Studies in Electrical Machines & Wind Turbines associated with developing Reliable Power Generation

The publications listed in date order in this document are offered for the Degree of Doctor of Science in Durham University and have been selected from the author’s full publication list. The papers in this thesis constitute a continuum of original work in fundamental and applied electrical science, spanning 30 years, deployed on real industrial problems, making a significant contribution to conventional and renewable energy power generation. This is the basis of a claim of high distinction, constituting an original and substantial contribution to engineering science

Approaches to hazard-oriented groundwater management based on multivariate analysis of groundwater quality

Drinking water extracted near rivers in alluvial aquifers is subject to potential microbial contamination due to rapidly infiltrating river water during high discharge events. The heterogeneity of river-groundwater interaction and hydrogeological characteristics of the aquifer renders a complex pattern of groundwater quality. The quality of the extracted drinking water can be managed using decision support and HACCP (Hazard Analysis and Critical Control Point) systems, but the detection of potential contamination remains a complex task to master. The methodology proposed herein uses a combination of high-resolution measurements and multivariate statistical analyses to characterise actual groundwater quality and detect potential contamination. The aim of this project was to improve the protection of riverine groundwater extraction wells and to increase the degrees of freedom available to the management of fluvial planes with drinking-water production and aquifer recharge by river-groundwater interaction. The monitoring network was set up in the Reinacherheide in North-west Switzerland and encompassed the depth-oriented installation of multiparameter instruments, a surface-water monitoring station and a flow-through cell with an automated sampler and high-precision measurement instruments. The parameters recorded included temperature, electrical conductivity, spectral absorption coefficient, particle density and turbidity. Two of the observation wells were equipped with a telemetry system and the flow cell could be controlled remotely. The well-field encompassed eight groundwater extraction wells. The optimal choice of observation wells and indicator parameters was assessed using principal component analysis of groundwater head, temperature and electrical conductivity time-series to detect the influence of, for example, river-water infiltration or river-stage fluctuations on the time-series recorded in the groundwater observation wells. Groundwater head was susceptible to pressure waves induced by both river-stage fluctuations and groundwater extraction. Temperature time-series showed only weak responses to high discharge events. Electrical conductivity, however, showed a distance-driven response pattern to high discharge events. To further assess the representative strength of individual groundwater quality indicator parameters for identifying microbial contamination, a bi-weekly and a high-resolution sampling campaign were carried out. The results showed high faecal-indicator bacteria densities (E. coli and Enterococcus sp.) at the beginning of high discharge events, followed by a rapid decrease, leading to a strong hit-and-miss characteristic in the bi-weekly sampling campaign. The third approach applied used the neural network-based combination of self-organizing maps and Sammon's projection (SOM-SM) to detect shifts in groundwater quality system states. The nonlinear analysis was carried out with groundwater head, temperature and electrical conductivity time-series from six observation wells. The subsequent shading of the projected trajectory of system states with independent time-series (spectral absorption coefficient and particle density) allowed the identification of critical system states, when actual groundwater quality decreased and contamination of the extraction wells was imminent. The time at which the changes in system state occurred and were detected were used as potential warning indicators for the water supplier. The effects of altered groundwater extraction (as a consequence of the SOM-SM warning) were then simulated using a groundwater flow model. The outcome of the SOM-SM analysis is, thus, proposed as an interface between the monitoring system and extraction-well management system. The proposed approach incorporates hydrogeological knowledge and the analysis of prevalent conditions concerning river-groundwater interaction with real-time telemetric data transfer, data-base management and nonlinear statistical analysis to detect deterioration in actual groundwater quality due to rapidly infiltrating river water. As the SOM-SM is not based on threshold values and independent of indicator parameters, the approach can be transferred to other sites with similar characteristics

Automated Data Collection and Management at Enhanced Lagoons for Wastewater Treatment

