WO2014085939A1

WO2014085939A1 - Determining the hairiness lengths on a yarn

Info

Publication number: WO2014085939A1
Application number: PCT/CH2013/000198
Authority: WO
Inventors: Kay-Uwe Kirstein; Rafael Storz; Thomas Nasiou
Original assignee: Uster Technologies Ag
Priority date: 2012-12-07
Filing date: 2013-11-12
Publication date: 2014-06-12

Abstract

The invention relates to a method for determining the hairiness length distribution of a yarn, in which the hairiness lengths are measured (602) on the yarn. Results of the hairiness length measurements are stored. Categories of hairiness lengths are automatically formed (603) as a function of the results of said hairiness length measurements. A frequency distribution of the measured hairiness lengths is issued (604) in the form of a diagram based on the categories formed automatically. This flexible categorisation also allows the hairiness length distribution to be determined for yarn types that are non-typical.

Description

HAIR LENGTH DETERMINATION ON ONE YARN

AREA OF EXPERTISE

The present invention is in the field of textile quality control. It relates to a method and a device for determining the Haarigkeitslängenverteilung a yarn, according to the preambles of the independent claims. Such methods and devices are typically used in a textile laboratory.

STATE OF THE ART

In staple yarns spun from many fibers, individual fibers are not fully integrated into the actual yarn hull. They partially protrude from the

Yarn hull out what is called the hairiness of the yarn. The hairiness is an important yarn property, which is why the textile industry has a great interest in their reliable and reproducible determination and classification. Many methods and devices for determining the hairiness of yarns are known. Such a device distributes the present applicant under the name USTER ^® ZWEIGLE HL400. This device is in

Application Manual "USTER ^® ZWEIGLE HL400 Application Handbook", Uster Technologies AG, June 201 1, and described in WO 2011/153650 A1. It is equipped with an optoelectronic Garnsensoreinrichtung. It is the moving along its longitudinal direction yarn in transmitted light on a two-dimensional Imaging is used to determine a frequency distribution of hair length lengths, and the protruding fibers are classified into seven fixed hair length classes, namely 1, 2, 3, 4, 6, 8 and 10 mm Hair length classification has been adopted for compatibility reasons with older hair length measuring devices (Zweigle G565, G566 and G567 and USTER ^® ZWEIGLE HT5) and is suitable for many common yarn types, in particular ordinary ring spun yarns, suitable. The number of fibers per 100 m is given for each class and displayed in a histogram.

DE-199'24'840 A1 shows a finer hair length classification in which each hair length class has a class width of 0.1 mm. From the resulting frequency density distribution, different hairiness parameters are calculated. In a similarly refined manner, the following article presents frequency density distributions for hair length lengths and calculates a tissue simulation from them: Ozkaya YA, Acar M, Jackson MR: "Hair density distrubution profile to evaluate yarn hairiness and is application to fabric simulation", Journal of the Textile Institute, Vol. 98, No. 6, 2007.

SUMMARY OF THE INVENTION It is an object of the present invention to further improve the known method and apparatus. In particular, a higher resolution should be achieved and user-friendliness increased.

These and other objects are achieved by the method according to the invention and the device according to the invention, as defined in the independent patent claims. Advantageous embodiments are given in the dependent claims.

The inventive improvement consists in the dissolution or flexibilization of the hitherto rigid hair length classes. The invention thus accomplishes a

Paradigm shift from classification, that is, assignment of results into predefined classes, to categorization, ie the automatic formation of new categories based on the results obtained or expected. The categories are formed automatically, preferably by being adapted during the measurements to the already existing measurement results. A set of several category systems may be specified, one of which is then automatically selected. The choice of a suitable category system can due to the type of yarn concerned, the type of yarn can be automatically detected or entered manually.

Accordingly, in the method of the present invention for determining the hairiness length distribution of a yarn, hair length lengths are measured on the yarn, and a frequency distribution of the measured hair length is output. Results of the hairiness length measurements are stored. Categories of hair length are automatically formed depending on the results of hair length measurements. The frequency distribution is output in the form of a diagram based on the automatically formed categories.

At least the step of automatically forming categories of hair length is carried out in the method of the invention by a computer or similar device.

The hair length is preferably measured by moving the yarn along its longitudinal direction through a yarn sensor device and along the

For example, the graph may be a histogram or a histogram corresponding line graph.

