Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Intelligent Computer Vision System for Analysis and Characterization of Yarn Quality

Version 1 : Received: 29 November 2022 / Approved: 30 November 2022 / Online: 30 November 2022 (10:09:03 CET)

A peer-reviewed article of this Preprint also exists.

Pereira, F.; Macedo, A.; Pinto, L.; Soares, F.; Vasconcelos, R.; Machado, J.; Carvalho, V. Intelligent Computer Vision System for Analysis and Characterization of Yarn Quality. Electronics 2023, 12, 236. Pereira, F.; Macedo, A.; Pinto, L.; Soares, F.; Vasconcelos, R.; Machado, J.; Carvalho, V. Intelligent Computer Vision System for Analysis and Characterization of Yarn Quality. Electronics 2023, 12, 236.

Abstract

The quality of yarn is essential in the control of the fabrics processes. There is some commercial equipment that measures the quality of yarn based on sensors, of different types, used for collecting data about some yarn characteristic parameters. The existing equipment, for the above-mentioned purpose, is characterized by its high size and cost, and for allowing the analysis of only few yarn quality parameters. Thus, this paper presents the development and results obtained with the design of a mechatronic prototype integrating a computer vision system that allows, among other parameters, the analysis and classification, in real time, of the hairs of the yarn using artificial intelligence techniques. The system also determines other characteristics inherent to the yarn quality analysis, such as: linear mass, diameter, volume, twist orientation, twist step, average mass deviation, coefficient of variation, hairiness coefficient, average hairiness deviation and standard hairiness deviation, as well as performs spectral analysis. A comparison of the obtained results with the designed system and a commercial equipment was performed validating the undertaken methodology.

Keywords

Yarn Mass Parameters; Artificial Intelligence; Image Processing; Machine Learning; Mechatronic Prototype

Subject

Engineering, Electrical and Electronic Engineering

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.