Journal of
eISSN: 2574-8114
Submit manuscript...
Research Article Volume 12 Issue 4
Development of an online detection system for ring-spun fine yarns using capacitive sensors
Haoyu Liu, Wei Xie, Senyang Liu, Shangyong Zhang, Jun Chen
Received: September 15, 2026 | Published: September 29, 2026
Citation: Liu H, Xie W, Liu S, et al. Development of an online detection system for ring-spun fine yarns using capacitive sensors. J Textile Eng Fashion Technol. 2026;12(4):283-288. DOI: 10.15406/jteft.2026.12.00474
Abstract
An online yarn evenness detection system for ring-spun yarns using capacitive sensors was developed. Appropriate mounting brackets were designed for the sensors to ensure stable acquisition of yarn evenness data from the spinning frame during operation. In addition, algorithms were used to process the acquired yarn signals; thermal drift correction and signal filtering were essential for maintaining signal stability. The accuracy of the online evenness data output by the system was verified by comparison with measurements from a Uster evenness tester. The results showed that the piecewise linear representation method with 10 segments effectively reduced thermal drift in the yarn signals; after correction, the measurement accuracy improved by 12.01%, and the error decreased by 1.28%. For signal filtering, Gaussian filtering with σ = 2.1 was applied and performed well in processing yarn signals. Compared with the CV% obtained from the Uster evenness tester, the CV% obtained by the online system showed an average accuracy of 92.46% and an average error of 1.04%, indicating an overall improvement in the precision of the online evenness data.
Keywords: yarn evenness CV%, capacitive sensor, online detection, process optimization
©2026 Liu, et al. This is an open access article distributed under the terms of the, which permits unrestricted use, distribution, and build upon your work non-commercially.