EP0877108B1 - Verfahren und Vorrichtung zum Reinigen von Garnen - Google Patents

Verfahren und Vorrichtung zum Reinigen von Garnen Download PDF

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Publication number
EP0877108B1
EP0877108B1 EP98106399A EP98106399A EP0877108B1 EP 0877108 B1 EP0877108 B1 EP 0877108B1 EP 98106399 A EP98106399 A EP 98106399A EP 98106399 A EP98106399 A EP 98106399A EP 0877108 B1 EP0877108 B1 EP 0877108B1
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EP
European Patent Office
Prior art keywords
yarn
density
defects
values
classification field
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Expired - Lifetime
Application number
EP98106399A
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German (de)
English (en)
French (fr)
Other versions
EP0877108A1 (de
Inventor
Hanspeter Wepfer
Johannes Heusser
Enrico Biondi
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Uster Technologies AG
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Uster Technologies AG
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Publication of EP0877108A1 publication Critical patent/EP0877108A1/de
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Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65H—HANDLING THIN OR FILAMENTARY MATERIAL, e.g. SHEETS, WEBS, CABLES
    • B65H63/00—Warning or safety devices, e.g. automatic fault detectors, stop-motions ; Quality control of the package
    • B65H63/06—Warning or safety devices, e.g. automatic fault detectors, stop-motions ; Quality control of the package responsive to presence of irregularities in running material, e.g. for severing the material at irregularities ; Control of the correct working of the yarn cleaner
    • B65H63/062—Electronic slub detector
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65H—HANDLING THIN OR FILAMENTARY MATERIAL, e.g. SHEETS, WEBS, CABLES
    • B65H2701/00—Handled material; Storage means
    • B65H2701/30—Handled filamentary material
    • B65H2701/31—Textiles threads or artificial strands of filaments

