This thesis presents novel methods for advanced modelling and fault diagnosis of power apparatuses, which mainly contain power transformers and induction motors. These two popular applied power apparatuses are inherently reliable. But, they may deteriorate and fail without effective preventive maintenance. This gives rise to the need of research work for condition monitoring and assessment. For the condition monitoring and assessment of a power transformer, dissolved gas analysis (DGA) has been applied to determine the condition of a power transformer during the past decades. A core problem needs to be considered is the classification of nonlinear DGA gas data. As a well-approved technique to diagnose incipient faults, all the applied fault interpretation methods are based on the DGA data of laboratory simulation and industrial faulty inspection. These inspection data are usually obtained by periodically sampling liquids from power transformers and analysing the dissolved gases in laboratories. Threshold values of DGA interpretation methods are obtained by using the DGA gas records of laboratory simulation and industrial faulty inspection. But, it is not always possible to conduct precise measurements of gas records, the measurement errors sometimes too big to obtain correct DGA results. Hence, threshold values and error redundancy of current DGA methods need to be re-examined using DGA gas records within a reasonable error range. In the study, in order to test the reliability of DGA methods, the ±5% variation is applied to faulty gas value of laboratory simulated case and the ±10% variation is used to those fault cases identified by inspection of the equipment. Based on the analysis of results, three zones of Duval triangle, which represent highly possible misclassification faults of discharge, overheating and partial discharge, are concluded for improving its reliability. Conventional DGA ratio methods are not unbiased and sometimes provide different judgements. In order to establish a reliable, intelligent fault classification method, three main aspects, including DGA data pre-processing, effective gas feature extraction, and optimised computational classifiers have been considered for the classification of non-linear DGA data. To cope with the highly versatile or noise-corrupted DGA data, two methods, bootstrap and logarithm transformation under two base and ten base conditions, are employed as data pre-processing tools. For gas feature extraction, unified and non-unity new features are first obtained based on in-depth analysis of current DGA standards. Meanwhile, the statistical characteristics of the selected gas features are used for prioritisation. A ten based logarithmic transformation is first applied to three select ratios of combustible gases against the total gas volume and the total gas volume itself. The bootstrap method is used to overcome the shortage of class samples. Nine features, including five features of conventional ratios, are used as input vectors to SVM, LSSVM and SVDD, whose tunning parameters are optimised by PSO. Comparisons of classification results between conventional gas ratios and the proposed nine feature ratios are illustrated finally. It shows that PSO-LSSVM has the highest classification accuracy using nine feature ratios. These unified features of different classifications might cause redundant information that leads to a low overall accuracy. Therefore, attempts have been made to achieve feature extraction for different classification condition by the analysis of Duval triangle, IEC standards and feature prioritisation. A two based logarithmic transformation is applied as data preprocessing. Prioritization orders of all gas features are obtained for different classification levels by using the Kolmogorov- Smirnov (K-S) test. The first three highly ranked features are selected as input vectors for a multi-layer PSO-SVM classifier. For comparison, a three layer multilayer perception (MLP) neural networks, PSO-SVM and KNN are applied with different number of genetic programming (GP) features. Among all classification accuracies, the PSO-SVM with the proposed features can gain the highest accuracy. In the appendix part, the detection of broken bars of an induction machine based on multiple coupled circuit model is proposed. The optimised motor parameters are achieved by minimising the gap between experimental results and simulation model responses using GA. Based on the optimised model, faults of one broken bar and two broken bars conditions are detected by extracting the harmonic components appearing at the right and left sides of the fundamental frequency.

Developments in theory and experiment have raised the prospect of an electronic technology based on the discrete nature of electron tunnelling through a potential barrier. This thesis deals with novel design and analysis tools developed to study such systems. Possible devices include those constructed from ultrasmall normal tunnelling junctions. These exhibit charging effects including the Coulomb blockade and correlated electron tunnelling. They allow transistor-like control of the transfer of single carriers, and present the prospect of digital systems operating at the information theoretic limit. As such, they are often referred to as single electronic devices. Single electronic devices exhibit self quantising logic and good structural tolerance. Their speed, immunity to thermal noise, and operating voltage all scale beneficially with junction capacitance. For ultrasmall junctions the possibility of room temperature operation at sub picosecond timescales seems feasible. However, they are sensitive to external charge; whether from trapping-detrapping events, externally gated potentials, or system cross-talk. Quantum effects such as charge macroscopic quantum tunnelling may degrade performance. Finally, any practical system will be complex and spatially extended (amplifying the above problems), and prone to fabrication imperfection. This summarises why new design and analysis tools are required. Simulation tools are developed, concentrating on the basic building blocks of single electronic systems; the tunnelling junction array and gated turnstile device. Three main points are considered: the best method of estimating capacitance values from physical system geometry; the mathematical model which should represent electron tunnelling based on this data; application of this model to the investigation of single electronic systems.

