Defect classification for steam generator tubes of a nuclear power plant using ultrasonic nondestructive evaluation

The purpose of Nondestructive Evaluation (NDE) is to detect flaws and other failure-related conditions in a structural part without causing any damage or performance deterioration. Various forms of energy have been used in NDE including electromagnetic (ranging in frequency from dc resistivity measurements through quasi static and RF impedance measurements to visual and X-ray inspections), thermal energy, neutron and ultrasonic. Ultrasonic NDE is one of the most widely used because of many advantages - it can be inexpensively generated and detected, it can propagate deeply into the interior of many structures without excess attenuation and the return signals have sufficient information-carrying capacity to determine important failure-related characteristics. Steam generator tubes have an important safety role in a nuclear power plant because they constitute one of the primary barriers between the radioactive and non-radioactive sides of the plant. For this reason, the integrity of the tubing is essential in minimizing the leakage of water between the two sides of the plant. Any defects formed on these tubes can result into fatal consequences. Eddy current examination techniques used to inspect steam generator tubing provide a good screening for tube integrity but lack the ability to accurately size certain flaw mechanisms. Due to this sizing uncertainty, conservative decisions must be made with regard to remedies resulting in premature plugging and reduced inspection cycle lengths. It has been argued in some cases that ultrasonic examination techniques could provide better sizing and characterization. In this research project, a classification system was developed that classifies the cracks from deposits formed on the steam generator tubes. Various stages involved in the entire process were 1) Pre-processing of the raw signals (B-Scans), 2) Feature extraction and selection, 3) Classifier design, and 4) testing and validation of the system performance. The available B-Scan data was pre-processed and then features were extracted by using the Discrete Wavelet Transform (DWT). Appropriately chosen DWT coefficients were then applied to a MLP neural network with back propagation learning algorithm. The results obtained were satisfactory ([Difference symbol]94% correct classification) keeping in view the limited amount of data set available for training the neural network

Custom architecture for multicore audio Beamforming systems

The audio Beamforming (BF) technique utilizes microphone arrays to extract acoustic sources recorded in a noisy environment. In this article, we propose a new approach for rapid development of multicore BF systems. Research on literature reveals that the majority of such experimental and commercial audio systems are based on desktop PCs, due to their high-level programming support and potential of rapid system development. However, these approaches introduce performance bottlenecks, excessive power consumption, and increased overall cost. Systems based on DSPs require very low power, but their performance is still limited. Custom hardware solutions alleviate the aforementioned drawbacks, however, designers primarily focus on performance optimization without providing a high-level interface for system control and test. In order to address the aforementioned problems, we propose a custom platform-independent architecture for reconfigurable audio BF systems. To evaluate our proposal, we implement our architecture as a heterogeneous multicore reconfigurable processor and map it onto FPGAs. Our approach combines the software flexibility of General-Purpose Processors (GPPs) with the computational power of multicore platforms. In order to evaluate our system we compare it against a BF software application implemented to a low-power Atom 330, amiddle-ranged Core2 Duo, and a high-end Core i3. Experimental results suggest that our proposed solution can extract up to 16 audio sources in real time under a 16-microphone setup. In contrast, under the same setup, the Atom 330 cannot extract any audio sources in real time, while the Core2 Duo and the Core i3 can process in real time only up to 4 and 6 sources respectively. Furthermore, a Virtex4-based BF system consumes more than an order less energy compared to the aforementioned GPP-based approaches. © 2013 ACM

Advancements and Breakthroughs in Ultrasound Imaging

Ultrasonic imaging is a powerful diagnostic tool available to medical practitioners, engineers and researchers today. Due to the relative safety, and the non-invasive nature, ultrasonic imaging has become one of the most rapidly advancing technologies. These rapid advances are directly related to the parallel advancements in electronics, computing, and transducer technology together with sophisticated signal processing techniques. This book focuses on state of the art developments in ultrasonic imaging applications and underlying technologies presented by leading practitioners and researchers from many parts of the world