Definitions

  • the invention relates to a method and an apparatus for cleaning yarn in which measurable properties of the yarn during its production or rewinding detected and yarn defects to be cleaned defined by an adjustable cleaning limit which indicates which yarn defects are cleaned and which are not.
  • Such a method is known for example from CH 683 350.
  • Two-dimensional yarn defect due to a deviation from a target value of the yarn thickness and the length of the yarn defect are mapped and classified.
  • the numbers of yarn defects that have occurred and are measured are entered, for example stored in cells.
  • the cleaning limit is set so that it is in the Surroundings of cells with high numbers of yarn defects outside, in the surroundings of cells with low numbers of yarn defects is moved inwards. In this way the number of necessary knots or splices in the yarn is reduced.
  • EP 415222 describes a method for setting response limits electronically Yarn cleaner known. The measured values of the Delicacy is recorded continuously and over a long length of yarn and it becomes their distribution certainly. From this distribution and from a predetermined permissible alarm frequency the response limits become independent on the basis of statistical laws established. These response limits become additional to known cleaning limits specified.
  • This further procedure concerns the setting of response limits in yarn monitoring systems, where yarn number deviations or deviations in yarn count, the middle dimension of a yarn, trigger an alarm or stop production, where a yarn as a whole is wrong or right, i.e. has the right delicacy or not.
  • a method for optimally managing a cleaning limit without much effort is missing with that still.
  • the invention as characterized in the claims, therefore solves the problem of to create a method and a device that allow the determination and Adjust the cleaning limit for yarn cleaners so that they are as frequent as possible and an optimal setting can be achieved if certain requirements are met.
  • the cleaning limit is once set is also automatically set on the thread cleaner so that it changes periodically or can continuously adapt to the type and frequency of yarn defects that occur. This can based on a standard or initial setting, or data from a previous one Production of the same item is done.
  • the definition of the cleaning limit is that Result of a regulation, the measured values of properties of the yarn and various, important criteria for the course of the cleaning limit are taken into account and preferably processed according to rules of fuzzy logic. The criteria mentioned can be difficult be measurable or not in a clear mathematical context with the Cleaning limit.
  • the device mentioned essentially consists of a control loop with a fuzzy controller, an input for values of properties recorded on the yarn and from units for Entry of criteria for determining or influencing the cleaning limit.
  • a control loop can also have multiple entries for values of several yarns and with several Yarn cleaner to be connected to the output of a common cleaning limit.
  • the advantages achieved by the invention can be seen in the fact that different criteria can be considered for the design of the cleaning limit. These can refer to the yarn such as the density of the yarn defects or the shape of the package, or they can affect the line on which yarn is produced or rewound such as the type of sensor (optical or capacitive). Further criteria can consider general quality considerations such as the fact that large yarn defects are more disturbing than small ones or that certain defects in one area affect the Disturb users particularly badly, etc. Also, cleaning limits can be reached Adjust the method used to measure yarn defects. For example, so take into account the fact that the capacitive scanning of the yarn is very short Yarn defects are no longer fully detected, but the optical scanning also shows short yarn defects in full extent.
  • the system can be left to its own devices, that is, without it special input, starting from a standard input, work or it can be optimized by appropriate entries according to all possible criteria work.
  • the proposed modeling of the yarn defects based on the determined Yarn error values can be the amount of samples or yarn error values required for creation a representative relief of the yarn defect density and thus for the determination of a cleaning limit are necessary to be reduced.
  • 1 shows a horizontal axis 1, along the values for a first dimension or one first parameters, here the length, of yarn defects are recorded.
  • a vertical Axis 2 are deviations in diameter (or mass) for a yarn to an average diameter (or average mass) as a percentage of the average Diameter (or the average mass) as a second dimension or second parameter applied.
  • Fields 3 in particular fields 3a, 3b, 3c, etc., the classes for yarn defects define how they are already described in CH 477 573 and general are known under the name USTER CLASSIMAT. In the plane or in the fields 3 yarn error measurements are indicated by crosses.
  • the cross indicates 4 that the length of the yarn defect is about 8 cm and its thickness or mass is the middle Diameter or the average mass exceeds 400%.
  • the cleaning limit is 5 piles or Clouds of crosses and thus yarn faults are circumvented in such a way that between axis 1 and the cleaning limit 5.
  • Fig. 2 shows a block diagram of the method or the device for cleaning yarn.
  • the device consists of a control circuit 6, which is preferably a fuzzy controller trained controller 7 and several processing units 8, 9 and 10 for individual process steps has, but which are just as well understood as part of the controller 7 can. Here they are for clearer presentation of individual functions or procedural steps listed individually.
  • the processing unit 8 is actually a memory with several Storage locations, the parameters (length and diameter deviation) of a yarn defect save for a selectable thread length (e.g. 100km).
  • the processing unit 8 with the The memory also has at least one input 11 a, 11 b for measured values and this is again connected to a yarn cleaner 32, 33. If the device for several Yarn cleaner works, several inputs 11 are provided accordingly.
  • the processing unit 9 is used to prepare the individual measured values, as will be shown later and consists essentially of a processor or computer or a part of such.
  • the processing unit 10 also consists of a memory with several Storage locations corresponding to fields 3a, 3b, 3c etc. (Fig. 1).
  • the regulator 7, the out a processor or computer also has an output 12 for values of a cleaning limit and, if it is designed as a fuzzy controller, further inputs 13 for which Entering productivity criteria, 14 for entering general quality criteria, 15 for entering yarn-specific criteria, 16 for entering plant-specific criteria Criteria and 17 for entering additional or special quality criteria.
  • the exit 12 is in turn connected to the processing unit 8, so that the values of the Cleaning limit, as indicated by field 30, there again for storage, for Display or issue for further purposes.
  • the output 12 is the Controller 7 is preferably also connected to the yarn cleaners 32, 33.
  • a modeled yarn defect is a partial and simplified reconstruction of a yarn defect from a single measurement. For example, it is modeled as a Gauss bell. Its maximum is provided at the point where the corresponding cross, for example cross 4 in Fig. 1, would be in the classification field.
  • the volume under the bell is defined as 1.
  • the partial surface 19 is here through an axis 20, along the radius or Diameter deviations are plotted and an axis 21, along which the lengths of the Errors are plotted limited.
  • the height or the volume is along an axis 22 of the yarn error.