Wireless Sensor Networks appear as a technology, which provides the basisfor a broad field of applications, drawing interest in various areas. On theone hand, they appear to allow the next step in computer networks, buildinglarge collections of simple objects, exchanging information with respect totheir environment or their own state. On the other hand, their ability tosense and communicate without a fixed physical infrastructure makes theman attractive technology to be used for measurement systems.Although the interest inWireless Sensor Network research is increasing,and new concepts and applications are being demonstrated, several fundamentalissues remain unsolved. While many of these issues do not requireto be solved for proof-of-concept designs, they are important issues to beaddressed when referring to the long-term operation of these systems. Oneof these issues is the system’s lifetime, which relates to the lifetime of thenodes, upon which the system is composed.This thesis focuses on node lifetime extension based on energy management.While some constraints and results might hold true from a moregeneral perspective, the main application target involves environmental measurementsystems based onWireless Sensor Networks. Lifetime extensionpossibilities, which are the result of application characteristics, by (i) reducingenergy consumption and (ii) utilizing energy harvesting are to be presented.For energy consumption, we show howprecise task scheduling due to nodesynchronization, combined with methods such as duty cycling and powerdomains, can optimize the overall energy use. With reference to the energysupply, the focus lies on solar-based solutions with special attentionplaced on their feasibility at locations with limited solar radiation. Furtherdimensioning of these systems is addressed.It will be shown, that for the presented application scenarios, near-perpetualnode lifetime can be obtained. This is achieved by focusing on efficient resourceusage and by means of a carefully designed energy supply.

In the emerging technology of Micro Electronic Mechanical Systems (MEMS) there are challenges such as adoption, economies of scale, packaging and reliability incurred by many nascent technologies. The advantages of MEMS devices such as small micron scale, low power consumption and lab on a chip style data processing clearly outline the practical potential for the technology. Packaging and reliability driven by cost, however; are the factors that hinder progress of the technology and further entry into market. In the case of MEMS however, existing methods must be reassessed as fundamentally the concepts and scales have changed. MEMS is a market that despite challenges of the economy is still committed to heavy global investment from figures of $7bn in 2009 with 13% growth in 2010 with a projected growth rate of 14-15% over the years 2011 – 2015. (Dempsey, 2010) Reliability in essence holds the key to driving down the unit cost of production and technology adoption; if units are more reliable there is a potential for increased sales, further refinement and development as the case with mobile phones and the automotive industry. Thus the aim of this project is to create and apply a methodology of assessing the reliability of MEMS components. This research project focused on using a scientific based research methodology, conventional metrology and engineering techniques to produce a method of predicting lifetime information for a particular device component. A broad selection of experimental techniques were assessed and deemed unsuitable, primarily due to inflicting unnecessary damage of the fragile structures, range restrictions on forces that could be loaded and availability of equipment. Following laboratory work and iterative refinement, a successful methodology was created and refined; allowing to mechanically actuate a MEMS membrane to high cycle fatigue failure without damage due to contact force. This used with the bulge test can provide information on new MEMS composites and how they behave as realistically as possible in their future application space. Working closely with QinetiQ and an international collaboration funded by the European Defence Agency (EDA), on a broader MEMS reliability project called POLYNOE; it is now possible to achieve lifetime information for MEMS membranes and use the created experimental technique to cater for any micron sized membrane for any duration at a cycle rate not known or explored in this domain before. Characterisation data, of the membrane and thin film with substrate structure was obtained and using traditional Finite Element Analysis (FEA) and Accelerated Life Cycle Prediction techniques the stresses incurred and Mean Times to Failures (MTTF) for the membranes was calculated as 32million cycles at a comparative operating force of 0.14mN. Suggestions have been made at the possibilities of implementing the methodology and techniques at QinetiQ; to complement their traditional low cycle method of stressing the membranes and therefore iterate the useful information back into the development cycle to refine designs increase reliability and therefore reduce unit cost.

