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008			180818s2019 gw a o |||| 0|eng d
020			_a9783319992686
024	7		_a10.1007/978-3-319-99268-6 _2doi
040			_bspa _dES-MaUEC _cES-MaUEC
050		4	_aTJ1058 _b2019 EB
245	0	0	_aProceedings of the 10th International Conference on Rotor Dynamics - IFToMM : _bVol. 2 _cedited by Katia Lucchesi Cavalca, Hans Ingo Weber
264		1	_aCham _bSpringer International Publishing : _bImprint: Springer _c2019
300			_a1 recurso en línea (XIV, 576 páginas) _b398 ilustraciones
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aEngineering (Springer-11647)
490	0		_aMechanisms and Machine Science _x2211-0984 _v61
505	0		_aCrack Detection and Dynamic Analysis of a Cracked Rotor with Soft Bearings Using Different Methods of Solution -- Nuclear Reactor Heat Transfer Pump Rotordynamic Based Diagnostics and field Data Model Reconciliation -- Performance Analysis of Support Vector Machine and Wavelet Packet Transform based Fault Diagnostics of Induction Motor at Various Operating Conditions -- Multi Fault Diagnosis of Centrifugal Pumps with Time, Frequency and Wavelet based Features using Support Vector Machines -- Interpretation of Dynamic Data Plots for Troubleshooting and Resolving Vibration in Large Rotating Machinery -- Prediction of Dynamic Characteristics Induced by Rubbing Between Rotating Blade and Casing -- Application of Machine Learning in Diesel Engines Fault Identification -- Detection of Cracks in a Rotating Shaft Using Density Characterization of Orbit Plots -- Model-Based Vibration Condition Monitoring for Fault Detection and Diagnostics Applied to Large Hydro Generators -- Monitoring of Induction Motor Mechanical and Electrical Faults by Optimum Multiclass-Support Vector Machine Algorithms Using Genetic Algorithm -- Application of Deep Stacked Auto-Encoder Neural Networks to Feature Learning for Intelligent Diagnosis of Machine Condition.
520	3		_aIFToMM conferences have a history of success due to the various advances achieved in the field of rotor dynamics over the past three decades. These meetings have since become a leading global event, bringing together specialists from industry and academia to promote the exchange of knowledge, ideas, and information on the latest developments in the dynamics of rotating machinery. The scope of the conference is broad, including e.g. active components and vibration control, balancing, bearings, condition monitoring, dynamic analysis and stability, wind turbines and generators, electromechanical interactions in rotor dynamics and turbochargers. The proceedings are divided into four volumes. This second volume covers the following main topics: condition monitoring, fault diagnostics and prognostics; modal testing and identification; parametric and self-excitation in rotor dynamics; uncertainties, reliability and life predictions of rotating machinery; and torsional vibrations and geared systems dynamics. .
650		7	_2embne _aRotores _xDinámica _xCongresos y asambleas _9668198
650		7	_2embne _aIngeniería mecánica _xCongresos y asambleas
700	1		_aCavalca, Katia Lucchesi. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aWeber, Hans Ingo. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
710	2		_aSpringerLink (Online service) _9106996
776	0	8	_iPrinted edition: _z9783030075811
776	0	8	_iPrinted edition: _z9783319992679
776	0	8	_iPrinted edition: _z9783319999258
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-99268-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aPrimersemestre_2019_Engineering
998			_aSI _cm _dz _feng _ggw _h0 _b09/2019 _eel _zSI