Model-based Filtering of Interfering Signals in Ultrasonic Time Delay Estimations

In dieser Arbeit werden modellbasierte algorithmische Ansätze zur Interferenz-invarianten Zeitverschiebungsschätzung vorgestellt, die speziell für die Schätzung kleiner Zeitverschiebungsdifferenzen mit einer notwendigen Auflösung, die deutlich unterhalb der Abtastzeit liegt, geeignet sind. Daher lassen sich die Verfahren besonders gut auf die Laufzeit-basierte Ultraschalldurchflussmessung anwenden, da hier das Problem der Interferenzsignale besonders ausgeprägt ist. Das Hauptaugenmerk liegt auf der Frage, wie mehrere Messungen mit unterschiedlichen Zeitverschiebungen oder Prozessparametern zur Unterdrückung der Interferenzsignale in Ultraschalldurchflussmessungen verwendet werden können, wobei eine gute Robustheit gegenüber additivem weißen Gauß\u27schen Rauschen und eine hohe Auflösung erhalten bleiben sollen. Zu diesem Zweck wird ein Signalmodell angenommen, welches aus stationären Interferenzsignalen, die nicht von wechselnden Zeitverschiebungen abhängig sind, und aus Zielsignalen, die den Messeffekt enthalten, besteht. Zunächst wird das Signalmodell einer Ultraschalldurchflussmessung und sein dynamisches Verhalten bei Temperatur- oder Zeitverschiebungsschwankungen untersucht. Ziel ist es, valide Simulationsdatensätze zu erzeugen, mit denen die entwickelten Methoden sowohl unter der Prämisse, dass die Daten perfekt zum Signalmodell passen, als auch unter der Prämisse, dass Modellfehler vorliegen, getestet werden können. Dabei werden die Eigenschaften der Signalmodellkomponenten, wie Bandbreite, Stationarität und Temperaturabhängigkeit, identifiziert. Zu diesem Zweck wird eine neue Methode zur Modellierung der Temperaturabhängigkeit der Interferenzsignale vorgestellt. Nach der Charakterisierung des gesamten Messsystems wird das Signalmodell -- angepasst an die Ultraschalldurchflussmessung -- als Grundlage für zwei neue Methoden verwendet, deren Ziel es ist, die Auswirkungen der Interferenzsignale zu reduzieren. Die erste vorgeschlagene Technik erweitert die auf der Signaldynamik basierenden Ansätze in der Literatur, indem sie die Voraussetzungen für die erforderliche Varianz der Zeitverschiebungen abschwächt. Zu diesem Zweck wird eine neue Darstellung von mehreren Messsignalen als Punktwolken eingeführt. Die Punktwolken werden dann mithilfe der Hauptkomponentenanalyse und B-Splines verarbeitet, was entweder zu Interferenz-invarianten Zeitverschiebungsschätzungen oder geschätzten Interferenzsignalen führt. In diesem Zusammenhang wird eine neuartige gemeinsame B-Spline- und Registrierungsschätzung entwickelt, um die Robustheit zu erhöhen. Der zweite Ansatz besteht in einer regressionsbasierten Schätzung der Zeitverschiebungsdifferenzen durch das Erlernen angepasster Signalunterräume. Diese Unterräume werden effizient durch die Analytische Wavelet Packet Transformation berechnet, bevor die resultierenden Koeffizienten in Merkmale transformiert werden, die gut mit den Zeitverschiebungssdifferenzen korrelieren. Darüber hinaus wird ein neuartiger, unbeaufsichtigter Unterraum-Trainingsansatz vorgeschlagen und mit den konventionellen Filter- und Wrapper-basierten Merkmalsauswahlmethoden verglichen. Schließlich werden beide Methoden in einem experimentellen Ultraschalldurchflussmesssystem mit einem hohen Maß an vorhandenen Interferenzsignalen getestet, wobei sich zeigt, dass sie in den meisten Fällen den Methoden aus der Literatur überlegen sind. Die Qualität der Methoden wird anhand der Genauigkeit der Zeitverschiebungsschätzung bewertet, da die Grundwahrheit für die Interferenzsignale nicht zuverlässig bestimmt werden kann. Anhand verschiedener Datensätze werden die Abhängigkeiten von den Hyperparametern, den Prozessbedingungen und, im Falle der regressionsbasierten Methode, dem Trainingsdatensatz analysiert

