LEADER 05163nam 2200637 450 001 9910140498703321 005 20200520144314.0 010 $a1-118-63876-X 010 $a1-118-63874-3 010 $a1-118-63875-1 035 $a(CKB)2670000000577991 035 $a(EBL)1866794 035 $a(SSID)ssj0001382820 035 $a(PQKBManifestationID)11746303 035 $a(PQKBTitleCode)TC0001382820 035 $a(PQKBWorkID)11474672 035 $a(PQKB)11479121 035 $a(MiAaPQ)EBC1866794 035 $a(DLC) 2014028164 035 $a(Au-PeEL)EBL1866794 035 $a(CaPaEBR)ebr10990965 035 $a(CaONFJC)MIL664770 035 $a(OCoLC)897021490 035 $a(PPN)249289288 035 $a(EXLCZ)992670000000577991 100 $a20140625d2015 uy| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMachinery prognostics and prognosis oriented maintenance management /$fJihong Yan 210 1$aSingapore :$cWiley,$d2015. 215 $a1 online resource (356 p.) 300 $aDescription based upon print version of record. 311 $a1-322-33488-9 311 $a1-118-63872-7 320 $aIncludes bibliographical references and index. 327 $aMachine generated contents note: Preface i Acknowledgements i Chapter 1 Introduction 7 1.1 Historical perspective 7 1.2 Diagnostic and prognostic system requirements 8 1.3 Need for prognostics and sustainability based maintenance management 9 1.4 Technical challenges in prognosis and sustainability based maintenance decision making 11 1.5 Data processing, prognostics and decision making 13 1.6 Sustainability based maintenance management 16 1.7 Future of prognostics based maintenance 19 References 20 Chapter 2 Data processing 21 2.1 Probability Distributions 21 2.2 Statistics on Unordered data 32 2.3 Statistics on Ordered Data 38 2.4 Technologies for incomplete data 39 References 428 Chapter 3 Signal processing 45 3.1 Introduction 45 3.2 Signal pre-processing 47 3.3 Techniques for signal processing 50 3.4 Real-time image feature extraction 72 3.5 Fusion or integration technologies 77 3.6 Statistical pattern recognition and data mining 80 3.7 Advanced technology for feature extraction 92 References 102 Chapter 4 Health monitoring and prognosis 110 4.1 Health monitoring as a concept 110 4.2 Degradation indices 111 4.3 Real-time monitoring 116 4.4 Failure prognosis 142 4.5 Physics-based prognosis models 155 4.6 Data-driven prognosis models 158 4.7 Hybrid prognosis models 162 Reference 165 Chapter 5 Prediction of residual service life 172 5.1 Formulation of problem 172 5.2 Methodology of probabilistic prediction 173 5.3 Dynamic life prediction using time series 180 5.4 Residual life prediction by crack-growth criterion 197 References 202 Chapter 6 Maintenance planning and scheduling 205 6.1 Strategic planning in maintenance 205 6.2 Maintenance scheduling 219 6.3 Scheduling techniques 232 6.4 Heuristic methodology for multi-unit system maintenance scheduling 261 References 266 Chapter 7 Prognosis incorporating maintenance decision making 270 7.1 The changing role of maintenance 270 7.2 Development of maintenance 272 7.3 Maintenance effects modeling 274 7.4 Modeling of optimization objective - maintenance cost 282 7.5 Prognosis oriented maintenance decision making 284 7.6 Maintenance decision making considering energy consumption 301 References 317 Chapter 8 Case studies 321 8.1 Improved Hilbert-Huang transform based weak signal detection methodology and its application on incipient fault diagnosis and ECG signal analysis 322 8.2 Ant colony clustering analysis based intelligent fault diagnosis method and its application to rotating machinery 329 8.3 BP Neural Networks Based Prognostic Methodology and Its Application 336 8.4 A Dynamic Multi-scale Markov Model Based Methodology for Remaining Life Prediction 343 8.5 A group technology based methodology for maintenance scheduling for hybrid shop 358 References 365 Index 369. 330 $a"This book gives a complete presentation of the basic essentials of machinery prognostics and prognosis oriented maintenance management, and takes a look at the cutting-edge discipline of intelligent failure prognosis technologies for condition-based maintenance. Latest research results and application methods are introduced for signal processing, reliability moelling, deterioration evaluation, residual life prediction and maintenance-optimization as well as applications of these methods"--$cProvided by publisher. 606 $aMachinery$xMaintenance and repair 606 $aMachinery$xService life 606 $aMachinery$xReliability 615 0$aMachinery$xMaintenance and repair. 615 0$aMachinery$xService life. 615 0$aMachinery$xReliability. 676 $a621.8/16 686 $aTEC032000$2bisacsh 700 $aYan$b Jihong$0860857 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910140498703321 996 $aMachinery prognostics and prognosis oriented maintenance management$91921026 997 $aUNINA