The study introduces the Qatar University Dual-Machine Bearing Fault Benchmark dataset (QU-DMBF) containing sound and vibration data from two motors across 1080 conditions. It proposes a deep learning approach for sound-based fault detection, addressing limitations of vibration-based methods. Experiments on QU-DMBF show sound-based detection is more robust, independent of sensor location, and cost-effective while matching vibration-based performance. Why it matters: The new dataset and findings could shift the focus toward sound-based methods for more reliable and accessible predictive maintenance in industrial settings.
AMRC researchers Jide Oyebanji and Tarcisio Silvia will present papers at the MATLAB User Group Meeting in Abu Dhabi. Oyebanji's paper focuses on the 'Design of an Interactive TPMS Designing Desktop App' using MATLAB's numerical capabilities. Silvia's presentation discusses the optimization of MIMO active vibration controllers for electromechanical systems using MATLAB Simulink and Particle Swarm Optimization. Why it matters: The presentations showcase the application of computational tools like MATLAB in advanced materials research and digital engineering within the UAE.
Professor Marco Amabili, advisor at the Advanced Materials Research Center (AMRC), received the 'Cataldo Agostinelli and Angiola Gili Agostinelli' International Prize from the Lincei National Academy of Sciences of Italy. The award recognizes Prof. Amabili's research in mechanical vibrations, composite structures, and vascular biomechanics. He received the award in Rome from Nobel laureate Professor Giorgio Parisi. Why it matters: The recognition highlights the growing international visibility of UAE-based researchers and the increasing commitment of UAE institutions like TII to deep-tech research.
Video motion magnification amplifies subtle movements in video footage, making the imperceptible visible across various fields. In healthcare, it allows non-invasive monitoring of vital signs and micro-expressions. In engineering, it helps detect structural vibrations in infrastructure, while also being used in sports science, security, and robotics. Why it matters: The technology's ability to reveal hidden details has the potential to revolutionize diagnostics, monitoring, and decision-making in diverse sectors across the Middle East.
KAUST alumnus Hassan Al-Ismail (M.S. '14) leads a team at Saudi Aramco implementing vibrational wave modeling of 2D data. He returned to Saudi Arabia to work for Saudi Aramco after receiving his bachelor's degree and was later sponsored by the company to study at KAUST. Al-Ismail also emphasized the value of his time at KAUST for academic and personal growth. Why it matters: This highlights KAUST's role in developing talent for key industries in Saudi Arabia, particularly in areas relevant to energy and resource management.