Discrete Wavelet Transforms

The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications

Fatigue reliability of ship structures

Today we are sitting on a huge wealth of structural reliability theory but its application in ship design and construction is far behind. Researchers and practitioners face a daunting task of dove-tailing the theoretical achievements into the established processes in the industry. The research is aimed to create a computational framework to facilitate fatigue reliability of ship structures. Modeling, transformation and optimization, the three key elements underlying the success of computational mechanics are adopted as the basic methodology through the research. The whole work is presented in a way that is most suitable for software development. The foundation of the framework is constituted of reliability methods at component level. Looking at the second-moment reliability theory from a minimum distance point of view the author derives a generic set of formulations that incorporate all major first and second order reliability methods (FORM, SORM). Practical ways to treat correlation and non- Gaussian variables are discussed in detail. Monte Carlo simulation (MCS) also accounts for significant part of the research with emphasis on variance reduction techniques in a proposed Markov chain kernel method. Existing response surface methods (RSM) are reviewed and improved with much weight given to sampling techniques and determination of the quadratic form. Time-variant problem is touched upon and methods to convert it to nested reliability problems are discussed. In the upper layer of the framework common fatigue damage models are compared. Random process simulation and rain-flow counting are used to study effect of wide-banded non-Gaussian process. At the center of this layer is spectral fatigue analysis based on SN curve and first-principle stress and hydrodynamic analysis. Pseudo-excitation is introduced to get linear equivalent stress RAO in the non-linear ship-wave system. Finally response surface method is applied to this model to calculate probability of failure and design sensitivity in the case studies of a double hull oil tanker and a bulk carrier

The use of geometric uncertainty data in aero engine structural analysis and design

A gas turbine disc has three critical regions for which lifing calculations are essential: the assembly holes or weld areas, the hub region, and the blade-disc attachment area. Typically, a firtree joint is used to attach the blades to the turbine disc instead of a dove-tail joint, which is commonly used for compressor discs. A firtree joint involves contact between two surfaces at more than one location which makes the joint more difficult to design. Large loads generated due to the centrifugal action of the disc and associated blades are distributed over multiple areas of contact within the joint. All of the contacts in a firtree joint are required to be engaged simultaneously when the blades are loaded. However, slight variations in the manufacture of these components can have an impact on this loading. It is observed that small changes in the geometric entities representing contact between the two bodies can result in variations in the stress distribution near contact edges and the notch regions. Even though manufacturing processes have advanced considerably in the last few decades, the variations in geometry due to these processes cannot be completely eliminated. Hence, it is necessary to design such components in the presence of uncertainties in order to minimise the variation observed in their performance. In this work, the variations in geometry due to the manufacturing processes used to produce firtree joints between a gas turbine blade and the disc are evaluated. These variations are represented in two different ways using measurement data of firtree joints obtained from a coordinate measuring machine (CMM): (i) the variation for the pressure angle in the firtree joint is extracted from a simple curve fit and (ii) using the same measurement data, the unevenness of the pressure surfaces is represented using a Fourier series after filtering noise components. A parametric computer aided design (CAD) model which represents the manufacturing variability is implemented using Siemens NX. Non-smooth surfaces are also numerically generated by assuming the surface profile to be a random process. Two- and three-dimensional elastic stress analysis is carried out on the firtree joint using the finite element code, Abaqus and the variations observed in the notch stresses with changing pressure angle are extracted. A surrogate assisted multiobjective optimisation is performed on the firtree joint based on the robustness principles. Kriging based models are used to build a surrogate for notch stresses and the non-dominated sorting genetic algorithm-II (NSGA-II) is implemented to perform a multiobjective optimisation in order to minimise the mean and standard deviation of the notch stresses. An iterative search algorithm that updates the Kriging models with equally spaced infill points from the predicted Pareto front is adopted. Finally, a new design of the firtree joint is obtained which has better performance with respect to the variation in the notch stresses due to manufacturing uncertainties

Modelling surface topography from reflected light.

