DSpace Collection:
http://theses.ncl.ac.uk/jspui/handle/10443/1522
2024-03-28T09:38:30ZTowards Automatic Photo-Identification of Cetaceans: A Fine-Grained, Few-Shot Problem in Marine Ecology
http://theses.ncl.ac.uk/jspui/handle/10443/5981
Title: Towards Automatic Photo-Identification of Cetaceans: A Fine-Grained, Few-Shot Problem in Marine Ecology
Authors: Trotter, Cameron
Abstract: Understanding the health of Earth’s ecosystems is imperative for the future safeguarding
of our planet and its inhabitants. One of the most common tools utilised by researchers
to develop their understanding of an area’s health is indicator species, organisms whose
abundance or absence in a system reflects overall environmental health. Cetaceans such as
dolphins, porpoises, and odontocetes (toothed whales) are excellent indicator species given
their status as top predators, allowing for the monitoring of risks to marine environments,
such as offshore wind farm development or commercial fishing activity.
Cetacean monitoring is frequently performed using capture-recapture surveys, through
which researchers record the presence of individual animals to produce population estimates.
Photo-identification (photo-id) is one of the main non-invasive capture-recapture methods,
whereby image data containing the animals’ individually identifiable prominent markings
are captured. Upon survey completion these data are curated to produce a photo-id catalogue,
allowing for an abundance estimate to be generated and ecosystem health to be determined.
Catalogues are updated over time as more surveys are undertaken, new individuals are
encountered, and prominent markings change. Photo-id catalogue curation is traditionally
performed manually and can be extremely labour and cost intensive, especially for large
resident populations.
This thesis details a framework for automatic photo-id catalogue matching based on
unprocessed field imagery via a pipeline of computer vision models. The creation of a
photo-id catalogue containing cetaceans resident in the waters of Northumberland, UK,
is first outlined. The development of a coarse-grained dorsal fin detector and the use of
post-processing techniques to aid downstream identification is then examined. Next, the
created photo-id catalogue is utilised to facilitate the development of a model capable of finegrained, few-shot catalogue matching via latent space similarity, allowing for the flagging of
potentially uncatalogued individuals. At all stages, the developed techniques’ robustness to
spatio-temporal changes is evaluated, including their generalisability to multiple cetacean
species. The automation of photo-id data curation outlined in this thesis affords researchers
more time to work on application of their data, for example to inform mitigation and policy
change, rather than administration.
Description: Ph. D. Thesis2023-01-01T00:00:00ZMulti-objective torque control of switched reluctance machine
http://theses.ncl.ac.uk/jspui/handle/10443/5634
Title: Multi-objective torque control of switched reluctance machine
Authors: Dankadai, Najib Kabir
Abstract: The recent growing interest in Switched Reluctance Drives (SRD) is due to the electrification
of many products in industries including electric/hybrid electric vehicles, more-electric
aircrafts, white-goods, and healthcare, in which the Switched Reluctance Machine (SRM) has
potential prospects in satisfying the respective requirements of these applications. Its main
merits are robust structure, suitability for harsh environments, fault-tolerance, low cost, and
ability to operate over a wide speed range. Nevertheless, the SRM has limitations such as large
torque ripple, high acoustic noise, and low torque density. This research focuses on the torque
control of the SRD with the objectives of achieving zero torque error, minimal torque ripple,
high reliability and robustness, and lower size, weight, and cost of implementation.
Direct Torque Control and Direct Instantaneous Torque Control are the most common methods
used to obtain desired torque characteristics including optimal torque density and minimized
torque ripple in SRD. However, these torque control methods, compared to conventional
hysteresis current control, require the use of power devices with a higher rating of about 150%
to achieve the desired superior performance. These requirements add extra cost, conduction
loss, and stress on the drive’s semiconductors and machine winding. To overcome these
drawbacks, a simple and intuitive torque control method based on a novel adaptive quasi sliding mode control is developed in this study. The proposed torque control approach is
designed considering the findings of an investigation performed in this thesis of the existing
widely used control techniques for SRD based on information flow complexity.
A test rig comprising a magnet assisted SRM driven by an asymmetric converter is constructed
to validate the proposed torque control method and to compare its performance with that of
direct instantaneous torque control, and current hysteresis control methods. The simulation and
experimental results show that the proposed torque control reduces the torque ripple over a
wide speed range without demanding a high current and/or a high switching frequency. In
addition, It has been shown that the proposed method is superior to current hysteresis control
method in the sensorless operation of the machine. Furthermore, the sensorless performance of
the proposed method is investigated with the lower component count R-Dump converter. The
simulation results have also demonstrated the excellent controller response using the standard
R-Dump converter and also with its novel version developed in this thesis that needs only one
current sensor.
