Analysis develops a digital twin model for textile machinery, indicating reliability improvements using temperature data.
The textile industry relies on high-speed rotating and thermally loaded equipment such as spinning frames, carding cylinders, and weaving looms. To enhance reliability and reduce unplanned stoppages, this study develops a digital twin model of textile machinery by integrating vibration, temperature, and degradation data. A multi-sensor acquisition system records real-time signals, while a physics-based rotor dynamic model and thermal model simulate machine behavior.
No takes yet. Share an insight, caveat, or question.
Khonturaev et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: