| Attributes | Values |
|---|
| rdf:type
| |
| Description
| - Yarn packing density is an important parameter in correlating the internal structure of the yarn to its final properties and performance. The current methods of determining the yarn packing density have three main drawbacks; they are labor dependent, they are time consuming, and they approximate many parameters of the fibers and the yarn. The current work utilizes the Chan-Vese (CV) segmentation model to detect the actual contours of the yarn and the fibers inside its cross-section. This algorithm allows the atomization of the process which reduces the time required for the analysis and makes it independent from the human element. The method also avoids the approximations involved in the traditional methods by calculating the actual areas of the fibers and the yarn which makes it more precise in determining the yarn packing density. A user friendly Graphical User Interface (GUI) was developed in the current work to read the images of the yarn cross-sections and utilize the CV algorithm for a quick image analysis and calculation of different yarn parameters such as the yarn's radial packing density, the yarn's effective diameter, and the yarn's effective packing density. One drawback of the introduced algorithm is its inability, with the given conditions, to consider the area of the fiber's wall as a part of the fiber's cross-sectional area which results in lower calculated values of packing density. These low values, however, were found to be comparable to the results of the traditional methods as these methods approximate the yarn cross-section to a bigger circle. The algorithm is described and tested with a 20 tex ring spun yarn of Lyocell fibers and the results were found to be in agreement with the reported values of such yarns.
- Yarn packing density is an important parameter in correlating the internal structure of the yarn to its final properties and performance. The current methods of determining the yarn packing density have three main drawbacks; they are labor dependent, they are time consuming, and they approximate many parameters of the fibers and the yarn. The current work utilizes the Chan-Vese (CV) segmentation model to detect the actual contours of the yarn and the fibers inside its cross-section. This algorithm allows the atomization of the process which reduces the time required for the analysis and makes it independent from the human element. The method also avoids the approximations involved in the traditional methods by calculating the actual areas of the fibers and the yarn which makes it more precise in determining the yarn packing density. A user friendly Graphical User Interface (GUI) was developed in the current work to read the images of the yarn cross-sections and utilize the CV algorithm for a quick image analysis and calculation of different yarn parameters such as the yarn's radial packing density, the yarn's effective diameter, and the yarn's effective packing density. One drawback of the introduced algorithm is its inability, with the given conditions, to consider the area of the fiber's wall as a part of the fiber's cross-sectional area which results in lower calculated values of packing density. These low values, however, were found to be comparable to the results of the traditional methods as these methods approximate the yarn cross-section to a bigger circle. The algorithm is described and tested with a 20 tex ring spun yarn of Lyocell fibers and the results were found to be in agreement with the reported values of such yarns. (en)
|
| Title
| - A METHOD FOR MORE ACCURATE EVALUATION OF YARN PACKING DENSITY
- A METHOD FOR MORE ACCURATE EVALUATION OF YARN PACKING DENSITY (en)
|
| skos:prefLabel
| - A METHOD FOR MORE ACCURATE EVALUATION OF YARN PACKING DENSITY
- A METHOD FOR MORE ACCURATE EVALUATION OF YARN PACKING DENSITY (en)
|
| skos:notation
| - RIV/46747885:24410/14:#0003844!RIV15-MSM-24410___
|
| http://linked.open...avai/riv/aktivita
| |
| http://linked.open...avai/riv/aktivity
| |
| http://linked.open...vai/riv/dodaniDat
| |
| http://linked.open...aciTvurceVysledku
| |
| http://linked.open.../riv/druhVysledku
| |
| http://linked.open...iv/duvernostUdaju
| |
| http://linked.open...titaPredkladatele
| |
| http://linked.open...dnocenehoVysledku
| |
| http://linked.open...ai/riv/idVysledku
| - RIV/46747885:24410/14:#0003844
|
| http://linked.open...riv/jazykVysledku
| |
| http://linked.open.../riv/klicovaSlova
| - Radial packing density; Yarn effective packing density; Yarn effective diameter; Yarn cross-sectional image analysis (en)
|
| http://linked.open.../riv/klicoveSlovo
| |
| http://linked.open...ontrolniKodProRIV
| |
| http://linked.open...in/vavai/riv/obor
| |
| http://linked.open...ichTvurcuVysledku
| |
| http://linked.open...cetTvurcuVysledku
| |
| http://linked.open...UplatneniVysledku
| |
| http://linked.open...iv/tvurceVysledku
| - Ibrahim, Sayed
- Neckář, Bohuslav
- Eldessouki, Mohamed
|
| http://localhost/t...ganizacniJednotka
| |
![[RDF Data]](/fct/images/sw-rdf-blue.png)
![[cxml]](/fct/images/cxml_doc.png)
![[csv]](/fct/images/csv_doc.png)
![[text]](/fct/images/ntriples_doc.png)
![[turtle]](/fct/images/n3turtle_doc.png)
![[ld+json]](/fct/images/jsonld_doc.png)
![[rdf+json]](/fct/images/json_doc.png)
![[rdf+xml]](/fct/images/xml_doc.png)
![[atom+xml]](/fct/images/atom_doc.png)
![[html]](/fct/images/html_doc.png)