Title:Characterization of Yarn Mass Parameters and Production Characteristics Using Optical Sensors, Capacitive Sensors and Image Processing
VOLUME: 2 ISSUE: 3
Author(s):Vitor Carvalho, Nuno Goncalves, Filomena Soares, Rosa Vasconcelos and Michael Belsley
Affiliation:University of Minho, Dept. Industrial Electronics, Campus de Azurem, 4800-058, Guimaraes, Portugal.
Keywords:Optical Sensors, Capacitive Sensors, Yarn Mass, Yarn Hairiness, Yarn Diameter, Yarn Production Characteristics,
Image Processing, Optical Signal Processing
Abstract:This paper describes a custom developed yarn parameterization system to characterize yarn diameter, mass and
hairiness. The system has been named YSQ (Yarn System Quality) and is based on capacitive and optical sensors generally
used to infer information about yarn quality. The designed sensor system is fully described. All data acquisition and
processing is performed using a DAQ board from National Instruments (USB-6251) and custom software developed in
LabVIEW®. Moreover it presents a solution based on image processing techniques to determine yarn mass parameters as
well as yarn production characteristics. A low cost solution based on a web-pc camera plus the optics of a low cost analog
microscope and a software tool based on IMAQ Vision from LabVIEW® were employed. Several tests were performed
and compared to other methodologies of yarn parameterization validating the proposed solution. The results support the
claim that this system can be an alternative solution to the traditional yarn testers, with several advantages (including: low
cost, low weight, low volume, easy maintenance and reduced hardware).