Model-based Filtering of Interfering Signals in Ultrasonic Time Delay Estimations

This work presents model-based algorithmic approaches for interference-invariant time delay estimation, which are specifically suited for the estimation of small time delay differences with a necessary resolution well below the sampling time. Therefore, the methods can be applied particularly well for transit-time ultrasonic flow measurements, since the problem of interfering signals is especially prominent in this application

Model-based Filtering of Interfering Signals in Ultrasonic Time Delay Estimations

This work presents model-based algorithmic approaches for interference-invariant time delay estimation, which are specifically suited for the estimation of small time delay differences with a necessary resolution well below the sampling time. Therefore, the methods can be applied particularly well for transit-time ultrasonic flow measurements, since the problem of interfering signals is especially prominent in this application

AGV RAD: AGV positioning system for ports using microwave doppler radar

Automation and intelligence have become an inevitable trend in the development of container terminals. The AGV (Automated Guided Vehicle) positioning is a primary problem to build the automated ports. Although the existing Ultra-High Frequency(UHF) RFID technology has good measurement accuracy and stability in the port AGV positioning, the exposed magnetic tags are easy to damage under the common heavy load, and its construction and maintenance cost is unbearable to most ports. Among the candidate technologies for the AGV positioning, microwave Doppler radar has a strong penetrating ability, and can work well in a complex environment (day and night, foggy, rainy). Therefore, the microwave Doppler radar-based AGV positioning system has attracted a lot of attention. In this thesis, a test system using the above technique was established, together with a NI myRIO real-time Wi-Fi compatible computation platform. Several computation algorithms were implemented to extract the accurate values of range and velocity. Wavelet denoising with the adapted threshold function was considered to filter noise contained in radar signals. In the frequency domain analysis, FFT and Chirp-Z Transform (CZT) joint algorithm was proposed to suppress the influence of fence effects and also improves real-time performance. In addition, 2D-FFT is used to calculate velocity of AGV. According to the port-like environment, the suitable AGV positioning algorithm and communication method based on microwave Doppler radars and NI myRIO-1900s also be proposed. The effectiveness of the proposed system was experimentally tested and several results are included in this thesis.Automação e inteligência artifical tornaram-se uma tendência inevitável no desenvolvimento dos terminais dos contentores. O posicionamento do VAG (Veículo Autónomo Guiado) é um dos problemas principais para construir as portas automatizadas. Embora a tecnologia RFID de frequência ultra-alta (UHF) existente tenha uma boa precisão e estabilidade de medição no posicionamento VAG dos portos, as etiquetas magnéticas expostas são fáceis de danificar sob a comum carga pesada e o seu habitual custo de construção e manutenção é insuportável para a maioria das portos. Entre as tecnologias para o posicionamento VAG, o radar Doppler de microondas possui uma forte capacidade de penetração e pode funcionar bem em ambientes complexos (dia, noite, nevoeiro e chuva). Portanto, o sistema de posicionamento VAG baseado em radar Doppler de microondas atraiu muita atenção. Nesta tese, foi estabelecido um sistema de teste usando a técnica acima mencionada, juntamente com uma plataforma de computação em tempo real, NI myRIO compatível com Wi-Fi. Vários algoritmos de computação foram envolvidos para extrair os valores precisos de distancia e velocidade. O “denoising” de wavelets com a função de limiar adaptado foi utilizado para filtrar o ruído nos sinais de radar. Na análise do domínio da frequência, o algoritmo conjunto FFT e Chirp-Z Transform (CZT) foi proposto para suprimir a influência dos efeitos de resolução e também melhorar o desempenho em tempo real. Além disso, o algoritmo 2D-FFT é usado para calcular a velocidade do VAG. De acordo com o ambiente dos portos, o algoritmo de posicionamento VAG e o método de comunicação adequado baseados em radares Doppler de microondas e NI myRIO-1900s também serão propostos. A eficiência do sistema proposto foi testada experimentalmente e vários resultados estão descritos nesta dissertação

