WO2014054528A1 - Procédé d'inspection de filets, dispositif d'inspection de filets, procédé de production de filets, ensemble filet et module à filet - Google Patents

Procédé d'inspection de filets, dispositif d'inspection de filets, procédé de production de filets, ensemble filet et module à filet Download PDF

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Publication number
WO2014054528A1
WO2014054528A1 PCT/JP2013/076253 JP2013076253W WO2014054528A1 WO 2014054528 A1 WO2014054528 A1 WO 2014054528A1 JP 2013076253 W JP2013076253 W JP 2013076253W WO 2014054528 A1 WO2014054528 A1 WO 2014054528A1
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WIPO (PCT)
Prior art keywords
yarn
width
thread
inspection method
procedure
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PCT/JP2013/076253
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English (en)
Japanese (ja)
Inventor
亮 内野
理 倉又
尚 皆木
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東レ株式会社
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Application filed by 東レ株式会社 filed Critical 東レ株式会社
Priority to KR1020157009712A priority Critical patent/KR102047153B1/ko
Priority to JP2013556080A priority patent/JP6260280B2/ja
Priority to CN201380051780.6A priority patent/CN104685347B/zh
Publication of WO2014054528A1 publication Critical patent/WO2014054528A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
    • D—TEXTILES; PAPER
    • D06—TREATMENT OF TEXTILES OR THE LIKE; LAUNDERING; FLEXIBLE MATERIALS NOT OTHERWISE PROVIDED FOR
    • D06H—MARKING, INSPECTING, SEAMING OR SEVERING TEXTILE MATERIALS
    • D06H3/00—Inspecting textile materials
    • D06H3/08—Inspecting textile materials by photo-electric or television means
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/89—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles
    • G01N21/892—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles characterised by the flaw, defect or object feature examined
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G01N21/952—Inspecting the exterior surface of cylindrical bodies or wires

Definitions

  • 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.
  • Threads represented by fibers, fibers and hollow fiber membranes have been used and utilized in various fields and applications since the past.
  • 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.
  • 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.
  • 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 manufacturing.
  • 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.
  • 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.
  • 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.
  • 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).
  • 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.
  • the present invention adopts the following method.
  • 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 the predetermined number of divisions in the predetermined section.
  • 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.
  • the data processing may include (g) the yarn in addition to (a), (b), (c), (d), (e), and (f).
  • 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.
  • 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.
  • the data processing is performed in addition to (a), (b), (c), (d), and (i), and (j) the previously designed yarn.
  • 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 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.
  • the yarn manufacturing method of the present invention includes an inspection step of inspecting the traveling yarn using any one of the above-described 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.
  • the running yarn is imaged, and the total length of the running yarn is inspected from the obtained image data.
  • the yarn which should be recognized as normal, from being erroneously recognized as a defect due to running yarn skew or skew.
  • 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.
  • 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.
  • 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. 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
  • 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.
  • 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.
  • the product is a yarn product having any of the above, any object can be inspected.
  • 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.
  • hollow fiber membrane to which the yarn inspection method of the present invention is applied examples include polycarbonate, polyolefin, polyamide, polyimide, cellulose, polysulfone, polyethersulfone, polymethacrylic acid, polyacrylonitrile, and polyfluoride.
  • 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.
  • 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 the traveling yarn and a data processing means for processing the image data obtained by the image pickup means.
  • the imaging means refers to a sensor in which image sensors (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.
  • image sensors 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.
  • 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.
  • manufacturer products such as Nippon Electro Sensor Device Co., Ltd., Takenaka System Equipment Co., Ltd., Basler Co., DALSA Co., etc. can be used.
  • the imaging means 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 running 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 illuminating means in the present invention it is only necessary to 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%.
  • 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
  • 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.
  • 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 position on a different side.
  • the imaging unit receives light reflected or scattered by the yarn illuminated by the illumination unit.
  • the yarn portion is imaged as a bright portion and the background portion as a dark portion.
  • 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.
  • a high-frequency lighting type fluorescent lamp, LED line illumination or the like in which the irradiated portion is in a line shape can be used.
  • 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
  • illumination means for illuminating the end face of a cylindrical rod lens 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.
  • the traveling yarn is imaged by the imaging means, and the obtained image data is processed by the data processing means.
  • 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 around the yarn periphery are imaged.
  • the yarn portion in a predetermined section in the traveling direction is extracted.
  • 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.
  • image noise 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.
  • 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.
  • step B the yarn width variation is calculated for each yarn from the yarn width data group calculated in step A.
  • 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.
  • step C the variation in the yarn width data group calculated in step 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.
  • 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.
  • 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. .
  • this predetermined section needs to be larger than the influence range of the defect. Specifically, if it is set to about 1 to 10 times the influence range of the defect. good.
  • FIG. 1 is a schematic side view of an inspection apparatus that acquires and processes image data used for carrying out 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.
  • 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 R1, R2, and travel in the direction indicated by the arrow YCD.
  • a running surface YCP (shown 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 / absence and state of the running yarn defect.
  • FIG. 3 is a schematic diagram of data processing means for processing image data after obtaining the image data used for carrying out the yarn inspection method of the present invention.
  • 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.
  • procedure B a variation in yarn width is calculated for each yarn from the calculated yarn width data group.
  • 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.
  • 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.
  • 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).
  • 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).
  • 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.
  • 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.
  • 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.
  • 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).
  • 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
  • step E the representative value of the yarn width is calculated from the yarn width data group for each yarn obtained from the image data.
  • step 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.
  • 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.
  • the difference between the circumscribed rectangle width and the representative value of the yarn width is larger than the second threshold value, for example, it is determined that the yarn has a defect “node”. 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.
  • 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).
  • 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).
  • 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 ⁇ m), 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.
  • the second threshold value e.g. 150 [mu] m
  • 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.
  • 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.
  • step I the pre-designed yarn width is compared with the circumscribed rectangle width and / or inscribed rectangle width.
  • procedure J 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).
  • a fourth threshold value for example, 150 ⁇ m
  • a fifth threshold for example, 150 ⁇ m
  • procedure L a procedure 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 ⁇ m), it can be determined that the yarn is manufactured with the designed yarn width.
  • a sixth threshold for example, 50 ⁇ m
  • 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.
  • 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.
  • 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.
  • the “yarn package” in the present invention refers to a state in which yarns that have been made 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.
  • the yarn is a hollow fiber membrane
  • a dialyzer used for artificial dialysis and a cartridge used for water purification can be used.
  • 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.
  • 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
  • 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 ⁇ m), 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 ⁇ m), 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 ⁇ m), it was regarded as a “neck” defect.
  • 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.
  • 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.
  • Example 1 and Example 2 have a lower number of erroneously detected quality abnormalities than the comparative example.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • Image pickup means 2 Illumination 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 transporting roll YCD: Yarn traveling direction YCP: Yarn traveling surface YT ⁇ YT 1 to YT n ⁇ : Yarn

