The DSP is used as the control kernel in this thesis, proposing a method of sensorless and variable speed driving with current feedback for the DC compressor. By detecting the back electromotive force signals directly, the information of rotor position can be obtained, the commutation process and the speed estimation can also be achieved. Combining the current feedback method, the sinusoidal commutation with sensorless control makes the motor lower speed ripple and higher rotating efficiency. The results show that the sinusoidal commutation approach has the advantages of higher efficiency and less speed ripple as compared to the approaches of traditional-step commutation and six-step with current feedback by experimental setting.

Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2004. / Includes bibliographical references (leaves 108-111). Also available in electronic version. Access restricted to campus users.

Blood pressure is one of the fundamental clinical measures. For more than 100 years, clinicians and researchers have used the mercury sphygmomanometer for blood pressure measurement. Environmental concern about mercury contamination has highlighted the need to find a replacement for traditional mercury sphygmomanometers. A number of currently used non-invasive blood pressure measurement methods have been studied in this research. The most commonly used automatic pressure monitoring method nowadays is the Oscillometric method. Height-based and Slope-based criteria are the two general means used to determine the systolic and diastolic pressures. However, these two criteria have many disputed points, making them debatable as a good standard for blood pressure measurement. For this reason, the auscultatory method continues to be the gold-standard for non-invasive blood pressure measurement. Current research uses a newly developed cuff with three different lengths of piezo film sensors and a pressure sensor to collect signals from the brachial artery. The objectives of the research are to process the measured signal from the sensors and develop a blood pressure measurement algorithm that will accurately determine the blood pressure noninvasively. Signal processing and heart beat / heart rate detection software have been developed. The best algorithm has been selected from three developed algorithms for further modification and validation. The final algorithm used two feed-forward Neural Networks to classify the acquired pressure signals into various regions of the pressure signals. The final algorithm has been tested on 258 measurements from 86 subjects. The testing result showed that the algorithm achieved grade A for both systolic and diastolic pressures according to the British Hypertension Society protocol. The mean differences (SD) between the observers and the developed algorithm were 1.44 (5.27) mmHg and 1.77 (6.17) mmHg for systolic and diastolic pressures, respectively, which also fulfilled the Association for the Advancement of Medical Instrumentation protocol. In conclusion, this algorithm was successfully developed and it is recommended for further clinical trial in a wider adult population. Further development of this algorithm also includes extending to other subgroups such as pregnant women, arrhythmia, diabetics and other subjects with diseases.

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2004. / Includes bibliographical references (leaves 141-153). Also available in electronic version. Access restricted to campus users.

The work presented in this thesis is divided loosely into three main areas of interest: development of a novel method of solid-state nanopore fabrication; applications of this method to some of the open problems in the field; and analysis of nanopore data. The first of these occupies the majority of the research presented in this thesis, covering research dedicated to the development and characterization of a novel method of solid-state nanopore fabrication which achieves nanometer scale control over matter using simple and low cost circuitry. Termed controlled breakdown (CBD), this technique is in the process of revolutionizing the field of nanopore research, and in the few short years I have been part of its development it has seen adoption in nanopore labs across the globe, both academic and industrial. Due to the simple nature of CBD, this technique also enables novel applications of nanopores in device architectures that were inaccessible to the expensive and inflexible methods used previously. The second part of this thesis takes advantage of the unique opportunities presented by CBD to develop a device architecture comprising two nanopores in series. This nanodevice tackles one of the main problems standing between nanopores and the promise of cheap genomic analysis: control of the motion and conformation of the polymer both prior to and during translocation through the pore. Finally, because the field of nanopore research is still relatively young, very few tools are available which provide high-quality analysis of nanopore data. The last part of this thesis is dedicated to a thorough discussion of the complexities involved in analysing nanopore signals, as well as the development of several tools which directly address this knowledge gap.

This thesis examines the application of Digital Signal Processing (DSP) techniques, and specifically Wavelets, to the field of automatic coin recognition. The aim is to utilise DSP techniques to exploit information that is contained within time domain signals representing coins, which can not be accessed by other means. Attention is also given to the power requirement of possible solutions, with a low power solution being a secondary aim, as the solutions are targeted for use in a line-powered payphone. An examination of existing coin recognition techniques is presented, for which an improved but basic DSP coin recognition scheme using peak and trough location, is achieved. This is then improved using more advanced DSP techniques to access previously unavailable information contained within the signals. The advanced DSP techniques are developed into an integrated framework for automatic coin recognition. The framework is used to identify a single Wavelet solution that supplies a DSP representation of a set of coins. The representations of different coin types exist within a region of n-dimensional Euclidean space, which the framework attempts to locate uniquely for each coin type. To enable the framework to operate successfully, a key feature presented is the resampling of the waveforms input into the framework, to normalise any temporal variations in the input data. The location of the single Wavelet for analysis can not be achieved analytically and so is obtained using a novel Data Mining solution to search a Wavelet dictionary for possible solutions. This thesis proves that utilisation of the time localisation properties of the Discrete Wavelet Transform is possible when taken together with a distance metric strategy. Appropriate results are presented to verify the performance of the Wavelet solutions provided by the framework, especially in respect of counteracting fraudulent coins in the recognition process. As an overall validation of the research solution, an emulation of the coin recognition system was produced that could validate coins in real time, this is also documented. Both the hardware and software components of the integrated framework which have been developed, are fully modular and hold significant potential for expansion and integration into newer, more powerful cost effective coin recognition systems.

