Real-Time Identification of Yarn Irregularities on DTY Machine Through Vibration Monitoring - Kurnia, Deni; Sutanto, Agus; Fakhrurroja, Hanif; Roni Wibowo, Nanang (Politeknik Negeri Lhokseumawe, 2024)
This paper presents an innovative real-time monitoring system for detecting yarn irregularities during the draw texturing process in DTY machine. The system uses advanced sensors to continuously measure vibration signals, which are then analyzed for anomalies. The system incorporates advanced sensors, controllers, and embedded software for monitoring the vibrations produced during the draw texturing process. Fast Fourier Transform (FFT) in LabVIEW converts these vibration signals into their frequency-domain representation. This helps identify anomalies that could indicate potential yarn irregularities. The results from the sensor data clearly indicate that amplitude values serve as a reliable measure for detecting yarn irregularities. For normal spindles, the amplitude ranges from 10.9 to 12.2 m/s², while abnormal spindles show significantly higher values, between 31.9 and 44.3 m/s². This distinction facilitates real-time classification of yarn quality. The system's ability to identify these amplitude variations promptly can significantly reduce waste and enhance quality control. Future developments will focus on integrating an intelligent early warning system that alerts operators immediately upon detecting irregularities, enabling quicker interventions and minimizing downtime.