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006			m o d
007			cr cnu---unuuu
008			170628s2017 si ob 001 0 eng d
020			_a9789811041174
020			_a9789811041181 _q(electronic bk.)
020			_a9811041172
020			_a9811041180 _q(electronic bk.)
020			_z9789811041174
040			_aN$T _cN$T _dN$T _dEBLCP _dGW5XE _dUAB _dYDX _dAZU _dUPM _dOCLCF _dMERER _dESU _dOCLCQ _dCOO _dOCLCQ _dVT2 _dIOG _dES-MaUEC _bspa
050		4	_aTA654.15 _bA975 2017 EB
100	1		_aAu, Siu-Kui, _eautor
245	1	0	_aOperational modal analysis : _bmodeling, bayesian inference, uncertainty laws _cSiu-Kui Au.
264		1	_aSingapore _bSpringer _c2017.
300			_a1 recurso en línea
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF
500			_aSpringerLink _bSpringer Engineering eBooks 2017 English+International
504			_aIncluye referencias bibliográficas e índice
505	0		_aIntroduction -- Spectral Analysis of Deterministic Process -- Structural Dynamics -- Spectral Analysis of Stationary Stochastic Process -- Stochastic Structural Dynamics -- Ambient Data Analysis and Simulation -- Bayesian Inference -- Classical Statistical Inference -- Bayesian OMA Framework -- Single Mode Problem -- Multi-Mode Problem -- Multi-Setup Problem -- Managing identification uncertainty -- Theory of Uncertainty Laws.
520	3		_aThis book presents operational modal analysis (OMA), employing a coherent and comprehensive Bayesian framework for modal identification and covering stochastic modeling, theoretical formulations, computational algorithms, and practical applications. Mathematical similarities and philosophical differences between Bayesian and classical statistical approaches to system identification are discussed, allowing their mathematical tools to be shared and their results correctly interpreted. Many chapters can be used as lecture notes for the general topic they cover beyond the OMA context. After an introductory chapter (1), Chapters 2-7 present the general theory of stochastic modeling and analysis of ambient vibrations. Readers are first introduced to the spectral analysis of deterministic time series (2) and structural dynamics (3), which do not require the use of probability concepts. The concepts and techniques in these chapters are subsequently extended to a probabilistic context in Chapter 4 (on stochastic processes) and in Chapter 5 (on stochastic structural dynamics). In turn, Chapter 6 introduces the basics of ambient vibration instrumentation and data characteristics, while Chapter 7 discusses the analysis and simulation of OMA data, covering different types of data encountered in practice. Bayesian and classical statistical approaches to system identification are introduced in a general context in Chapters 8 and 9, respectively. Chapter 10 provides an overview of different Bayesian OMA formulations, followed by a general discussion of computational issues in Chapter 11. Efficient algorithms for different contexts are discussed in Chapters 12-14 (single mode, multi-mode, and multi-setup). Intended for readers with a minimal background in mathematics, Chapter 15 presents the 'uncertainty laws' in OMA, one of the latest advances that establish the achievable precision limit of OMA and provide a scientific basis for planning ambient vibration tests. Lastly Chapter 16 discusses the mathematical theory behind the results in Chapter 15, addressing the needs of researchers interested in learning the techniques for further development. Three appendix chapters round out the coverage. This book is primarily intended for graduate/senior undergraduate students and researchers, although practitioners will also find the book a useful reference guide. It covers materials from introductory to advanced level, which are classified accordingly to ensure easy access. Readers with an undergraduate-level background in probability and statistics will find the book an invaluable resource, regardless of whether they are Bayesian or non-Bayesian.
650		7	_aAnálisis estructural (Ingeniería) _2embne _0(OCoLC)fst01024347 _0 _9150495
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=http://link.springer.com/10.1007/978-981-10-4118-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
988			_aEBOOK, asignarmaterias, EBSPRINGER_2017D
998			_b02/2018 _dz _e- _zSI
999			_c96267 _d96267 _x1