  • the values of the yarn defects are recorded with certain tolerances are determined by the system for the registration, e.g. uneven speed of the yarn. If the same thread defect were measured a second time, it could easily be different Result in values and can even be classified differently in the classification field. On the other hand, decreased the meaning of the mentioned tolerances if a lot of yarn errors are measured can.
  • FIG. 4 shows the sum of modeled yarn defects over a level according to level 3 in FIG. 1 shown as area 29. These modeled yarn defects are plotted on the same axes, as they are known from FIG. 3. In contrast to Fig. 3, there are many Partial areas 19 with the modeled yarn errors added together recorded so that the modeled measured values of the individual partial areas 19 are also correct can still influence each other by making smooth transitions between the Adjust marginal areas of the partial areas. Large error frequencies can be seen in particular in an area 23, lower error rates in an area 24 and none noteworthy frequencies in adjacent areas.
  • a surface 25 which indicates the degree of disturbance caused by a yarn defect. From this you can see for example, that a yarn defect with a large length and a large mass or Diameter deviation means a major disturbance caused, for example, by Values can be quantified.
  • areas 26a, 26b, 26c, etc. are increasing disturbing yarn defects defined.
  • the area 25 is thus a Part of a conical surface. But it can also be any area that indicates the degree of interference represented in the sense of the user.
  • a yarn cleaner 32, 33 yarn errors or their measured values are determined with the yarn sensor, which correspond, for example, to the diameter or the mass of the yarn.
  • the diameter deviation and the length of a yarn defect are chosen as parameters - they are related in a known manner to an average value for the diameter or the mass of the yarn per unit length and from this the relative deviation to the average Diameter or the average yarn mass calculated. Values for the length of such deviations which exceed a threshold value (for the mass or the diameter) are determined in the yarn cleaner in a likewise known manner from these measured values.
  • Such measured values for the relative deviation and the length of the deviation are introduced into the control circuit 6 via the input 11.
  • these values first reach the processing unit 8, where they are stored.
  • yarn error values are stored for a predetermined yarn length, which can occupy an entire classification field, as shown in FIG. 1 with the yarn errors indicated by crosses 4.
  • These processes are already known per se, since the classification of values that are measured on the yarn has long been state of the art.
  • the processes just described can also be carried out for measured values of several yarns from several yarn cleaners, which input all of their measured values into the processing unit 8 via the inputs 11.
  • the contents of the memories or just the yarn defects are read into the processing unit 9, where the yarn defects are modeled as shown in FIG. 3.
  • the entire classification field i.e. the entirety of fields 3a, 3b, 3c, etc. according to FIG.
  • a grid is finely divided by a grid, the grid fields of which can comprise one or more partial areas 19, so that a modeled yarn defect is spread over one or more grid fields can extend.
  • the grid can, for example, be resolved in 5% steps along axis 2 and in 1 mm steps along axis 1.
  • the extent of the Gauss bell can also be varied and should expediently extend over several grid fields. The more the bell is stretched, the smaller its height so that the volume remains constant. The further away the yarn defect to be modeled is from the intersection of axes 1 and 2, the more the Gauss bell representing it should be stretched. In order to later calculate the density in a grid, the volumes of all Gauss bell parts located above the grid are added together.
  • the density is also calculated in the same way over the entire classification field, so that the density can be represented as area 29, as shown in FIG. 4.
  • the purpose of these processes is to ensure that, when determining the local yarn defect density, there are no isolated discrete values, but an area is formed that allows a statement about the density of the yarn defects at every location in the classification field. This is especially true where only a few yarn defects are to be expected.
  • a surface 25 was loaded into the processing unit 10 in parallel or in advance, as shown in Fig. 5, which is a representation of the gard of the failure of yarn defects indicates.
  • the controller 7 finds a comparison between the now available ones Values about the yarn defect density and given criteria instead. All of these operations in the processing units 9, 10 and in the computer 7 run on a purely computing level from, i.e. the illustrations shown in FIGS. 3 to 5 are only for a better explanation to understand.
  • the allowable degree of disruption as caused by the Area 25 is expressed and the sum of modeled yarn defects or the yarn defect density as expressed by the area 29 (FIG. 4), it can be determined which yarn defects, which are shown in Fig. 4, are not permitted and which are not.
  • controller 7 or preferably fuzzy controller, which is thus a known first Rule taken into account, which is roughly as follows: The larger the product of mass and the length of the yarn defect, the more troublesome the yarn defect.
  • This rule will be expressed by the representation in FIG. 5.
  • this could be the first Cleaning limit can be obtained by cutting the surface 25 with that surface which represents the sum of the modeled yarn defects in FIG. As for ongoing measurements on the yarn this sum also forms a continuously changing surface that Surface 25 but remains the same over time, the cutting line adjusts and thus the cleaning limit automatically to changed conditions and thus the controller 7 passes the output 12 the values of a cleaning limit. This can be periodic, ongoing or happen at the external instigation. A conventional one is sufficient for this controllers known from other applications 7.
  • the course of a cleaning limit is in Fig. 4 designated 31.
  • the cleaning limit is not optimized for all cases. To do this, there should be further criteria can be taken into account. These can be productivity criteria, for example, which are entered into controller 7 via input 13.
  • productivity criteria for example, which are entered into controller 7 via input 13.
  • One such criterion is, for example the number of allowed cuts per km of yarn.
  • General quality criteria can be entered via input 14 become. For example, can be specified as a rule that areas with relatively high Yarn defect density in the classification field must be avoided by the cleaning limit.
  • Soche areas can be identified by the fuzzy controller when it leaves the processing unit 10 receives an indication of the yarn defect density and this with a specification compares.
  • Yarn-specific criteria e.g. to adjust the Cleaning can be specified to the yarn characteristics. As a criterion, for example a distance to the package is entered, which defines a zone around the package, in which errors are disregarded. System-specific can also be input 16 Criteria can be entered. Here the comparability of measured values from different (optical, capacitive) cleaning systems are promoted by as As a rule, it is specified that short yarn errors are greater for capacitively determined measured values, however, long yarn defects are weighted more heavily for optically determined measured values. Or it can be specified that process-related systematic yarn defects are specially cleared or not to be cleaned.
  • the invention uses a preferred example of properties of the yarn, i.e. the deviations in thickness or mass and their length has been set out, this can in the same sense for other properties such as the color, the structure (hairiness, Twist), periodic fluctuations in the diameter of the yarn. So could also for yarn defects such as foreign fibers, foreign substances, hairiness etc. cleaning limits be set and adjusted.