Made available in DSpace on 2014-06-11T19:34:58Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-07-07Bitstream added on 2014-06-13T19:44:42Z : No. of bitstreams: 1 costa_c_dr_guara.pdf: 2365051 bytes, checksum: 734a89b6d453aae979b320a037beeda4 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / O monitoramento em tempo real de eventos em uma planta industrial é uma técnica avançada que apresenta condições reais de funcionamento das máquinas responsáveis pelo processo de manufatura. Um programa de manutenção preditiva em máquinas rotativas engloba várias técnicas de monitoramento da condição da máquina, para determinar o surgimento de falhas. Para o aumento da confiabilidade operacional e redução da manutenção preditiva, faz-se necessário um instrumento eficiente de análise e monitoramento do processo que, em tempo real possibilite a detecção de falhas incipientes. Durante os últimos anos tem ocorrido uma grande evolução tecnológica na área de sistemas digitais, abrangendo inovações tanto em hardware como em software. tais inovações permitem o desenvovimento de novas metodologias de projeto que levam em conta a facilidade de futuras modificações modernizações e expansões do sistema projetado. Este trabalho apresenta um estudo de novas ferramentas de projeto para sistemas digitais embarcados, baseados em aquitetura de hardware aberta com lógica reconfigurável. Será abordado um estudo de caso na área de detecção de falhas em máquinas rotativas, bem como sua implementação e teste / The real-time monitoring of events in an industrial plant is an advanced technique that presents the real conditions of operation of the machinery responsible for the manufactiring process. A predictive maintenance program inclues various rotating machinery condition monitoring rwchiques of the machine to determine the conditions of failure. To increase the operational reliability and reduced preventive maintenance, it is necessary an efficient tool for analysis and process monitoring, in real time, enabling the detection of incipient faults. Over the past few years there has been a major technological developments related to digital systems, including innovations in both hardware and software. These innovations enable the development of new design methodologies that take into account the ease of future modifications, upgrade and expansions of the esigned system. This paper presents a study of new design tools for embedded digital systems based on open hardware architecture eith reconfigurable logic. Wil be discussed a case study in the area of fault detection in rotating machinery, as well as its implementation and testing

Master of Science / Department of Electrical and Computer Engineering / Alexei Nikitin / Balasubramaniam Natarajan / It has been shown that the performance of communications systems can be severely limited by non-Gaussian and impulsive interference from a variety of sources. The non-Gaussian nature of this interference provides an opportunity for its effective mitigation by nonlinear filtering. In this thesis, we describe blind adaptive analog nonlinear filters, referred to as Adaptive Nonlinear Differential Limiters (ANDLs), that are characterized by several methodological distinctions from the existing digital solutions. When ANDLs are incorporated into a communications receiver, these methodological differences can translate into significant practical advantages, improving the receiver performance in the presence of non-Gaussian interference. A Nonlinear Differential Limiter (NDL) is obtained from a linear analog filter by introducing an appropriately chosen feedback-based nonlinearity into the response of the filter, and the degree of nonlinearity is controlled by a single parameter. ANDLs are similarly controlled by a single parameter, and are suitable for improving quality of non-stationary signals under time-varying noise conditions. ANDLs are designed to be fully compatible with existing linear devices and systems (i.e., ANDLs’ behavior is linear in the absence of impulsive interference), and to be used as an enhancement, or as a simple low-cost alternative, to state-of-the-art interference mitigation methods. We provide an introduction to the NDLs and illustrate their potential use for noise mitigation in communications systems. We also develop a digital implementation of an ANDL. This allows for rapid prototyping and performance analysis of various ANDL configurations and use cases.