Description: PhD Thesis2022-01-01T00:00:00ZOptimal scheduling of Distributed Energy Resources connected to Electricity Distribution Networks using Robust Mixed-Integer Second Order Cone Programming
http://theses.ncl.ac.uk/jspui/handle/10443/5626
Title: Optimal scheduling of Distributed Energy Resources connected to Electricity Distribution Networks using Robust Mixed-Integer Second Order Cone Programming
Authors: Zografou Barredo, Natalia Maria
Abstract: Tackling climate change is a global emergency, driving the electricity sector to
go through rapid changes, including the increasing reliance on local generating
assets, called distributed energy resources (DER). DER range from onsite energy
storage systems, to gas or diesel generators, and renewable generators, but could
also include other forms of generation such as electric vehicles with vehicle-to-grid
capabilities. This PhD proposes a model to optimally schedule DER connected
to radial distribution networks, which can form an active distribution network or a
microgrid, aiming at delivering improvements in operational cost, security of supply
and environmental sustainability. This is mathematically formulated using robust
mixed-integer second-order cone programming. The proposed model takes into
account an accurate power flow model for radial networks and a robust approach
to deal with uncertainty in the market price, the electricity demand, the renewable
generation, and the time and duration of a scheduled interruption from the main grid
when DER form part of a microgrid. Computational experiments support the suitability
of the proposed model, in a number of case studies informed by real-world data
and operational scenarios. This research concludes the following. Firstly, that it is
important to account for detailed modelling of network losses in operational decisions
of such systems, as they profoundly affect both the cost and the network’s operating
state and conditions. Secondly, that the robust approach used in this thesis in order to
deal with uncertainty allows distribution system and/or microgrid operators to manage
trade-offs between the level of the aforementioned uncertainties they are willing to
tolerate, and the operational cost of network assets. Benefits of using the proposed
model include, reduction of the operational cost, and mitigation of technical constraint
violations in actual conditions. The proposed model can be used by a range of
stakeholders including, microgrid operators, distribution system operators, and DER
owners.
Description: Eng. D. Thesis.2022-01-01T00:00:00ZMulti-layer carbon fiber reinforced plastic characterization and reconstruction using eddy current pulsed thermography
http://theses.ncl.ac.uk/jspui/handle/10443/5451
Title: Multi-layer carbon fiber reinforced plastic characterization and reconstruction using eddy current pulsed thermography
Authors: Yi, Qiuji
Abstract: Carbon fibre composite materials are widely used in high-value, high-profit
applications, such as aerospace manufacturing and shipbuilding – due to their low
density, high mechanical strength, and flexibility. Existing NDT techniques such as
eddy current testing suffers from electrical anisotropy in CFRP (carbon fibre reinforced
plastics). Ultrasonic is limited by substantial attenuation of signal caused by the multilayer structure. The eddy current pulsed thermography has previously been applied for
composites NDE (non-destructive evaluation)such as impact damage, which has the
ability for quick and accurate QNDE(quantitative non-destructive evaluation)
inspection but can be challenging for detection and evaluation of sub-surface defects,
e.g., delamination and debonding in multiple layer structures. Developing QNDE
solutions using eddy current thermography for addressing subsurface defects evaluation
in multi-layer and anisotropic CFRP is urgently required.
This thesis proposes the application of eddy current pulsed thermography (ECPT) and
ECPuCT (eddy current pulse compression thermography) for tackling the challenges of
anisotropic properties and the multi-layer structure of CFRP using feature-based and
reconstruction-based QNDE and material characterisation. The major merit for eddy
current heating CFRP is the volumetric heating nature enabling subsurface defect
detectability. Therefore, the thesis proposes the investigation of different ECPT and
their features for QNDE of various defects, including delamination and debonding.
Based on the proposed systems and QNDE approach, three case studies are
implemented for delamination QNDE, debonding QNDE, conductivity estimation and
orientation inverse reconstruction using the two different ECPT systems and features,
e.g., a pulse compression approach to increase the capability of the current ECPT
system, the feature-based QNDE approach for defect detection and quantification,
and reconstruction-based approach for conductivity estimation and inversion. The
three case studies include 1) investigation of delamination with different depths in terms
of delamination location, and depth quantification using K-PCA, proposed temporal
feature-crossing point feature and ECPuCT system; 2) investigation of debonding with
different electrical and thermal properties in terms of non-uniform heating pattern
removal and properties QNDE using PLS approaches, impulse response based features
Description: Ph. D. Thesis.2021-01-01T00:00:00Z