10 citations · 14 across the 4 of their papers we have counts for
4 papers
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…
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…
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…
Real-Time Damage Detection in Fiber Lifting Ropes Using Lightweight Convolutional Neural Networks
Tuomas Jalonen, Mohammad Al-Sa'd, Roope Mellanen +2
The health and safety hazards posed by worn crane lifting ropes mandate periodic inspection for damage. This task is time-consuming, prone to human error, halts operation, and may…