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008			170203s2017 gw ob 000 0 eng d
020			_a3662540304 _q(electronic bk.)
020			_a9783662540305 _q(electronic bk.)
020			_z3662540282
020			_z9783662540282 _q(print)
035			_a(OCoLC)971245648 _z(OCoLC)971587636 _z(OCoLC)971952334 _z(OCoLC)972101563 _z(OCoLC)972204785 _z(OCoLC)972395053 _z(OCoLC)972538418 _z(OCoLC)973806564 _z(OCoLC)981776749 _z(OCoLC)1005770208 _z(OCoLC)1011901759
040			_aN$T _cN$T _dGW5XE _dEBLCP _dIDEBK _dN$T _dOCLCF _dNJR _dUAB _dCOO _dIOG _dAZU _dUWO _dVT2 _dUPM _dESU _dZ5A _dYDX _dJBG _dIAD _dICW _dICN _dOTZ _dOCLCQ _dU3W _dES-MaUEC _bspa
050		4	_aTA409.2 _bS595 2017 EB
100	1		_aSi, Xiao-Sheng, _eautor
245	1	0	_aData-driven remaining useful life prognosis techniques : _bstochastic models, methods and applications _cXiao-Sheng Si, Zheng-Xin Zhang, Chang-Hua Hu.
264		1	_aBerlin, Germany _bSpringer _c2017
300			_a1 recurso en línea
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	0		_aSpringer series in reliability engineering _x1614-7839
500			_aSpringerLink
504			_aIncluye referencias bibliográficas
505	0		_aFrom the Contents: Part I Introduction, Basic Concepts and Preliminaries -- Overview -- Advances in Data-Driven Remaining Useful Life Prognosis -- Part II Remaining Useful Life Prognosis for Linear Stochastic Degrading Systems -- Part III Remaining Useful Life Prognosis for Nonlinear Stochastic Degrading Systems -- Part IV Applications of Prognostics in Decision Making -- Variable Cost-based Maintenance Model from Prognostic Information.
520	3		_aThis book introduces data-driven remaining useful life prognosis techniques, and shows how to utilize the condition monitoring data to predict the remaining useful life of stochastic degrading systems and to schedule maintenance and logistics plans. It is also the first book that describes the basic data-driven remaining useful life prognosis theory systematically and in detail. The emphasis of the book is on the stochastic models, methods and applications employed in remaining useful life prognosis. It includes a wealth of degradation monitoring experiment data, practical prognosis methods for remaining useful life in various cases, and a series of applications incorporated into prognostic information in decision-making, such as maintenance-related decisions and ordering spare parts. It also highlights the latest advances in data-driven remaining useful life prognosis techniques, especially in the contexts of adaptive prognosis for linear stochastic degrading systems, nonlinear degradation modeling based prognosis, residual storage life prognosis, and prognostic information-based decision-making.
988			_aEBOOK, asignarmaterias, EBSPRINGER_2017B
650		7	_aResistencia de materiales _2embne _0(OCoLC)fst00902019 _9139841
700	1		_aHu, Chang-Hua, _eautor
700	1		_aZhang, Zheng-Xin, _eautor
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=http://link.springer.com/10.1007/978-3-662-54030-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2018 _dz _e- _zSI