Inverse Problems In Physical Diagnostics

Unlike direct problems related to the solution of differential equations, inverse problems are typically expressed by integral equations. These equations relate media parameters to parameters of a measured signal, or input parameters to output ones in various measurement systems. The solution of integral equations is, with few exceptions, an ill-posed problem, and additional a priori information about the exact solution should be used to solve such problems. The specific character of the a priori information determines various regularisation methods that are in use here to obtain an approximate solution: Tikhonov's method, statistical regularisation method, methods based on the use of additional equations or restrictions or of models with limited number of unknown parameters. The main point of this book is the study of convergence properties of each method and the wide application of numerical modelling that gives the accuracy of the solution in a chosen metric. It is an unaccustomed procedure for physicists, but, because there is no proportionality between data and solution errors in ill-posed problems, such approach is inevitable.

This research monograph presents a systematic treatment of the theory of the propagation of transient electromagnetic fields (such as optical pulses) through dielectric media which exhibit both dispersion a.nd absorption. The work divides naturally into two parts. Part I presents a summary of the fundamental theory of the radiation and propagation of rather general electromagnetic waves in causal, linear media which are homogeneous and isotropic but which otherwise have rather general dispersive and absorbing properties. In Part II, we specialize to the propagation of a plane, transient electromagnetic field in a homogeneous dielectric. Although we have made some contributions to the fundamental theory given in Part I, most of the results of our own research appear in Part II. The purpose of the theory presented in Part II is to predict and to explain in explicit detail the dynamics of the field after it has propagated far enough through the medium to be in the mature-dispersion regime. It is the subject of a classic theory, based on the research conducted by A. Sommerfeld and L.

This book presents a methodology based on inverse problems for use in solutions for fault diagnosis in control systems, combining tools from mathematics, physics, computational and mathematical modeling, optimization and computational intelligence. This methodology, known as fault diagnosis – inverse problem methodology or FD-IPM, unifies the results of several years of work of the authors in the fields of fault detection and isolation (FDI), inverse problems and optimization. The book clearly and systematically presents the main ideas, concepts and results obtained in recent years. By formulating fault diagnosis as an inverse problem, and by solving it using metaheuristics, the authors offer researchers and students a fresh, interdisciplinary perspective for problem solving in these fields. Graduate courses in engineering, applied mathematics and computing also benefit from this work.

This book describes unified image-based measurement methods (theories, numerical methods, and algorithms) to determine the important physical quantities of complex flows in engineering and natural systems, including velocity, pressure, temperature, heat transfer, and skin friction. It presents a systematical study of the inverse problems in global flow diagnostics in a unified framework of the variational formulations. The authors further illustrate the main physical quantities in fluid mechanics, including velocity, pressure, skin friction and surface heat flux, extracted from flow visualization images obtained in experiments and observations. The developed methods are applicable in various image-based flow measurements in diverse disciplines ranging from fluid mechanics/aerodynamics to plenary sciences.

This book provides readers with an overview of recent theories and methods for machinery diagnostics applied to machinery maintenance. Each chapter, accepted after a rigorous peer-review process, reports on a selected, original piece of work discussed at the International Congress on Technical Diagnostics, ICTD2016, held on September 12 – 16, 2016, in Gliwice, Poland. The book covers a broad range of topics, including machines operating in non-stationary conditions, and examples from different industrial fields of mechanical, civil, computer and electronic engineering as well as the medical, food, automotive, and mining industries. By presenting state-of-the-art diagnostic solutions and discussing important industrial issues the book offers a valuable resource to both academics and professionals as well as a bridge to facilitate communication and collaboration between the two groups.

This is the first book to offer a comprehensive exploration of new methods in inverse problems in electromagnetics. The book provides systematic descriptions of the most important practical inverse problems, and details new methods to solve them. Also included are descriptions of the properties of inverse problems and known solutions, as well as reviews of the practical implementation of these methods in electric circuit theory and electromagnetic fields theory. This comprehensive collection of modern theoretical ideas and methods to solve inverse problems will be of value to both students and working professionals.

The purpose of this book is to present a methodology for designing and tuning fuzzy expert systems in order to identify nonlinear objects; that is, to build input-output models using expert and experimental information. The results of these identifications are used for direct and inverse fuzzy evidence in forecasting and diagnosis problem solving. The book is organised as follows: Chapter 1 presents the basic knowledge about fuzzy sets, genetic algorithms and neural nets necessary for a clear understanding of the rest of this book. Chapter 2 analyzes direct fuzzy inference based on fuzzy if-then rules. Chapter 3 is devoted to the tuning of fuzzy rules for direct inference using genetic algorithms and neural nets. Chapter 4 presents models and algorithms for extracting fuzzy rules from experimental data. Chapter 5 describes a method for solving fuzzy logic equations necessary for the inverse fuzzy inference in diagnostic systems. Chapters 6 and 7 are devoted to inverse fuzzy inference based on fuzzy relations and fuzzy rules. Chapter 8 presents a method for extracting fuzzy relations from data. All the algorithms presented in Chapters 2-8 are validated by computer experiments and illustrated by solving medical and technical forecasting and diagnosis problems. Finally, Chapter 9 includes applications of the proposed methodology in dynamic and inventory control systems, prediction of results of football games, decision making in road accident investigations, project management and reliability analysis.

No detailed description available for "Ill-Posed Problems in Natural Sciences".