In one embodiment, the automatic formation of the categories takes place on the basis of already measured hair length lengths. It can during the measurements of the

Hair length lengths running the automatic formation of the categories done and a respectively updated diagram are output.

The automatic formation of the categories may be due to input of yarn data or due to an automatic determination of yarn data.

After the output of the diagram based on the automatically formed categories, an operator is given the opportunity to comment on the diagram. The operator comments by means of an input to the diagram. The categories are preferably automatically adjusted to the opinion, and the fitted chart is output. The hair length lengths are preferably measured optoelectronically by moving the yarn along its longitudinal direction through an optoelectronic yarn sensor device, the optoelectronic yarn sensor device successively taking a plurality of images of the yarn and from the images, preferably from each individual image from the plurality of images

Image processing hairiness lengths are evaluated. The number of in one

Measurement series taken and evaluated images is z. Between 10 and 10,000 and preferably between 100 and 1000.

The device according to the invention for determining the hair length distribution of a yarn includes a yarn sensor device for measuring hair length on the yarn, an evaluation device for evaluating output signals of the yarn

Yarn sensor device, an output device for outputting a frequency distribution of the measured hair length and a control device for controlling the

Contraption. The evaluation device and the control device are set up to carry out the method according to the invention described above.

Compared with the rigid classes according to the prior art, the invention has the advantage that with high resolution, the Haarigkeitslängenverteilung can also be determined by those yarns that are out of the ordinary, such as compact yarns or air-spun yarns. Thus, even with such yarns, the manufacturing processes can be better monitored due to the particular Haarigkeitslängenverteilung.

As used herein, the term "hair length" generally includes both the length of the stretched fiber and the length of the projection of the fiber, possibly curved and / or skewed, in a direction perpendicular to the longitudinal direction of the yarn, ie, the maximum distance of the yarn Fiber from the yarn surface. In one and the same application of the invention but applies only one of the above meanings. TITLE OF DRAWINGS

The invention will be explained in detail with reference to the schematic drawings.

FIG. 1 shows a device according to the invention in a perspective view

View.

FIG. 2 schematically shows an optoelectronic Gamsensoreinrichtung in

Cross-section.

Figure 3 shows a histogram as may result from a method known from the prior art.

Figures 4 and 5 show diagrams as they may result from the inventive method.

FIGS. 6-8 are flowcharts of three embodiments of the present invention

inventive method.

FIG. 9 shows a flowchart of a variant of the invention

Process.

EMBODIMENT OF THE INVENTION

Figure 1 shows from the outside a device 1 for determining the

Hair length distribution of a yarn 9. One recognizes in this illustration a substantially cuboid housing 1 1, various yarn guide elements 12.1 -12 for guiding the yarn 9, a sensor cover 16 for an optoelectronic

Yarn sensor device 3 and a roll cover 17 for a yarn conveying device 1 The optoelectronic yarn sensor device 3 measures at least one parameter of the yarn 9, in particular the length of fibers ("hairs") protruding from the yarn 9.

FIG. 2 shows a schematic representation of the optoelectronic yarn sensor device 3. The optoelectronic yarn sensor device 3 includes a lighting unit and an imaging unit. The illumination unit has at least one light source 31 and one illumination optics 32. As a light source 31 z. As a light emitting diode (English light emitting diode, LED) can be used. The light source 31 transmits electromagnetic radiation in the visible, infrared and / or ultraviolet

Spectral range, which is summarized in this document for the sake of simplicity by the term "light." The illumination optics 32 collimates that of the

Light source 31 emitted light on a portion of the yarn 9. Preferably, the Köhl ersehe illumination is used, which is well known from microscopy and will not be discussed here. The imaging unit has a

Imaging optics 33 and an optoelectronic image sensor 34. The imaging optics

33 images the illuminated section of the yarn 9 onto the image sensor 34. The image sensor

34 is preferably a two-dimensional image sensor 34 having a multiplicity of picture elements (pixels) arranged in the form of a matrix. Such image sensors 34 are commercially available in the form of integrated optoelectronic components in various technologies, for example, from digital cameras well known and widely used. Alternatively, as the image sensor 34, a likewise known one-dimensional line sensor with a multiplicity of pixels which are arranged on a straight line perpendicular to the yarn longitudinal direction can be used. For the sake of simplicity, these are