Many industrial processes have non-linear and time-varying dynamics, for which the control and optimization require further investigations. Adaptive modelling techniques using radial basis function (RBF) networks often provide competitive modelling performances but encounter slow recovery speed when processes operating regions are shifted largely. In addition, RBF networks based model predictive control results as a non-linear programming problem, which restricts the application to fast dynamic systems. To these targets, the thesis presents the development of adaptive and factorized RBF network models. Model predictive control (MPC) based on the factorized RBF model is applied to a non-linear proton exchange membrane fuel cell (PEMFC) stack system. The main contents include three parts: RBF model adaptation; model factorization and fast long-range prediction; and MPC for the PEMFC stack system. The adaptive RBF model employs the recursive orthogonal least squares (ROLS) algorithm for both structure and parameter adaptation. In decomposing the regression matrix of the RBF model, the R matrix is obtained. Principles for adding centres and pruning centres are developed based on the manipulation of the R matrix. While the modelling accuracy is remained, the developed structure adaptation algorithm ensures the model size to be kept to the minimum. At the same time, the RBF model parameters are optimized in terms of minimum Frobenius norm of the model prediction error. A simulation example is used to evaluate the developed adaptive RBF model, and the model performance in output prediction is superior over the existing methods. Considering that a model with fast long-range prediction is needed for the MPC of fast dynamic systems, a f-step factorization algorithm is developed for the RBF model. The model structure is re-arranged so that the unknown future process outputs are not required for output prediction. Therefore, the accumulative error caused by recursive calculation in normal neural network model is avoided. Furthermore, as the information for output prediction is explicitly divided into the past information and the future information, the optimization of the control variable in the MPC based on this developed factorized model can be solved much faster than the normal NARX-RBF model. The developed model adaptation algorithm can be applied to this f-step factorized model to achieve fast and adaptive model prediction. Finally, the developed factorized RBF model is applied to the MPC of a PEMFC stack system with a popular industrial benchmark model in Simulink developed at Michigan University. The optimization algorithms for quadratic and non-linear system without and with constraints are presented and discussed for application purpose in the NMPC. Simulation results confirm the effectiveness of the developed model in both smooth tracking performance and less optimization time used. Conclusions and further work are given at the end of the thesis. Major contributions of the research have been outlined and achievements are checked against the objectives assigned. Further work is also suggested to extend the developed work to industrial applications in real-time simulation. This is to further examine the effectiveness of developed models. Extensive investigations are also recommended on the optimization problems to improve the existing algorithms.

Cycling is an increasingly popular mode of travel in cities owing to the great advantages that it offers in terms of space consumption, health and environmental sustainability, and it is therefore favoured and promoted by many city authorities worldwide. A large number of recently introduced cycling-related schemes in many cities demonstrates this trend. However, the relatively low safety of pedal cycles as perceived by the users currently presents itself as a hurdle, and therefore cycling has yet to be adopted to a wider extent by users as a true alternative to the private car. Rising accident numbers, unfortunately, confirm this perception as reality, with a particular source of hazard appearing to originate from the interaction of cyclists with motorised traffic at low speeds in urban areas. Technological advances in recent years have resulted in a number of attempts to develop systems to prevent cyclist-vehicle collisions, but they have generally stumbled upon the challenge of accurate cyclist localisation and tracking, which can enable predicting a collision within a short-term time-horizon (5-10 seconds). Indeed, cyclist positioning accuracy is essential for any collision avoidance system, not only to ensure the effective operation of the system but also to minimise the occurrence of false alerts. Thus, motivated by the poor safety record, the research reported here involves the development and testing of an innovative technological solution for accurately localising and tracking cyclists, where the ultimate aim is to utilise the techniques in a concept called Cyclist 360° Alert to avoid collisions. The overarching innovation of this PhD is the development of the instrumented bicycle system, called iBike, which can be employed to track cyclists’ positions more precisely. The system relies on bicycles being instrumented with low-cost Micro-electromechanical systems (MEMS) sensors, and utilises multiple Kalman filters, which were developed from the geometrical and kinematics modelling of the bicycles, to conduct a multi-sensor fusion on the iBike acquisition data with the measurements from the Global Positioning System, Wi-Fi hotspots and mobile communication systems. Apart from the above, the thesis also reports on the results obtained from a number of field trials where an enhanced off-the-shelf positioning system was employed to validate the developed system. The overall results from the field experiments demonstrate that, on average with an 80% probability, the iBike system can be used to estimate a position with less than 0.5 m error compared to a 16.2 m error from the enhanced positioning system under the same circumstances. Thus, the results from the field trials using the iBike have shown successful outcomes for the developed methodologies. This means that the iBike can be used to predict a collision more precisely. These results are presented in detail together with the hardware and software of the iBike system in this thesis.

