LEADER 03040nam 2200433 450 001 9910483039003321 005 20210320033029.0 010 $a3-030-60967-7 024 7 $a10.1007/978-3-030-60967-2 035 $a(CKB)4100000011665207 035 $a(MiAaPQ)EBC6427482 035 $a(DE-He213)978-3-030-60967-2 035 $a(PPN)252517989 035 $a(EXLCZ)994100000011665207 100 $a20210320d2021 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBond graph modelling for control, fault diagnosis and failure prognosis /$fWolfgang Borutzky 205 $a1st ed. 2021. 210 1$aCham, Switzerland :$cSpringer,$d[2021] 210 4$dİ2021 215 $a1 online resource (XVIII, 317 p. 199 illus., 127 illus. in color.) 311 $a3-030-60966-9 327 $aIntroduction -- Structural Properties of Bond Graphs for Model-based Control -- Fault Diagnosis -- Failure Prognostic -- Fault Tolerant Control -- Software -- Applications -- Conclusion and Discussion. 330 $aThis book shows in a comprehensive presentation how Bond Graph methodology can support model-based control, model-based fault diagnosis, fault accommodation, and failure prognosis by reviewing the state-of-the-art, presenting a hybrid integrated approach to Bond Graph model-based fault diagnosis and failure prognosis, and by providing a review of software that can be used for these tasks. The structured text illustrates on numerous small examples how the computational structure superimposed on an acausal bond graph can be exploited to check for control properties such as structural observability and control lability, perform parameter estimation and fault detection and isolation, provide discrete values of an unknown degradation trend at sample points, and develop an inverse model for fault accommodation. The comprehensive presentation also covers failure prognosis based on continuous state estimation by means of filters or time series forecasting. This book has been written for students specializing in the overlap of engineering and computer science as well as for researchers, and for engineers in industry working with modelling, simulation, control, fault diagnosis, and failure prognosis in various application fields and who might be interested to see how bond graph modelling can support their work. Presents a hybrid model-based, data-driven approach to failure prognosis Highlights synergies and relations between fault diagnosis and failure prognostic Discusses the importance of fault diagnosis and failure prognostic in various fields. 606 $aBond graphs 615 0$aBond graphs. 676 $a620.0015115 700 $aBorutzky$b Wolfgang$0720789 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483039003321 996 $aBond graph modelling for control, fault diagnosis and failure prognosis$92844409 997 $aUNINA