Illumination optics 32 and the imaging optics 33 shown in Figure 2 as simple lenses; Of course, however, more complex optical systems can be used which, in addition to lenses, contain further optical elements such as diaphragms or filters. The image is preferably in transmission, d. H. without inserted yarn 9, the light source 31 is illuminated on the image sensor 34, and when yarn 9 is inserted, it shadows at least part of the light. The yarn 9 is drawn in this schematic representation as a yarn body 91 with a circular cross-section, from which individual fibers ("hairs") 92 protrude essentially radially outward

Longitudinal axis 90 of the yarn 9, an optical axis 30 of the optoelectronic

Garnsensoreinrichtung 3 does not intersect, but is spaced therefrom, for example. By a distance of a = 2-6 mm and preferably by about a = 4 mm. This offset a is based on the assumption that (at least when averaging over a certain length of yarn is performed), the yarn 9 is rotationally symmetric and therefore the hair length values to be measured along the circumference of the yarn are the same. If this assumption of symmetry is correct, then only one half space 93 needs to be considered, and a half space 94 complementary thereto can be disregarded. In the considered half space 93 For this the hairiness can be examined better, ie with greater resolution. The two half-spaces 93, 94 are separated by a plane which the

Yarn longitudinal axis 90 and parallel to the optical axis 30 extends. FIG. 3 shows a result of hair length determination in the form of a histogram 4 ', which is a result of a prior art method. Along a horizontal axis 41 'of the histogram 4' hair lengths in millimeters are plotted, by a device 1 similar device through

Image processing are determined. The hairiness lengths determined are classified in the example of FIG. 3 into the seven classes 1, 2, 3, 4, 6, 8 and 10 mm customary in the prior art. For each of these classes you get after examining a particular

Yarn length, eg 100 m, one frequency (number). The relative frequency density is plotted along a vertical axis 42 'of the histogram 4'. Thus, the area of the rectangles 43 'drawn as columns corresponds to the respective frequency.

It can be seen that the histogram 4 'of FIG. 3 contains only little information about the examined yarn 9. This is due to the fact that only short fibers 92 (see FIG. 2) appear to protrude from the yarn 9 examined, so that virtually no fibers were counted in the classes with hair length of more than 2 mm. This can be z. B. be the case with air-spun yarns. A verification of the expected exponential decay of the

Frequencies with increasing hairiness length are only possible on the basis of the two classes 1 mm and 2 mm, as well as no further numerical evaluations. Here, the present invention provides a remedy. It leaves the conventional, rigid classification scheme, as shown in Figure 3. Instead, it makes new categories of

Hair length, depending on the respective measurement results.

FIG. 4 shows a histogram 4 as a result of the method according to the invention. The hair length categories are automatically chosen so that useful, statistically significant numbers of fiber lengths occur in a majority of the categories. In the embodiment of Figure 4, eight categories for the hair length 0.3, 0.6, 0.9, 2.4 mm were formed. The number of categories may be any natural number, but is preferably between 5 and 20. From the statistics, rules of thumb are known for calculating the number of categories that determine the number of measurements and if necessary also consider the dispersion. The widths of each category can be the same or different. In the histogram 4, results of further evaluations can be drawn in, for example a fit curve 45 calculated for the frequencies in the categories by means of a compensation calculation. Experience has shown that the frequency drops exponentially with the length of the hair, so that the fit function for the compensation calculation

where H is the relative frequency density, L is the hair length and H ₀ and L _{e are} the fit parameters.

Results of several series of measurements on different yarns or on the same yarn can be displayed in a single histogram 4, for example by means of adjacent columns. It is advantageous to graphically differentiate the symbols for the different measurement series, for. B. by means of different colors, fill patterns, line types, etc.

The result of the method according to the invention does not necessarily have to be a histogram 4. FIG. 5 shows as an alternative a line diagram 5 which can result from the method according to the invention. These are again the

Hairiness lengths along a horizontal axis 51 plotted while along a vertical axis 52, the frequencies are plotted. Two lines 53, 54 represent the results for different yarns, the first line 53 substantially corresponding to the histogram shown in FIG. More than two results could be entered in the same diagram 5, be it from series of measurements on different yarns or on the same yarn. Preferably, graphically different symbols are used for this purpose, eg. B. different line types, colors, point symbols etc.

