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Field
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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downtime and operational costs. Traditional condition monitoring approaches often face challenges in accurately detecting early-stage faults, especially in the presence of highly impulsive signals
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using thermographic Non-Destructive Testing (NDT), a critical method for ensuring aircraft safety and reliability. NDT is increasingly vital in the aviation sector, enabling the detection of hidden
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processing power of a novel photonic integrated circuit architecture [Heuck2023]. This includes studying the effects of optical loss and decoherence and methods to overcome these by error detection and
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detection and classification algorithms using measured and/or simulated data, such as current pulses from cable faults (breakdown), partial discharges and external noise. In addition to being part of
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maintenance (O&M) practices for wind turbines, with a focus on fault types that degrade turbine and plant-level power performance. Identifying key signals or performance indicators related to asset health and
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
generate vast amounts of operational and maintenance data, much of it remains fragmented and underutilized. Unlocking insights from this unstructured data could enable earlier fault detection, improved
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parameters by trial-and-error, leading to a time consuming sub-optimal selection. In the domain of high precision machining, tools are prematurely discarded to avoid the risk of costly non-conformities
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This PhD at Cranfield University explores the development of resilient, AI-enabled electronic systems capable of detecting faults and autonomously recovering from failures in real time. The project
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Fuel Rig with Five Degradation Faults: Simulates various degradation scenarios in unmanned aerial vehicle (UAV) fuel systems, enabling research into fault detection, isolation, and prognostics. Machine