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020			_a9789811020315 _q(print)
020			_a9789811020322 _q(electronic bk.)
020			_a9811020310 _q(print)
020			_a9811020329 _q(electronic bk.)
020			_z9789811020315 _q(print)
035			_a(OCoLC)954214872 _z(OCoLC)957615932
040			_aN$T _cN$T _dYDXCP _dIDEBK _dGW5XE _dEBLCP _dOCLCF _dN$T _dYDX _dCOO _dOCLCQ _dIOG _dESU _dZ5A _dJBG _dIAD _dICW _dICN _dILO _dOTZ _dOCLCQ _dU3W _dES-MaUEC _bspa
050		4	_aTA169.6 _bN584 2016 EB
100	1		_aNiu, Gang, _eautor
245	1	0	_aData-driven technology for engineering systems health management : _bdesign approach, feature construction, fault diagnosis, prognosis, fusion and decisions _cGang Niu.
264		1	_aSingapore _bSpringer ; _aBeijing, China _bScience Press _c[2016]
264		4	_c2017
300			_a1 recurso en línea (xiii, 357 páginas) _bilustraciones
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
500			_aSpringerLink _bSpringer Engineering eBooks 2017 English+International
504			_aIncluye referencias bibliográficas e índice
505	0		_aPreface; Acknowledgements; Contents; 1 Background of Systems Health Management; 1.1 Introduction; 1.2 Maintenance Strategy; 1.3 From Maintenance to PHM; 1.4 Definitions and Terms of Systems Health Management; 1.5 Preface to Book Chapters; References; 2 Design Approach for Systems Health Management; 2.1 Introduction; 2.2 Systems Engineering; 2.3 Systems Engineering, Dependability, and Health Management; 2.4 SHM Lifecycle Stages; 2.4.1 Research Stage; 2.4.2 Requirements Development Stage; 2.4.3 System/Functional Analysis; 2.4.4 Design, Synthesis, and Integration.
505	8		_a2.4.5 System Test and Evaluation2.4.6 HM System Maturation; 2.5 A Systems-Based Methodology for PHM/CBM Design; 2.6 A Proposed PHM Design Approach for Rotary Machinery Systems; References; 3 Overview of Data-Driven PHM; 3.1 Introduction; 3.2 PHM Technical Approaches; 3.3 Data-Driven PHM/CBM System Architecture; 3.4 Role of Condition Monitoring, Fault Diagnosis, and Prognosis; 3.5 Fault Diagnosis Framework; 3.6 Problems During Implementation; 3.7 Related Techniques; References; 4 Data Acquisition and Preprocessing; 4.1 Introduction; 4.2 Data Acquisition; 4.2.1 Selecting a Proper Measure.
505	8		_a4.2.2 Vibration Transducers4.2.3 Transducer Selection; 4.2.4 Transducer Mounting; 4.2.5 Transducer Location; 4.2.6 Frequency Span; 4.2.7 Data Display; 4.3 Data Processing; 4.4 Data Analysis; 4.4.1 Features in Time Domain; 4.4.2 Features in Frequency Domain; 4.4.3 Features in Time-Frequency Domain; References; 5 Statistic Feature Extraction; 5.1 Introduction; 5.2 Basic Concepts; 5.2.1 Pattern and Feature Vector; 5.2.2 Class; 5.3 Parameter Evaluation Technique; 5.4 Principal Component Analysis (PCA); 5.5 Independent Component Analysis (ICA); 5.6 Kernel PCA; 5.7 Kernel ICA.
505	8		_a5.8 Fisher Discriminant Analysis (FDA)5.9 Linear Discriminant Analysis (LDA); 5.10 Generalized Discriminant Analysis (GDA); 5.11 Clustering; 5.11.1 k-Centers Clustering; 5.11.2 k-Means Clustering; 5.11.3 Hierarchical Clustering; 5.12 Other Techniques; References; 6 Feature Selection Optimization; 6.1 Introduction; 6.2 Individual Feature Evaluation (IFE); 6.3 Conditional Entropy; 6.4 Backward Feature Selection; 6.5 Forward Feature Selection; 6.6 Branch and Bound Feature Selection; 6.7 Plus l-Take Away r Feature Selection; 6.8 Floating Forward Feature Selection.
505	8		_a6.9 Distance-Based Evaluation Technique6.10 Taguchi Method-Based Feature Selection; 6.11 Genetic Algorithm; 6.11.1 General Concept; 6.11.2 Differences from Other Traditional Methods; 6.11.3 Simple Genetic Algorithm (SGA); 6.11.4 Feature Selection Using GA; 6.12 Summary; References; 7 Intelligent Fault Diagnosis Methodology; 7.1 Introduction; 7.2 Linear Classifier; 7.2.1 Linear Separation of Finite Set of Vectors; 7.2.2 Perceptron Algorithm; 7.2.3 Kozinec's Algorithm; 7.2.4 Multi-class Linear Classifier; 7.3 Quadratic Classifier; 7.4 Bayesian Classifier; 7.5 k-Nearest Neighbors (k-NN).
520	3		_aThis book introduces condition-based maintenance (CBM)/data-driven prognostics and health management (PHM) in detail, first explaining the PHM design approach from a systems engineering perspective, then summarizing and elaborating on the data-driven methodology for feature construction, as well as feature-based fault diagnosis and prognosis. The book includes a wealth of illustrations and tables to help explain the algorithms, as well as practical examples showing how to use this tool to solve situations for which analytic solutions are poorly suited. It equips readers to apply the concepts discussed in order to analyze and solve a variety of problems in PHM system design, feature construction, fault diagnosis and prognosis.
650		7	_aDiagnóstico de fallos _2embne _0(OCoLC)fst00921982 _0 _9669484
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=http://link.springer.com/10.1007/978-981-10-2032-2 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
988			_aEBOOK, asignarmaterias, EBSPRINGER_2017A
998			_b02/2018 _dz _e- _zSI
999			_c94448 _d94448 _x1