The diagram 4, 5 can be output on an output unit of the device 1. The output unit is not shown in FIG. 1 because such output units are known per se. It can be designed as a screen, as a printer or in some other way. It may be integrated into the device 1 or be part or peripheral device of a computer connected to the device 1. If the vertical axis 42, 52 of the histogram 4 according to Figure 4 or the

Line graph 5 is divided logarithmically according to Figure 5, then the fit curve 45 and the lines 53, 54 are approximately straight lines with negative slopes. Such and other representations of the frequency distribution are also encompassed by the invention.

A first embodiment of the method according to the invention is shown in the flow chart of FIG. As a starting point 601 serve predetermined standard classes for the hair length, as they are known from the prior art and shown in Figure 3. Hairiness measurements are automatically made 602 on the yarn 9 being tested. After one measurement or several measurements 602, the predetermined classes are automatically adapted to the measurement results 603, whereby new hair length categories are formed. The adaptation 603 is preferably carried out such that the following two criteria are met simultaneously:

(a) In no discarded category (that is, not shown in Diagram 4, 5) may the frequency (relative or extrapolated to a particular yarn length)

Number exceeds a predetermined first threshold; and

(b) In the category still assigned to the largest hair length, the frequency or number (relative or extrapolated to a certain yarn length) must exceed a predetermined second threshold which is less than or equal to the first threshold value.

In addition, specifications for the number and / or width of the categories can be followed. It can, for. For example, a certain number or a lower and an upper limit for the number of categories, and / or a certain width or a lower and upper limit for the width of the categories can be specified.

After adjustment, the diagram 4, 5 with the adjusted

Hairiness length categories and the ones entered therein, from the measurements

604 issued. The output 604 is preferably online, d. H. while another measuring operation 602 is running, on a display unit such. B. a screen.

Following the output 604 of the diagram 4, 5, a decision is made 605 as to whether further measurements 602 should be carried out. This decision 605 can automatically, for example, depending on whether a predetermined minimum yarn length has been examined or not. Alternatively, the decision 605 may be made by an operator input. Depending on decision 605, further measurements 602 are made or the process is terminated. In the latter case, the last output 604 displays the definitive diagram 4, 5.

FIG. 7 shows a second embodiment of the method according to the invention. On the examined yarn 9 hairiness measurements are carried out 701. A

The operator is required to enter information on the yarn 9 to be tested before, during, or during measurements or measurements 702. Such information may concern the following aspects:

• History of the yarn 9. Hairiness may have a role to play

which raw materials the yarn 9 has been made and which

Processing processes it has gone through.

• Presence of the yarn 9. The present state of the yarn 9 can be determined by

Parameters such as yarn count, non-uniformity, foreign substances, moisture content, etc. are characterized. Some of these parameters may be known. They can be related to the expected hairiness.

• future of the yarn 9. The intended use of the yarn 9 may be a

Indicate the expected hairiness.

The inputs 702 may be assisted by an automatic wizard known from the installation of software and other software applications. Based on the entered yarn data, the hairiness length categories become

set automatically 703. The rules required to define 703 can be stored in advance in a storage unit. It is also possible to design the device 1 so intelligently that it itself prepares and learns such rules based on previous measurements 701. Finally, a graph 4, 5 is output with the automatically determined categories 704 representing the measurement results.

A third embodiment of the method according to the invention is shown in FIG. In turn, once again hairiness measurements on the yarn 9 are carried out 801. Yarn data, as manually entered in the second embodiment, is automatically determined 802 based on the measurement results. Such automatic determination 802 of yarn data may include the measured hairiness and / or other measured yarn parameters, such as the yarn count. Yarn count or unevenness

consider. It is preferably based on predetermined rules.

Subsequently, due to the automatically determined yarn data, the

Hairline length categories are automatically set 803. This setting 803 is done as described for the second embodiment. Also analogous to the second embodiment, a histogram with the automatically determined categories is output 804.

FIG. 9 shows a variant of the method according to the invention. The inventive method is carried out according to any embodiment, for example. According to one of the embodiments according to Figures 6-8. This always results in an output 901 of the frequency distribution in the form of a diagram 4, 5 based on the automatically formed categories. An operator is asked by an output

902, whether she wants to comment on the hairiness length categories. If not, the process continues.