Five Facets of 6G: Research Challenges and Opportunities

Whilst the fifth-generation (5G) systems are being rolled out across the globe, researchers have turned their attention to the exploration of radical next-generation solutions. At this early evolutionary stage we survey five main research facets of this field, namely {\em Facet~1: next-generation architectures, spectrum and services, Facet~2: next-generation networking, Facet~3: Internet of Things (IoT), Facet~4: wireless positioning and sensing, as well as Facet~5: applications of deep learning in 6G networks.} In this paper, we have provided a critical appraisal of the literature of promising techniques ranging from the associated architectures, networking, applications as well as designs. We have portrayed a plethora of heterogeneous architectures relying on cooperative hybrid networks supported by diverse access and transmission mechanisms. The vulnerabilities of these techniques are also addressed and carefully considered for highlighting the most of promising future research directions. Additionally, we have listed a rich suite of learning-driven optimization techniques. We conclude by observing the evolutionary paradigm-shift that has taken place from pure single-component bandwidth-efficiency, power-efficiency or delay-optimization towards multi-component designs, as exemplified by the twin-component ultra-reliable low-latency mode of the 5G system. We advocate a further evolutionary step towards multi-component Pareto optimization, which requires the exploration of the entire Pareto front of all optiomal solutions, where none of the components of the objective function may be improved without degrading at least one of the other components

Multibiometric security in wireless communication systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 05/08/2010.This thesis has aimed to explore an application of Multibiometrics to secured wireless communications. The medium of study for this purpose included Wi-Fi, 3G, and WiMAX, over which simulations and experimental studies were carried out to assess the performance. In specific, restriction of access to authorized users only is provided by a technique referred to hereafter as multibiometric cryptosystem. In brief, the system is built upon a complete challenge/response methodology in order to obtain a high level of security on the basis of user identification by fingerprint and further confirmation by verification of the user through text-dependent speaker recognition. First is the enrolment phase by which the database of watermarked fingerprints with memorable texts along with the voice features, based on the same texts, is created by sending them to the server through wireless channel. Later is the verification stage at which claimed users, ones who claim are genuine, are verified against the database, and it consists of five steps. Initially faced by the identification level, one is asked to first present one’s fingerprint and a memorable word, former is watermarked into latter, in order for system to authenticate the fingerprint and verify the validity of it by retrieving the challenge for accepted user. The following three steps then involve speaker recognition including the user responding to the challenge by text-dependent voice, server authenticating the response, and finally server accepting/rejecting the user. In order to implement fingerprint watermarking, i.e. incorporating the memorable word as a watermark message into the fingerprint image, an algorithm of five steps has been developed. The first three novel steps having to do with the fingerprint image enhancement (CLAHE with 'Clip Limit', standard deviation analysis and sliding neighborhood) have been followed with further two steps for embedding, and extracting the watermark into the enhanced fingerprint image utilising Discrete Wavelet Transform (DWT). In the speaker recognition stage, the limitations of this technique in wireless communication have been addressed by sending voice feature (cepstral coefficients) instead of raw sample. This scheme is to reap the advantages of reducing the transmission time and dependency of the data on communication channel, together with no loss of packet. Finally, the obtained results have verified the claims

Photodetectors

In this book some recent advances in development of photodetectors and photodetection systems for specific applications are included. In the first section of the book nine different types of photodetectors and their characteristics are presented. Next, some theoretical aspects and simulations are discussed. The last eight chapters are devoted to the development of photodetection systems for imaging, particle size analysis, transfers of time, measurement of vibrations, magnetic field, polarization of light, and particle energy. The book is addressed to students, engineers, and researchers working in the field of photonics and advanced technologies