Search

EP-4735881-A1 - METHOD AND DEVICE FOR CLASSIFYING AN EVENT IN AN ELONGATE TEXTILE TEST SPECIMEN

EP4735881A1EP 4735881 A1EP4735881 A1EP 4735881A1EP-4735881-A1

Abstract

In this computer-implemented method for classifying an event in an elongate textile test specimen, at least one measured value of at least one event parameter for the event is measured (901). At least one reference dataset, containing, for a respective reference event, at least one reference value of the at least one event parameter and a classification of the reference event, is provided (902). The at least one measured value is compared (904) with the at least one reference value of all of the reference datasets. The event is classified (908) in accordance with the classification of the reference event whose at least one reference value is most similar to the at least one measured value in accordance with a predefined similarity criterion. The method achieves high quality and, at the same time, high productivity.

Inventors

  • GANAPATHY, Parameswaran
  • JOSS, ROLF

Assignees

  • Uster Technologies AG

Dates

Publication Date
20260506
Application Date
20240820

Claims (20)

  1. 1. A computer-implemented method for classifying an event (540, 640, 740) in an elongated textile test piece (110), comprising the following steps: a) measuring (901) at least one measured value of at least one event parameter for the event (540, 640, 740); b) providing (902) at least one reference data set, which contains, for each reference event, at least one reference value of the at least one event parameter and a classification of the reference event; c) comparing (904) the at least one measured value with the at least one reference value of all reference data sets; and d) classifying (908) the event (540, 640, 740) according to the classification of the reference event whose at least one reference value is most similar to the at least one measured value according to a predetermined similarity criterion.
  2. 2. The method according to claim 1, wherein the at least one event parameter is an event variable, for example a deviation of a length-related mass density, a cross-section or a reflectivity of the test material (110) from a target value, and the at least one reference value and the at least one measured value are each a signal (220, 210) which consists of a plurality of values of the event variable as a function of a length position or of time.
  3. 3. The method of claim 2, wherein the similarity criterion includes a cross-correlation of the two signals.
  4. 4. The method according to claim 1, wherein the at least one event parameter comprises an event size, for example a deviation of a length-related mass density, a cross-section or a reflectivity of the test material (110) from a target value, and an event length.
  5. 5. The method according to claim 4, wherein the similarity criterion includes a distance between a point representing the event and a point representing the reference event (811, 812) in a coordinate system spanned by the event length and the event size.
  6. 6. Method according to one of the preceding claims, wherein several different event parameters are taken into account.
  7. 7. The method according to claim 6, wherein at least one first event parameter is measured capacitively and at least one second event parameter is measured optically.
  8. 8. Method according to one of the preceding claims, wherein the measured value of the at least one event parameter is measured (901) while the elongated textile test material (110) is moved along its longitudinal direction.
  9. 9. Method according to one of the preceding claims, wherein the at least one reference data set is provided (1003) by measuring the at least one reference value for each reference event (1003), the reference event is visually assessed and classified by an operator (1007), and the classification is assigned to the at least one reference value (1008) and stored together with the reference value as a reference data set (1009).
  10. 10. The method of claim 9, wherein the reference event is visually assessed by capturing (1006) an image (520, 620, 720) of the reference event and presenting the image (520, 620, 720) to the operator for visual assessment.
  11. 11. Method according to one of the preceding claims, wherein the classification (908) is carried out in a classification system with exactly two classes, namely a first class with permissible events and a second class with impermissible events.
  12. 12. Computer-implemented method for cleaning yarn (110) moved along its longitudinal direction, wherein events (540, 640, 740) in the yarn (110) are classified according to claim 11 and events classified in the second class are removed from the yarn (110).
  13. 13. A device (120) for classifying an event (540, 640, 740) in an elongated textile test piece (110), comprising: a) a measuring device (121) for measuring at least one measured value of at least one event parameter for the event (540, 640, 740); and a computer system (123) with b) a memory (125) for storing at least one reference data set, which contains, for each reference event, at least one reference value of the at least one event parameter and a classification of the reference event; c) a processor configured to compare the at least one measured value with the at least one reference value of all reference data sets; and d) a processor configured to classify the event (540, 640, 740) according to the classification of the reference event whose at least one reference value is most similar to the at least one measured value according to a predetermined similarity criterion.
  14. 14. Device (120) according to claim 13, wherein the at least one event parameter is an event variable, for example a deviation of a length-related mass density, a cross-section or a reflectivity of the test material from a target value, the at least one reference value and the at least one measured value are each a signal (220, 210) which consists of a plurality of values of the event variable as a function of a length position or of time, and the measuring device (121) is set up to record the signal (210).
  15. 15. Device (120) according to claim 13, wherein the at least one event parameter comprises an event size, for example a deviation of a length-related mass density, a cross-section or a reflectivity of the test material (110) from a target value, and an event length.
  16. 16. Device (120) according to one of claims 13-15, wherein the measuring device (121) is arranged to measure a plurality of different event parameters.
  17. 17. The device (120) according to claim 16, wherein the measuring device (121) is configured to capacitively measure at least one first event parameter and to optically measure at least one second event parameter.
  18. 18. The apparatus (120) according to any one of claims 13-17, wherein the processor is configured for classifying in a classifying system having exactly two classes, namely a first class with permissible events and a second class with impermissible events.
  19. 19. Yarn clearing system for cleaning yarn (110) moving along its longitudinal direction, comprising a device (120) according to claim 18 and a cutting device triggerable by the computer system (123) for cutting the yarn (110) as a result of classifying an event in the second class.
  20. 20. Yarn processing machine, e.g., a dishwashing machine (100) or spinning machine, having a plurality of yarn processing stations (101, 102), at each of which yarn (110) is wound onto a bobbin (112), comprising a yarn clearing system according to claim 19.