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Abstract

Cette invention concerne un procédé d'inspection de filets. Dans le procédé de production de filets destiné à produire un filet sans fin continu dans le sens longitudinal selon l'invention, une image du filet sans fin est capturée, et la longueur totale du filet sans fin est inspectée à grande vitesse à partir des données d'images obtenues, pour acquérir ainsi des informations concernant un défaut de filet sans fausse reconnaissance d'un cas où le filet tremble simplement ou d'un cas où le filet est simplement oblique comme un défaut de filet. Le procédé d'inspection de filets selon l'invention est caractérisé en ce qu'une image d'un filet sans fin est capturée par un moyen de capture d'images, et les données d'images obtenues par le moyen de capture d'images sont soumises à un traitement de données par un moyen de traitement de données, ledit traitement de données comprenant : (a) une étape de calcul d'une pluralité de largeurs de filet dans une partie prédéfinie dans le sens longitudinal à partir des données d'images relatives au filet sans fin ; (b) une étape de calcul d'une variation de largeur de filet à partir de la pluralité de largeurs de filet ; et (c) une étape de comparaison de la variation de largeur de filet à une première valeur de seuil.
PCT/JP2013/076253 2012-10-04 2013-09-27 Procédé d'inspection de filets, dispositif d'inspection de filets, procédé de production de filets, ensemble filet et module à filet WO2014054528A1 (fr)

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KR1020157009712A KR102047153B1 (ko) 2012-10-04 2013-09-27 사조의 검사 방법, 사조의 검사 장치, 사조의 제조 방법, 사조 패키지 및 사조 모듈
JP2013556080A JP6260280B2 (ja) 2012-10-04 2013-09-27 糸条の検査方法、糸条の検査装置、糸条の製造方法、糸条パッケージおよび糸条モジュール
CN201380051780.6A CN104685347B (zh) 2012-10-04 2013-09-27 丝线的检查方法、丝线的检查装置、丝线的制造方法、丝线卷装以及丝线模块

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WO2018105489A1 (fr) * 2016-12-06 2018-06-14 日本電気硝子株式会社 Procédé d'inspection de la qualité d'un film de verre de type ruban et rouleau de verre
JP2019506623A (ja) * 2016-01-22 2019-03-07 エムジー センサーズ リミテッドＭｇ Ｓｅｎｓｏｒｓ Ｌｉｍｉｔｅｄ 糸撮像装置
WO2021205745A1 (fr) * 2020-04-06 2021-10-14 村田機械株式会社 Dispositif de surveillance de fil, procédé de surveillance de fil, enrouleur de fil et système de surveillance de fil

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CN110857919A (zh) * 2018-08-24 2020-03-03 东华大学 一种卷装长丝的尾丝缺陷检测方法
KR102478600B1 (ko) * 2021-12-27 2022-12-15 재단법인 한국섬유기계융합연구원 와전류 센서를 이용한 스프레드 탄소섬유의 섬유 배열 균제도 측정 시스템 및 그 방법

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CN104685347A (zh) 2015-06-03
KR102047153B1 (ko) 2019-11-20

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