Whether in textile cleaning, in the manufacture of clothing or in recycling, there are many application situations in which it is important to know what material a textile is made of. For example, while the color and shape of a textile can be easily recognized with the human eye, the material cannot be determined without additional help. 


Textile materials can be divided into natural fibers (including cotton, silk, wool) and chemical fibers (including polyester, viscose, elastane). Chemical fibers are usually cheaper than natural fibers and are therefore used in many counterfeits. Chemical fibers are also often illegally mixed with natural fibers, which can degrade the quality of a textile. 


With the InProSens sensor systems you can check in a few seconds and at any location whether a textile is the preferred material. The textile is not damaged in the process, since only a spectrum has to be recorded with the  sensor system.

Using a measured spectrum, it can be predicted which material the textile is made of. A prediction model is used for this, in which over 100 calibration measurements have been integrated as a data basis.


The prediction model for textiles currently includes 10 materials:

  • Cotton
  • Silk
  • Nylon
  • Wool
  • Polyester
  • Acetate
  • Polyurethane
  • Viscose
  • Jute
  • Elastane

Upon request, the model can be customized with additional materials.  

In the graphic with the calibration data you can see that each textile material has an individual spectrum. The point cloud also shows how big the differences are between the individual spectra. The closer two materials are to each other in the point cloud, the more similar the materials are.


If a measured spectrum corresponds to one of these calibration spectra, it can be predicted with a certain probability which textile material the present one is. 


Further information on the prediction model is available in the PDF file that can be downloaded here.

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