Description

Method and device for classifying an event in an elongated textile test piece FIELD OF EXPERTISE The present invention lies in the field of textile quality control. It relates to a computer-implemented method and a device for classifying an event in an elongated textile test sample. The invention also relates to a yarn clearing system and a yarn processing machine. It is preferably, but not exclusively, used in yarn clearers on spinning or dishwashing machines. Furthermore, the invention relates to a computer-implemented method for providing at least one reference data set for the method or device according to the invention for classifying an event. Finally, the invention also relates to a computer-readable medium on which at least one reference data set provided according to the method is stored. STATE OF THE ART To ensure yarn quality, so-called yarn clearers are used in spinning or dishwashing machines. A yarn clearer contains a measuring head with at least one sensor that scans the moving yarn. Commonly used sensor principles are capacitive and optical, both of which are described in WO-2012/051730 A1. The purpose of scanning is to detect events in the yarn. In this document, «events» in the elongated textile test piece are defined as points in the longitudinal direction (i.e., having a finite length of usually less than 1 m) at which at least one specific measured value deviates from a corresponding target value. If the elongated textile test piece is moved along its longitudinal direction, an event occurs in a finite time interval (of (usually less than 1 s) a fixed point, e.g., a sensor. Examples of events are thick spots, thin spots, or foreign matter in a yarn. Measurement results obtained from the sensor signal are continuously evaluated against predefined criteria, such as a cleaning limit. If a yarn defect is below the cleaning limit, it is tolerable; if it is above the cleaning limit, it is an intolerable yarn defect that must be removed from the yarn or at least recorded. The basis of yarn clearing is therefore a classification of yarn defects into a classification system with two classes: tolerable and intolerable yarn defects. A method for defining a cleaning limit is disclosed in WO-2011/038524 A1. First, a statistical representation of the yarn is determined by measurements on the yarn. Based on the statistical representation, the cleaning limit is calculated and suggested for application. A length-related number of inadmissible events expected with this cleaning limit is calculated and output. An operator can comment on the expected number of inadmissible events, after which the cleaning limit is automatically determined according to the comment. The yarn events can be plotted as points in a two-dimensional classification scheme, in which the defect length is typically plotted along the abscissa and the defect size (deviation of the mass per yarn length, the yarn cross-section, the yarn reflectivity, etc. from a target value) is plotted along the ordinate. Examples of a cleaning limit and a classification scheme are also given in WO-2011/038524 A1. According to EP-0'685'580 A1, yarn defects are recorded, entered into the classification scheme, and counted in each class. This creates a defect pattern in the classification scheme. This defect pattern is compared with predefined model reference patterns that allow conclusions to be drawn about the causes of the detected defects. The predefined reference patterns can be determined through prior testing or from experience. According to WO-2010/078665 A1, event densities in the classification scheme are determined from the defect size and length. In the classification scheme, a yarn body is represented as a surface. The surface is bounded by the abscissa, the ordinate, and a line in the event field that follows a constant event density. The events in the yarn body can be considered statistical "noise" belonging to the actual yarn and should not be removed from the yarn. WO-2013/185246 A1 also teaches the representation of a first density line in the classification scheme, which refers to a first test sample and follows a constant event density. In addition to the first density line, a reference density line is represented, which follows the same event density as the first density line but refers at least partially to a reference test sample that is different from the first test sample. This enables a comparison of the courses of the first density line and the reference density line. From the comparison of the courses of the density lines, a comparison of the qualities of the first test sample and the reference test sample can be made. WO-00/73189 A1 aims to enable improved, simplified, and rapid adjustment of the cleaning limit so that its effect on the final product can be more accurately predicted. To this end, representations of defects in the final product, e.g., in the yarn, are to be generated based on the cleaning limit, which visualiz