Otherwise, the operator gives his opinion about known per se

Input means such as a keyboard, a computer mouse or a touch screen

903. Opinion 903 may be provided with a graphical user interface associated with the input means. Opinion 903 may be, for example, These may be relative (i.e., incremental) or absolute

Hair length categories are adjusted 904 according to Opinion 903. Adaptation 904 is preferably automatic. The stored measurement results are output 901 in a further adapted diagram. The operator may be given the opportunity 902 to comment on the further diagram 903. The loop is repeated until no more statement 903 is desired. The latest issue 901 displays the definitive diagram. Prerequisite for all four embodiments described above is that the

Measurement results should be stored as possible without loss of information to their

Further processing, d. H. the formation of hairiness length categories. Ideally, the raw data of the measurements, i. H. Each measured fiber length or the length of the projection of the fiber in a direction perpendicular to the yarn longitudinal direction stored. A loss of information, a subsequent categorization

could, for example, occur if the measurement results were equally divided into predefined classes and only the number of measurements in each class would be stored. Such a procedure is only allowed in the method according to the invention if the classes are so fine, d. H. narrow are that the formation of new categories by merging several classes is possible.

Of course, the present invention is not limited to those discussed above

Limited embodiments. In particular, the three embodiments of FIGS. 6-8 can be combined with each other. With knowledge of the invention, the skilled person will be able to derive further variants, which also belong to the subject of the present invention, as defined in the independent patent claims.

LIST OF REFERENCE NUMBERS

1 device

1 1 housing

12.1-12.5 Guide elements for the yarn

16 sensor cover

17 Roller cover

18 Conveyance instructions

3 optoelectronic yarn sensor device

30 optical axis of the yarn sensor device

31 light source

32 illumination optics

33 imaging optics

34 image sensor

4 histogram

41 horizontal axis

42 vertical axis

43 pillar

45 fit curve

5 line chart

51 horizontal axis

52 length axis

53, 54 lines

9 yarn

90 yarn longitudinal axis

91 yarn hull

92 yarn hairs

93, 94 Half spaces a Axial offset between optical axis and yarn longitudinal axis

Claims

PATENT CLAIMS 1. Method for Determining Hair Lengths Distribution of a chamois (9), measuring hair length on the yarn (9) (602, 701, 801) and

a frequency distribution of the measured hair length is output (604, 704, 804, 901),

characterized in that

Results of hair length measurements (602, 701, 801) are stored, categories of hairiness lengths depending on the results of the hairiness measurements

Hair length measurements (602, 701, 801) are made automatically (603, 703, 803) and

the frequency distribution is output in the form of a graph (4, 5) based on the automatically formed categories (604, 704, 804, 901).

2. The method of claim 1, wherein the diagram (4, 5) is a histogram (4) or a histogram corresponding line diagram (5).

3. The method according to any one of the preceding claims, wherein the automatic

Formation (603) of the categories based on already measured hair length is done.

The method of claim 3, wherein during the measurements (602) the

Hair Lengths The automatic formation (603) of the categories is done and an updated chart is output (604).

5. The method according to any one of the preceding claims, wherein the automatic

Formation (703) of categories based on previously entered (702)

Garndaten takes place.

A method according to any one of claims 1-4, wherein the automatic formation (803) of the categories is based on automatic determination (802) of yarn data.

Method according to one of the preceding claims, wherein after the output (901) of the graph (4, 5) based on the automatically formed categories an operator has the opportunity (902) to comment on the graph (4, 5) (903 ), the operator comments (903) by means of an input to the diagram (4, 5), the categories are adapted to the statement (903) and the adapted diagram is output (901).

The method of claim 7, wherein the adaptation (904) of the categories to the

Opinion (903) is automatic.

9. The method according to any one of the preceding claims, wherein the Haarigkeitslängen be measured opto-electronically by

the yarn (9) along its longitudinal direction by an opto-electronic

Yarn sensor device (3) is moved,

the optoelectronic yarn sensor device (3) successively receives a plurality of images of the yarn (9) and

from the images, preferably from each individual image from the plurality of images, hairiness lengths are evaluated by means of image processing.

10. The method of claim 9, wherein the number of in a series of measurements

recorded and evaluated images between 10 and 10Ό00 and

preferably between 100 and 1000.

11. Device (1) for determining the Haarigkeitslängenverteilung a yarn (9), including

a yarn sensor device (3) for measuring hair length on the yarn (9), an evaluation device for evaluating output signals of

Yarn sensor device (3),

an output device for outputting a frequency distribution of the measured hair length lengths and

a control device for controlling the device (1),

characterized. the evaluation device and the control device are set up to carry out the method according to one of the preceding claims.