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  • Engineering & Computer Science (AREA)
  • Textile Engineering (AREA)
  • Quality & Reliability (AREA)
  • Filamentary Materials, Packages, And Safety Devices Therefor (AREA)
  • Length Measuring Devices With Unspecified Measuring Means (AREA)
  • Spinning Or Twisting Of Yarns (AREA)
  • Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
EP98106399A 1997-04-23 1998-04-08 Verfahren und Vorrichtung zum Reinigen von Garnen Expired - Lifetime EP0877108B1 (de)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
CH93897 1997-04-23
CH938/97 1997-04-23
CH93897 1997-04-23

Publications (2)

Publication Number Publication Date
EP0877108A1 EP0877108A1 (de) 1998-11-11
EP0877108B1 true EP0877108B1 (de) 2003-07-16

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EP98106399A Expired - Lifetime EP0877108B1 (de) 1997-04-23 1998-04-08 Verfahren und Vorrichtung zum Reinigen von Garnen

Country Status (5)

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US (1) US6374152B1 (ja)
EP (1) EP0877108B1 (ja)
JP (1) JP4117583B2 (ja)
CN (1) CN1154758C (ja)
DE (1) DE59809009D1 (ja)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102008037758A1 (de) 2008-08-14 2010-02-18 Oerlikon Textile Gmbh & Co. Kg Verfahren zur Qualitätsüberwachung eines längsbewegten Garnes an einer Arbeitsstelle einer Kreuzspulen herstellenden Textilmaschine
DE102019116475A1 (de) * 2019-06-18 2020-12-24 Saurer Spinning Solutions Gmbh & Co. Kg Optimierung des Betriebes einer Spinnmaschine
DE102022004857A1 (de) 2022-12-22 2024-06-27 Oerlikon Textile Gmbh & Co. Kg Verfahren zum Ermitteln der Spulenqualität einer Sammelspule

