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Field
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analytics, anomaly detection, and embedded redundancy to enhance system resilience. Students will focus on creating adaptive algorithms and hardware implementations that enable real-time diagnostics and
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from motion blur, defocus, and imaging artefacts, which hinder accurate diagnosis. This project aims to restore image clarity by designing intelligent algorithms that recover fine anatomical details
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algorithms are used that allow a computer to process large data-sets and learn patterns and behaviours, thus allowing them to respond when the same patterns are seen in new data. This include 'supervised
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of diagnostic and prognostic algorithms. Electronic Prognostics Systems: Facilities equipped to assess the health and predict the remaining useful life of electronic components, supporting studies in electronic
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and misalignment, facilitating the development and validation of diagnostic and prognostic algorithms. Electronic Prognostics Systems: Facilities equipped to assess the health and predict the remaining
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PhD student will be trained by a team consisting of a project-specific PDRA as well as Prof. Ringe and Dr Lomonosov (senior research associate in the group), towards gaining technical independence in
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prototype/demonstrator of a low-cost smart sensor. To develop an efficient algorithm to process the vibration signals locally and to develop the firmware to be embedded within the sensor node. To validate
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) of high-value critical assets. Through this PhD research, algorithms and tools will be further improved and developed, validated and tested. It is expected that combining the domain knowledge and the
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Supervisory Team: Prof. Gennaro Scarselli PhD Supervisor: Gennaro Scarselli Project description: Carbon fiber reinforced plastics (CFRPs) are popular in engineering applications due
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Supervisory Team: Dr N.C. Townsend, Prof A. Murphy PhD Supervisor: Nick Townsend Project description: In this PhD project you will explore novel wave energy harvesting systems for maritime robotic