3 papers
cs.LG2026
Real-Time Vibration-Based Bearing Fault Diagnosis Under Time-Varying Speed Conditions
Tuomas Jalonen, Mohammad Al-Sa'd, Serkan Kiranyaz +1
Detection of rolling-element bearing faults is crucial for implementing proactive maintenance strategies and for minimizing the economic and operational consequences of unexpected…
cs.LG2026
Dual-Domain Fusion for Semi-Supervised Learning
Tuomas Jalonen, Mohammad Al-Sa'd, Serkan Kiranyaz +1
Labeled time-series data is often expensive and difficult to obtain, making it challenging to train accurate machine learning models for real-world applications such as anomaly det…
cs.LG2026
Fusion of Quadratic Time-Frequency Analysis and Convolutional Neural Networks to Diagnose Bearing Faults Under Time-Varying Speeds
Mohammad Al-Sa'd, Tuomas Jalonen, Serkan Kiranyaz +1
Diagnosis of bearing faults is paramount to reducing maintenance costs and operational breakdowns. Bearing faults are primary contributors to machine vibrations, and analyzing thei…