Characterization of Yarn Mass Parameters and Production Characteristics Using Optical Sensors, Capacitive Sensors and Image Processing

Vitor      Carvalho; Nuno      Goncalves; Filomena      Soares; Rosa      Vasconcelos; Michael      Belsley

doi:10.2174/2210327911202030002

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).

Keywords: Optical Sensors, Capacitive Sensors, Yarn Mass, Yarn Hairiness, Yarn Diameter, Yarn Production Characteristics, Image Processing, Optical Signal Processing