Orientador: Mauro Hugo Mathias / Banca: José Elias Tomazini / Banca: Samuel Euzédice de Lucena / Banca: Jussara Pimenta Matos / Banca:Francisco Carlos Parquet Bizarria / Resumo: O monitoramento em tempo real de eventos em uma planta industrial é uma técnica avançada que apresenta condições reais de funcionamento das máquinas responsáveis pelo processo de manufatura. Um programa de manutenção preditiva em máquinas rotativas engloba várias técnicas de monitoramento da condição da máquina, para determinar o surgimento de falhas. Para o aumento da confiabilidade operacional e redução da manutenção preditiva, faz-se necessário um instrumento eficiente de análise e monitoramento do processo que, em tempo real possibilite a detecção de falhas incipientes. Durante os últimos anos tem ocorrido uma grande evolução tecnológica na área de sistemas digitais, abrangendo inovações tanto em hardware como em software. tais inovações permitem o desenvovimento de novas metodologias de projeto que levam em conta a facilidade de futuras modificações modernizações e expansões do sistema projetado. Este trabalho apresenta um estudo de novas ferramentas de projeto para sistemas digitais embarcados, baseados em aquitetura de hardware aberta com lógica reconfigurável. Será abordado um estudo de caso na área de detecção de falhas em máquinas rotativas, bem como sua implementação e teste / Abstract: The real-time monitoring of events in an industrial plant is an advanced technique that presents the real conditions of operation of the machinery responsible for the manufactiring process. A predictive maintenance program inclues various rotating machinery condition monitoring rwchiques of the machine to determine the conditions of failure. To increase the operational reliability and reduced preventive maintenance, it is necessary an efficient tool for analysis and process monitoring, in real time, enabling the detection of incipient faults. Over the past few years there has been a major technological developments related to digital systems, including innovations in both hardware and software. These innovations enable the development of new design methodologies that take into account the ease of future modifications, upgrade and expansions of the esigned system. This paper presents a study of new design tools for embedded digital systems based on open hardware architecture eith reconfigurable logic. Wil be discussed a case study in the area of fault detection in rotating machinery, as well as its implementation and testing / Doutor

Vocal cord vibration is the source of voiced phonemes in speech. Voice quality depends on the nature of this vibration. Vocal cords can be damaged by infection, neck or chest injury, tumours and more serious diseases such as laryngeal cancer. This kind of physical damage can cause loss of voice quality. To support the diagnosis of such conditions and also to monitor the effect of any treatment, voice quality assessment is required. Traditionally, this is done ‘subjectively’ by Speech and Language Therapists (SLTs) who, in Europe, use a well-known assessment approach called ‘GRBAS’. GRBAS is an acronym for a five dimensional scale of measurements of voice properties. The scale was originally devised and recommended by the Japanese Society of Logopeadics and Phoniatrics and several European research publications. The proper- ties are ‘Grade’, ‘Roughness’, ‘Breathiness’, ‘Asthenia’ and ‘Strain’. An SLT listens to and assesses a person’s voice while the person performs specific vocal maneuvers. The SLT is then required to record a discrete score for the voice quality in range of 0 to 3 for each GRBAS component. In requiring the services of trained SLTs, this subjective assessment makes the traditional GRBAS procedure expensive and time-consuming to administer. This thesis considers the possibility of using computer programs to perform objective assessments of voice quality conforming to the GRBAS scale. To do this, Digital Signal Processing (DSP) algorithms are required for measuring voice features that may indicate voice abnormality. The computer must be trained to convert DSP measurements to GRBAS scores and a ‘machine learning’ approach has been adopted to achieve this. This research was made possible by the development, by Manchester Royal Infirmary (MRI) Hospital Trust, of a ‘speech database’ with the participation of clinicians, SLT’s, patients and controls. The participation of five SLTs scorers allowed norms to be established for GRBAS scoring which provided ‘reference’ data for the machine learning approach.
To support the scoring procedure carried out at MRI, a software package, referred to as GRBAS Presentation and Scoring Package (GPSP), was developed for presenting voice recordings to each of the SLTs and recording their GRBAS scores. A means of assessing intra-scorer consistency was devised and built into this system. Also, the assessment of inter-scorer consistency was advanced by the invention of a new form of the ‘Fleiss Kappa’ which is applicable to ordinal as well as categorical scoring. The means of taking these assessments of scorer consistency into account when producing ‘reference’ GRBAS scores are presented in this thesis. Such reference scores are required for training the machine learning algorithms. The DSP algorithms required for feature measurements are generally well known and available as published or commercial software packages. However, an appraisal of these algorithms and the development of some DSP ‘thesis software’ was found to be necessary. Two ‘machine learning’ regression models have been developed for map- ping the measured voice features to GRBAS scores. These are K Nearest Neighbor Regression (KNNR) and Multiple Linear Regression (MLR). Our research is based on sets of features, sets of data and prediction models that are different from the approaches in the current literature. The performance of the computerised system is evaluated against reference scores using a Normalised Root Mean Squared Error (NRMSE) measure. The performances of MLR and KNNR for objective prediction of GRBAS scores are compared and analysed ‘with feature selection’ and ‘without feature selection’. It was found that MLR with feature selection was better than MLR without feature selection and KNNR with and without feature selection, for all five GRBAS components. It was also found that MLR with feature selection gives scores for ‘Asthenia’ and ‘Strain’ which are closer to the reference scores than the scores given by all five individual SLT scorers. The best objective score for ‘Roughness’ was closer than the scores given by two SLTs, roughly equal to the score of one SLT and worse than the other two SLT scores. The best objective scores for ‘Breathiness’ and ‘Grade’ were further from the reference scores than the scores produced by all five SLT scorers. However, the worst ‘MLR with feature selection’ result has normalised RMS error which is only about 3% worse than the worst SLT scoring. The results obtained indicate that objective GRBAS measurements have the potential for further development towards a commercial product that may at least be useful in augmenting the subjective assessments of SLT scorers.