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DE50001563D1 (de) * 1999-05-29 2003-04-30 Zellweger Luwa Ag Uster Verfahren und vorrichtung zum reinigen von garn
DE10129201A1 (de) * 2001-06-18 2002-12-19 Rieter Ingolstadt Spinnerei Eigenoptimierung für fadenführende Maschinen
DE10141963A1 (de) * 2001-08-28 2003-03-20 Rieter Ingolstadt Spinnerei Verfahren zum Einstellen einer Reinigungsgrenze bei einem elektronischen Garnreiniger
DE10352429A1 (de) 2003-11-10 2005-06-23 Saurer Gmbh & Co. Kg Garnreiniger
DE102004013776B4 (de) * 2004-03-20 2017-07-27 Rieter Ingolstadt Gmbh Verfahren und Vorrichtung zur Ausreinigung von Garnfehlern
JP2007211363A (ja) * 2006-02-08 2007-08-23 Murata Mach Ltd 糸欠点のクリアリング判定方法と糸処理装置
DE102007028651A1 (de) * 2007-06-21 2008-12-24 Oerlikon Textile Gmbh & Co. Kg Verfahren zur Visualisierung der Häufigkeitsverteilung von Garnfehlern
DE102008017258A1 (de) 2008-04-04 2009-10-08 Oerlikon Textile Gmbh & Co. Kg Verfahren und Vorrichtung zur optischen Detektion von Fremdfasern in einem längs bewegtem Faserstrang
CH699219A1 (de) * 2008-07-25 2010-01-29 Uster Technologies Ag Verfahren und Vorrichtung zur Garnreinigung.
CH699599A1 (de) * 2008-09-29 2010-03-31 Uster Technologies Ag Verfahren und vorrichtung zur überwachung von spleissen in einem länglichen textilen prüfgut.
CH700209A1 (de) * 2009-01-07 2010-07-15 Uster Technologies Ag Verfahren und vorrichtung zur charakterisierung eines länglichen textilen prüfguts.
CH701957A8 (de) * 2009-10-02 2011-11-15 Uster Technologies Ag Verfahren zum Festlegen einer Reinigungsgrenze auf einer Garnreinigungsanlage.
JP2014514225A (ja) 2011-03-16 2014-06-19 ウステル・テヒノロジーズ・アクチエンゲゼルシヤフト 繊維供試品の特徴づけ
DE102012102576A1 (de) 2012-03-26 2013-09-26 Maschinenfabrik Rieter Ag Verfahren zur Garnüberwachung
JP2013227155A (ja) * 2012-03-28 2013-11-07 Murata Machinery Ltd 糸欠陥分類装置及び糸巻取機
WO2013185245A1 (de) 2012-06-11 2013-12-19 Uster Technologies Ag Charakterisierung von regelmässigen ereignissen in einem länglichen textilen prüfgut
JP2015525347A (ja) 2012-06-11 2015-09-03 ウステル・テヒノロジーズ・アクチエンゲゼルシヤフト 長繊維の試験材の品質の比較
WO2013185247A1 (de) 2012-06-11 2013-12-19 Uster Technologies Ag Ortsbezogene charakterisierung der qualität eines länglichen textilen prüfgutes
WO2013185249A1 (de) 2012-06-11 2013-12-19 Uster Technologies Ag Bewertung einer mutmasslichen reinigung eines länglichen textilen prüfgutes
WO2013185248A1 (de) 2012-06-11 2013-12-19 Uster Technologies Ag Vergleich der qualitäten von länglichen textilen prüfgütern
WO2014107817A1 (de) 2013-01-09 2014-07-17 Uster Technologies Ag Ermittlung von fehlerursachen in einem produktionsprozess eines länglichen textilen gebildes
CZ306820B6 (cs) * 2015-11-03 2017-07-26 Rieter Cz S.R.O. Způsob justace pracovního místa a čističe příze nebo snímače kvality příze na textilním stroji vyrábějícím přízi
US20190137382A1 (en) 2016-05-04 2019-05-09 Uster Technologies Ag Monitoring Contamination in a Stream of Fiber Flocks
CZ2016607A3 (cs) * 2016-09-29 2018-05-02 Rieter Cz S.R.O. Způsob sledování příze na pracovním místě textilního stroje a textilní stroj k jeho provádění
JP2019137537A (ja) * 2018-02-14 2019-08-22 村田機械株式会社 クリアリングリミット設定装置及び糸巻取機
CN113396252B (zh) * 2019-01-31 2024-03-15 乌斯特技术股份公司 针对异物优化纺纱过程

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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102008037758A1 (de) 2008-08-14 2010-02-18 Oerlikon Textile Gmbh & Co. Kg Verfahren zur Qualitätsüberwachung eines längsbewegten Garnes an einer Arbeitsstelle einer Kreuzspulen herstellenden Textilmaschine
DE102019116475A1 (de) * 2019-06-18 2020-12-24 Saurer Spinning Solutions Gmbh & Co. Kg Optimierung des Betriebes einer Spinnmaschine
EP3760772A1 (de) 2019-06-18 2021-01-06 Saurer Spinning Solutions GmbH & Co. KG Optimierung des betriebes einer spinnmaschine
US11643757B2 (en) 2019-06-18 2023-05-09 Saurer Spinning Solutions Gmbh & Co. Kg Optimization of the operation of a spinning machine
DE102022004857A1 (de) 2022-12-22 2024-06-27 Oerlikon Textile Gmbh & Co. Kg Verfahren zum Ermitteln der Spulenqualität einer Sammelspule

Also Published As

Publication number Publication date
JPH10298836A (ja) 1998-11-10
JP4117583B2 (ja) 2008-07-16
CN1198486A (zh) 1998-11-11
DE59809009D1 (de) 2003-08-21
EP0877108A1 (de) 1998-11-11
US6374152B1 (en) 2002-04-16
CN1154758C (zh) 2004-06-23

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