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Joint Instantaneous Amplitude-Frequency Analysis of Vibration Signals for Vibration-Based Condition Monitoring of Rolling Bearings
Sulaiman Aburakhia, Ismail Hamieh, Abdallah Shami
Vibrations of damaged bearings are manifested as modulations in the amplitude of the generated vibration signal, making envelope analysis an effective approach for discriminating b…
Machine Learning for Pre/Post Flight UAV Rotor Defect Detection Using Vibration Analysis
Alexandre Gemayel, Dimitrios Michael Manias, Abdallah Shami
Unmanned Aerial Vehicles (UAVs) will be critical infrastructural components of future smart cities. In order to operate efficiently, UAV reliability must be ensured by constant mon…
On the Intersection of Signal Processing and Machine Learning: A Use Case-Driven Analysis Approach
Sulaiman Aburakhia, Abdallah Shami, George K. Karagiannidis
Recent advancements in sensing, measurement, and computing technologies have significantly expanded the potential for signal-based applications, leveraging the synergy between sign…
On the Peak-to-Average Power Ratio of Vibration Signals: Analysis and Signal Companding for an Efficient Remote Vibration-Based Condition Monitoring
Sulaiman Aburakhia, Abdallah Shami
Vibration-based condition monitoring (VBCM) is widely utilized in various applications due to its non-destructive nature. Recent advancements in sensor technology, the Internet of…
Similarity-Based Predictive Maintenance Framework for Rotating Machinery
Sulaiman Aburakhia, Tareq Tayeh, Ryan Myers +1
Within smart manufacturing, data driven techniques are commonly adopted for condition monitoring and fault diagnosis of rotating machinery. Classical approaches use supervised lear…
Machine Learning for Performance-Aware Virtual Network Function Placement
Dimitrios Michael Manias, Manar Jammal, Hassan Hawilo +4
With the growing demand for data connectivity, network service providers are faced with the task of reducing their capital and operational expenses while simultaneously improving n…