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High Performance Processing of Distributed Acoustic Sensing Data: Turning Optical Fibres into Massively Parallel Microphone Arrays

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  • Full or part time
    Dr A Garcia-Fernandez
    Prof S Maskell
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

Distributed Acoustic Sensing (DAS) offers great potential to extract pertinent information from the environment close to optical fibres, turning each 50km long fibre into 5000 (or more!) acoustic microphones. This has significant commercial utility in contexts that include monitoring roads and railways as well as protecting critical infrastructure (e.g. gas pipelines and nuclear power stations). A market-leading DAS company has a novel ability to use coherent processing to maximise the ability to extract such information. This provides an opportunity to develop a novel Bayesian signal processing chain that fully exploits the novel sensing capability.

This PhD will focus on developing a high performance variant of this processing chain using state-of-the-art techniques such as particle filters, Convolutional Neural Networks etc. The focus will be on a subset of: detection, localisation (e.g., using beamforming), tracking and classification of anomalies (e.g., the sounds of people walking, digging, driving, etc) as well as long term condition monitoring and simulation (both for assessment of performance and generation of training data for machine learning algorithms). Note that since the data-rates involved are high, it is anticipated that software will need to be developed with a view to implementation on a small cluster of GPUs or similar. The specific focus of the PhD will be chosen to be well matched to the skills of the student (as well as to the company’s needs).

To apply for this opportunity, please visit: https://www.liverpool.ac.uk/study/postgraduate-research/how-to-apply/

Funding Notes

This PhD is industry-funded for four years. The student stipend will be £19,277 per year (this is the EPSRC stipend plus a top-up equal to that normally associated with an EPSRC ICASE award). Extensive funding for travel (both to visit the industrial partner and to attend international conferences) is also included. This PhD also includes funding for PhD fees (for UK and EU students only). Extensive interaction with the industry partner, who have data from these novel DAS systems, is anticipated. The start date is to be agreed, but could be immediate.



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