Les stations de mesure automatiques sont utilisées pour suivre et contrôler des usines de traitement des eaux usées. Ce suivi en continu à haute fréquence est devenu indispensable afin de réduire les impacts négatifs sur l’environnement car les caractéristiques de l’eau varient rapidement dans l’espace et dans le temps. Toutefois, même s’il y a eu des progrès considérables, ces dernières années, de la technologie de mesure, les instruments sont encore chers. Aussi des problèmes de colmatage, d’encrassement ou de mauvaise calibration sont assez fréquents à cause du contact avec les eaux usées. La fiabilité des mesures en ligne et en continu est affectée négativement. Par conséquent, un bon entretien des instruments est essentiel, ainsi que la validation des données collectées, afin de détecter d’éventuelles valeurs aberrantes. Dans le contexte de ce mémoire, en collaboration avec Bionest®, une méthodologie est proposée pour attaquer ces problèmes. Deux cas d’études en étangs aérés au Québec ont été considérés, avec l’objectif d’optimiser les activités d’entretien, de réduire les données non fiables et d’obtenir des grandes séries de données représentatives.Automated monitoring stations have been used to monitor and control wastewater treatment plants. Their capability to monitor at high frequency has become essential to reduce the negative impacts to the environment since the wastewater characteristics have an elevated spatial and time variability. Over the last few years, the technology used to build these automatic monitoring stations, for example the sensors, has been improved. However, the instrumentation is still expensive. Also, in wastewater uses, basic problems like fouling, bad calibration or clogging are frequently affecting the reliability of the continuous on-line measurements. Thus, a good maintenance of the instruments, as well as a validation of the collected data to detect faults is required. In the context of this thesis, in collaboration with Bionest®, a methodology has been developed to deal with these problems for two facultative/aerated lagoon case studies in Québec, with the objective of optimizing the maintenance activities, of reducing the fraction of unreliable data and of obtaining large representative data series

Development of an autonomous lab-on-a-chip system with ion separation and conductivity detection for river water quality monitoring

This thesis discusses the development of a lab on a chip (LOC) ion separation for river water quality monitoring using a capacitively coupled conductivity detector (C⁴D) with a novel baseline suppression technique.Our first interest was to be able to integrate such a detector in a LOC. Different designs (On-capillary design and on-chip design) have been evaluated for their feasibility and their performances. The most suitable design integrated the electrode close to the channel for an enhanced coupling while having the measurement electronics as close as possible to reduce noise. The final chip design used copper tracks from a printed circuit board (PCB) as electrodes, covered by a thin Polydimethylsiloxane (PDMS) layer to act as electrical insulation. The layer containing the channel was made using casting and bonded to the PCB using oxygen plasma. Flow experiments have been conduced to test this design as a detection cell for capacitively coupled contactless conductivity detection (C⁴D).The baseline signal from the system was reduced using a novel baseline suppression technique. Decrease in the background signal increased the dynamic range of the concentration to be measured before saturation occurs. The sensitivity of the detection system was also improved when using the baseline suppression technique. Use of high excitation voltages has proven to increase the sensitivity leading to an estimated limit of detection of 0.0715 μM for NaCl (0.0041 mg/L).The project also required the production of an autonomous system capable of operating for an extensive period of time without human intervention. Designing such a system involved the investigation of faults which can occur in autonomous system for the in-situ monitoring of water quality. Identification of possible faults (Bubble, pump failure, etc.) and detection methods have been investigated. In-depth details are given on the software and hardware architecture constituting this autonomous system and its controlling software

Enhanced Living Environments

This open access book was prepared as a Final Publication of the COST Action IC1303 “Algorithms, Architectures and Platforms for Enhanced Living Environments (AAPELE)”. The concept of Enhanced Living Environments (ELE) refers to the area of Ambient Assisted Living (AAL) that is more related with Information and Communication Technologies (ICT). Effective ELE solutions require appropriate ICT algorithms, architectures, platforms, and systems, having in view the advance of science and technology in this area and the development of new and innovative solutions that can provide improvements in the quality of life for people in their homes and can reduce the financial burden on the budgets of the healthcare providers. The aim of this book is to become a state-of-the-art reference, discussing progress made, as well as prompting future directions on theories, practices, standards, and strategies related to the ELE area. The book contains 12 chapters and can serve as a valuable reference for undergraduate students, post-graduate students, educators, faculty members, researchers, engineers, medical doctors, healthcare organizations, insurance companies, and research strategists working in this area