The more electric aircraft initative results in significant challenges in the design of aircraft electrical power systems. Different power system architectures are currently being studied by the engineering community. In this thesis, a promising single DC bus-based, multiple-source multiple-load power system is investigated in terms of power management and stability. Due to its inherent modularity and ease of implementation, droop control, as a decentralised control method, has been widely used to cope with power sharing among parallel sources in the studied architecture. The thesis proposes a comparative study of different droop control approaches by focusing on steady-state power sharing performance and stability. • Different droop control methods may lead to different stability margins. Until now, the effect of different droop control schemes on system stability has not been fully investigated. The thesis presents the control scheme for current-mode and voltage-mode systems, derives the corresponding output impedance of the source subsystem and analyses the stability of the power system. Based on the developed mathematical model, comprehensive modal analysis of the power system is performed. • A generalised analytical impedance analysis is extended to a multi-source multi-load power system. To facilitate the analysis, the thesis proposes the concept of “global droop gain” as an important factor to determine the V-I bus characteristic and the stability behaviour of a parallel sources based DC system. • Considering the tradeoff between voltage regulation and power sharing accuracy in droop control, this thesis proposes an improved voltage regulation method in multi-source based DC electrical power system. Due to the absence of additional controllers or communication lines, the proposed approach can be relatively easily implemented in a small scale DC electrical power system. The proposed approach effectively improves the load sharing accuracy under high droop gain circumstances with consideration of cable impedance. Optimal droop gain settings are investigated and the selection of individual droop gains has been described in order to reduce the distribution losses. Finally, the above-mentioned analytical results are confirmed by time-domain simulations and experimental results.

In our increasingly connected world, maintaining the security of information systems is challenging. Today’s interconnected business environment calls for a change in how IS security is achieved to include thinking about the entire networks of relationships involved in preventing threats rather than just focusing on individual organizational security processes. Despite acknowledging the role of distributed and heterogeneous actors in achieving a secure environment, there is a lack of knowledge of how these actors actually prevent security threats. Moreover, the heterogeneity of actors involved gives rise to the issue of incentives needed to align their interests to ensure successful collective security efforts. This PhD thesis addresses these issues by zooming in on security networks, defined as collective efforts pursued by distributed actors to develop and adopt prevention measures to achieve security, to explain how these networks prevent security threats and identify the incentive mechanisms for converging the network’s heterogeneous actors. I challenge equilibrium and linearity assumptions identified in the current literature and argue for the need to adopt different theoretical and methodological approaches to uncover the dynamics in these networks. Through a historical case study of credit card fraud and how its prevention measures evolved over the last 55 years, I develop a process model of prevention encounters in security networks. The model depicts the dynamic and interactive nature of the prevention process and shows how the three proposed prevention mechanisms, namely, proposing solutions, resolving dissonance, and paving the way, interact to achieve prevention. The thesis further proposes three new forms of incentive mechanisms (transformative, preparatory, and captive) that are crucial for the survival of collective security efforts and show how they interact with the three prevention mechanisms. By this, this research complements the current security networks literature by offering a process model that explains how security networks achieve prevention. In addition, the interplay between the three incentive mechanisms reveals that incentives are not only ready-made structures or one-time event as depicted in the current literature but that they should also be seen as a socially dynamic process.

Axial-field permanent magnet motors have been shown to offer improved efficiency and power density compared with conventional machines. The different aspects of the advantages of permanent magnet disc armature motors have been demonstrated. A technique is described by which the magnetic circuit is then designed for optimum motor efficiency. The development of criteria for the selection of machine parameters leads to a commuter program that produces a realistic design given only the desired rower, speed, and voltage as input data. An analytical model has been established to quantitively predict the degree to which the permanent magnet field is demagnetised by the armature current. A new method for armature construction (skeleton armature) is described which is more satisfactory than encapsulation for the necessary mechanical strength and rigidity. The high power to weight and high power to volume allows novel locations to be considered for the drive motor within the vehicle, and a new design of axle-mounted twin-rotor machine will also be described. Such relocation, together with belt reduction gear, reduces the weight and rower losses associated with other transmission components. The construction of a vehicle test facility to evaluate the performance of electric and hybrid vehicles is described. The Nova series hybrid vehicle was tested on the rig. The trials showed that the losses in belt drive transmissions were less than those in a conventional transmission.

Helical devices are employed in the area of microwave technology. Applications such as filters and travelling-wave tubes are some of these in which helical devices are used. Ferrite loaded helical devices have been of interest to scientists and engineers throughout the last half century. The structure that is considered in this thesis is of a helix surrounded by a ferrite tube, both of which are enclosed in a cylindrical waveguide. Maxwell's equations for electromagnetism are employed in order to derive the expressions for the electric and magnetic fields. The parameters of the structure are varied in order to observe how certain factors will affect the dispersiveness, loss and phase shift of the structure. The investigation considers the effect of varying the applied magnetic field. The investigation also incorporates an air gap between the ferrite and helix and between the ferrite and metal waveguide. For the first time, the affects of these air gaps are analysed.