This thesis is concerned with the use of the modulus of the Fourier spectrum to characterise object features and also to reconstruct object surfaces in the complete absence of phase information. In general, a phaseless synthesis is completely meaningless and many characteristic features of the object are obliterated when the modulus of the spectral components is inverse Fourier transformed with zero phase. However, the outcome is different when the object possesses some form of regularity and repetition in its characteristics. In such circumstances, the utilisation of both the modulus and the intensity of the spatial spectrum can reveal information regarding the characteristic features of the object surface. The first part of this research has utilised the intensity of the spectral components as a means of surface feature characterisation in the study of a machined surface. Two separate approaches were adopted for assessing the zero-phase images. Both the optically recorded Fourier spectrum and the computer simulated Fourier spectrum were used to extract surface related parameters in the zero-phase synthesis. Although merely a characterisation, the zero-phase synthesis of the spectral components revealed periodic behaviour very similar to that present in the original surface. The presence of such cyclic components was confirmed by their presence in travelling microscope images and in scanning electron microscope images of the surface. Additionally, a novel approach has been adopted to recover finer periodicities on the surface. The scale sensitivity of the frequency domain fosters an exceptional means through which digital magnification can be performed with the added advantage that it is accompanied by enhanced resolution. Magnification realised through spatial frequency data is by far superior to any spatial domain magnification. However, there are limitations to this approach. The second part of this research has been centred around the possible use of a non-iteratively based approach for extracting the unknown phases from the modulus of the Fourier spectrum and thus retrieving the 3-D geometrical structure of the unknown object surface as opposed to characterising its profile. The logarithmic Hilbert transform is one such approach which allows a non-iterative means of extracting unknown phases from the modulus of the Fourier spectrum. However, the technique is only successful for object surfaces which are well-behaved and display well-behaved spectral characteristics governed by continuity. For real object surfaces where structure, definition and repetition governs the characteristics, the spectrum is not well behaved. The spectrum is populated by maxi ma, minima and many isolated regions which are occupied by colonies of zeros disrupting the continuity. A new and unique approach has been devised by the author to reform the spectral behaviour of real object surfaces without affecting the fidelity that it conveys. The resultant information enables phase extraction to be achieved through the logarithmic Hilbert transform. It is possible to reform the spread of spectral behaviour to cultivate better continuity amongst its spectral components through an object scale change. The combination of the logarithmic Hilbert transform and the Fourier scaling principle has led to a new approach for extracting the unknown phases for real object structures which would otherwise have been impossible to perform through the use of Hilbert transformation alone. The validity of the technique has been demonstrated in a series of simulations conducted on one-dimensional objects as well as the two-dimensional object specimens. The limitations of the approach, improvements and the feasibility for practical implementation are ail issues which have been addressed

Pattern Recognition

A wealth of advanced pattern recognition algorithms are emerging from the interdiscipline between technologies of effective visual features and the human-brain cognition process. Effective visual features are made possible through the rapid developments in appropriate sensor equipments, novel filter designs, and viable information processing architectures. While the understanding of human-brain cognition process broadens the way in which the computer can perform pattern recognition tasks. The present book is intended to collect representative researches around the globe focusing on low-level vision, filter design, features and image descriptors, data mining and analysis, and biologically inspired algorithms. The 27 chapters coved in this book disclose recent advances and new ideas in promoting the techniques, technology and applications of pattern recognition

Advances in Sonar Technology

The demand to explore the largest and also one of the richest parts of our planet, the advances in signal processing promoted by an exponential growth in computation power and a thorough study of sound propagation in the underwater realm, have lead to remarkable advances in sonar technology in the last years.The work on hand is a sum of knowledge of several authors who contributed in various aspects of sonar technology. This book intends to give a broad overview of the advances in sonar technology of the last years that resulted from the research effort of the authors in both sonar systems and their applications. It is intended for scientist and engineers from a variety of backgrounds and even those that never had contact with sonar technology before will find an easy introduction with the topics and principles exposed here

UAVs for the Environmental Sciences

This book gives an overview of the usage of UAVs in environmental sciences covering technical basics, data acquisition with different sensors, data processing schemes and illustrating various examples of application

Autocalibrating vision guided navigation of unmanned air vehicles via tactical monocular cameras in GPS denied environments

This thesis presents a novel robotic navigation strategy by using a conventional tactical monocular camera, proving the feasibility of using a monocular camera as the sole proximity sensing, object avoidance, mapping, and path-planning mechanism to fly and navigate small to medium scale unmanned rotary-wing aircraft in an autonomous manner. The range measurement strategy is scalable, self-calibrating, indoor-outdoor capable, and has been biologically inspired by the key adaptive mechanisms for depth perception and pattern recognition found in humans and intelligent animals (particularly bats), designed to assume operations in previously unknown, GPS-denied environments. It proposes novel electronics, aircraft, aircraft systems, systems, and procedures and algorithms that come together to form airborne systems which measure absolute ranges from a monocular camera via passive photometry, mimicking that of a human-pilot like judgement. The research is intended to bridge the gap between practical GPS coverage and precision localization and mapping problem in a small aircraft. In the context of this study, several robotic platforms, airborne and ground alike, have been developed, some of which have been integrated in real-life field trials, for experimental validation. Albeit the emphasis on miniature robotic aircraft this research has been tested and found compatible with tactical vests and helmets, and it can be used to augment the reliability of many other types of proximity sensors