition processing device L: Predetermined section P1: First side P2: Second side R1, R2: Yarn conveying roll YCD: Yarn traveling direction YCP: Yarn traveling surface YT {YT _{1 to} YT _n }: Yarn

Claims (17)

A yarn inspection method in which a traveling yarn is imaged by an imaging unit, and image data obtained by the imaging unit is processed by a data processing unit, wherein the data processing includes:
(A) a procedure for calculating a plurality of yarn widths in a predetermined section in the running direction from the image data of the running yarn; (b) a procedure for calculating a variation in yarn width from the plurality of yarn widths; and (c). A method of comparing the yarn width variation with a first threshold value.   The yarn width variation according to claim 1, wherein the variation in the yarn width is calculated from a plurality of yarn widths measured at measurement points designated by a predetermined number of divisions in the predetermined section. Inspection method. The data processing further includes (d) a procedure for calculating a circumscribed rectangular width and / or an inscribed rectangular width of the traveling yarn in a predetermined section in the traveling direction, and (e) a yarn width of the plurality of yarn widths. 3. The method according to claim 1, further comprising: a procedure for calculating a representative value; and (f) a procedure for comparing the representative value of the yarn width with the circumscribed rectangle width and / or the inscribed rectangle width. Yarn inspection method. The yarn inspection method according to claim 3, wherein the data processing further includes (g) a procedure of comparing a difference between the representative value of the yarn width and the circumscribed rectangle width with a second threshold value. . The yarn according to claim 3 or 4, wherein the data processing further includes (h) a step of comparing a difference between the representative value of the yarn width and the inscribed rectangle width with a third threshold value. Inspection method.   The representative value of the yarn width is an average value of a plurality of yarn widths measured at a measurement point designated by a predetermined number of divisions in the predetermined section. The yarn inspection method according to any one of the above.   The representative value of the yarn width is a median value of a plurality of yarn widths measured at a measurement point designated by a predetermined number of divisions in the predetermined section. The yarn inspection method according to any one of the above.   The representative value of the yarn width is a minimum value or a maximum value of a plurality of yarn widths measured at a measurement point designated by a predetermined number of divisions in the predetermined section. To 5. The yarn inspection method according to any one of 5 to 5.   The representative value of the yarn width is a yarn width in a predetermined order obtained by sorting a plurality of yarn widths measured at measurement points designated by a predetermined number of divisions in the predetermined section in ascending order. The yarn inspection method according to any one of claims 3 to 5, wherein: The data processing further includes (d) a procedure for calculating a circumscribed rectangular width and / or an inscribed rectangular width of the traveling yarn in a predetermined section in the traveling direction, and (i) a predesigned yarn width and the circumscribed rectangular width. And / or a procedure of comparing the width of the inscribed rectangle with each other. The yarn inspection according to claim 10, wherein the data processing further includes (j) a step of comparing a difference between the pre-designed yarn width and the circumscribed rectangle width with a fourth threshold value. Method. The yarn according to claim 10 or 11, wherein the data processing further includes (k) a step of comparing a difference between the pre-designed yarn width and the inscribed rectangle width with a fifth threshold value. Article inspection method. The data processing further includes (e) a procedure for calculating a representative value of the yarn width from the plurality of yarn widths, and (l) a difference between the pre-designed yarn width and the representative value of the yarn width, The yarn inspection method according to any one of claims 1 to 12, further comprising a procedure of comparing with a threshold value.   An image pickup means for picking up a traveling yarn, and a data processing means for processing data of image data obtained by the image pickup means, using the yarn inspection method according to any one of claims 1 to 13. A yarn inspection device that inspects the running yarn.   A yarn manufacturing method comprising an inspection step of inspecting a traveling yarn using the yarn inspection method according to any one of claims 1 to 13.   A yarn package comprising a yarn produced by the method according to claim 15.   A yarn module comprising a yarn produced by the method according to claim 15.

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