Chipless RFID sensor systems for structural health monitoring

Ph. D. ThesisDefects in metallic structures such as crack and corrosion are major sources of catastrophic failures, and thus monitoring them is a crucial issue. As periodic inspection using the nondestructive testing and evaluation (NDT&E) techniques is slow, costly, limited in range, and cumbersome, novel methods for in-situ structural health monitoring (SHM) are required. Chipless radio frequency identification (RFID) is an emerging and attractive technology to implement the internet of things (IoT) based SHM. Chipless RFID sensors are not only wireless, passive, and low-cost as the chipped RFID counterpart, but also printable, durable, and allow for multi-parameter sensing. This thesis proposes the design and development of chipless RFID sensor systems for SHM, particularly for defect detection and characterization in metallic structures. Through simulation studies and experimental validations, novel metal-mountable chipless RFID sensors are demonstrated with different reader configurations and methods for feature extraction, selection, and fusion. The first contribution of this thesis is the design of a chipless RFID sensor for crack detection and characterization based on the circular microstrip patch antenna (CMPA). The sensor provides a 4-bit ID and a capability of indicating crack width and orientation simultaneously using the resonance frequency shift. The second contribution is a chipless RFID sensor designed based on the frequency selective surface (FSS) and feature fusion for corrosion characterization. The FSS-based sensor generates multiple resonance frequency features that can reveal corrosion progression, while feature fusion is applied to enhance the sensitivity and reliability of the sensor. The third contribution deals with robust detection and characterization of crack and corrosion in a realistic environment using a portable reader. A multi-resonance chipless RFID sensor is proposed along with the implementation of a portable reader using an ultra-wideband (UWB) radar module. Feature extraction and selection using principal component analysis (PCA) is employed for multi-parameter evaluation. Overall, chipless RFID sensors are small, low-profile, and can be used to quantify and characterize surface crack and corrosion undercoating. Furthermore, the multi-resonance characteristics of chipless RFID sensors are useful for integrating ID encoding and sensing functionalities, enhancing the sensor performance, as well as for performing multi-parameter analysis of defects. The demonstrated system using a portable reader shows the capability of defects characterization from a 15-cm distance. Hence, chipless RFID sensor systems have great potential to be an alternative sensing method for in-situ SHM.Indonesia Endowment Fund for Education (LPDP

Structured monitoring of gas exchange in fermenters for control

Information from measurements made by on-line sensors are, directly or indirectly, critical to strategies for improved monitoring and control of industrial fermentations. Over the past 20 years, a large body of research has, with little success, attempted to expand the library of on-line measurements routinely used in industrial fermentation. Partly as a result, research efforts have increasingly been targeted at the development of models incorporating on-line data, that describe the dme-profiles of unmeasurable variables of importance to fermentation monitoring. Due to the complexity of most of these models, industrial applications have largely been limited to the simplest of empirical models, based around "derived variables" (that derive directly from one or more on-line measurements), most of them associated with gas exchange, examples being the carbon dioxide evolution rate (CER) and respiratory quotient (RQ). Improvements in the conditioning, analysis and application of gas exchange data would, therefore, be of considerable benefit in improved monitoring, modelling and control of fermentation. This project examines opportunities for such improvements. It was shown that the oxygen transfer rate (OTR) data contain a significant component of uncorrelated Gaussian noise arising from their calculation as a small difference between two large numbers. A chi-square filter was used to frt a linear model to a reduced data set containing only the most recent OTR data, in order to remove this noise. The benefits of applying such a filter were illustrated by the improvement in the quality of OTR data, and related derived variables (the mass transfer coefficient, KLO2a, and the respiratory quotient, RQ), during a Streptomyces clavuligerus fermentation. Theoretical work supported the view that carbon dioxide transfer can be treated as a purely liquid-film limited physical process, as for oxygen. Concerning the error involved in the (widely-used) assumption that the dissolved CO2 partial pressure is equal to the CO2 partial pressure in the exit gas, practical factors were shown to limit the maximum error possible. This error varies with KLO2a, and the aeration rate, being 20-30% in small fermentors, and less in large fermentors. The theoretical results were supported with experimental data from Escherichia coli fermentations. For fermentations run above pH 6.5, the high effective solubility of dissolved carbon dioxide can cause changes in the pH and CER to make unsteady-state terms in the CO2 mass balance important. An effect is to cause the "measured respiratory quotient" as apparent from gas analyses (called here the transfer quotient, or TQ) to differ from the real underlying respiratory quotient (RQ). A model to predict such effects agreed well with experimental results from fermentations of E. coli and S. clavuligerus. The control of pH by on-off additions of acid or base introduces regular fluctuations into the TQ that are not present in the underlying RQ. During exponential growth, the TQ is smaller than the RQ. The RQ can be estimated on-line from the TQ using the model developed. It was shown, both from theory and during an E. coli fermentation, that a simple ratio controller could control the partial pressure of dissolved CO2 to an approximately constant value