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focuses on AI-driven fault diagnosis, predictive analytics, and embedded self-healing mechanisms, with applications in aerospace, robotics, smart energy, and industrial automation. Based
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, increasing costs and resource waste. This Ph.D. project aims to address these challenges by advancing fault diagnosis and prognosis (FDP) for complex mechatronic systems. Building on Supervisor Team's
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This PhD project will focus on developing, evaluating, and demonstrating an intelligent solution of diagnosis and prognosis for rotating machinery to enhance safety, reliability, maintainability and
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conditions affect billions of women globally, impacting everything from cardiovascular to mental health. Despite this, women face significant delays in diagnosis and treatment, often experiencing a trial-and
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of the challenges is fault detection and diagnosis of bearings subject to low (rotational) speed. As vibration/acoustic signals generated by the faults of low-speed bearings are very weak and often covered by strong