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999			_c119369 _d119369
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005			20230102113945.0
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007			cr nn nnnaamaa
008			200222s2020 si a s |||| 0|eng d
020			_a9789811533280
024	7		_a10.1007/978-981-15-3328-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTJ1187.4 _b2020 EB
100	1		_aWu, Yuhou _9673770 _eautor
245	1	0	_aIntelligent Motorized Spindle Technology _cby Yuhou Wu, Lixiu Zhang.
250			_aFirst edition 2020.
264		1	_aSingapore _bSpringer Singapore _c2020
300			_a1 recurso en línea (XIII, 303 páginas) _b228 ilustraciones, 121 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aArchivo de texto _bPDF
490	0		_aSpringer Tracts in Mechanical Engineering _x2195-9862
490	0		_aIntelligent Technologies and Robotics (Springer-42732)
505	0		_aKey technology and performance of motorized spindle -- Motorized spindle drive mode and its basic theory -- Heat generation and transfer of motorized spindles -- Basic theory and method of spindle dynamic balance -- Intelligent identification technology of stator resistance of motorized spindle motor -- Thermal performance prediction of Motorized spindle -- Automatic suppression of motorized spindle vibration -- Motorized spindle fault diagnosis technology based on deep learning -- Development of intelligent ceramic motorized spindle.
520	3		_aThis book presents the latest information on the intelligent CNC machine tool spindle system, which integrates various disciplines such as mechanical engineering, control engineering, computer science and information technology. It describes a prediction method and model for temperature rise and thermal deformation in motorized spindles and proposes an intelligent stator resistance identification method to reduce the torque ripple of motorized spindles under direct torque control. Further, it discusses the on-line dynamic balance method for NC machine tool spindles. The biogeographic optimization algorithm and hybrid intelligent algorithm presented here were first applied in the field of motorized spindle performance control. In turn, the book presents extensive motorized spindle performance test data and includes detailed examples of how intelligent algorithms can be applied to motor spindle stator resistance identification, temperature field prediction and on-line dynamic balance. In summary, the book provides readers with the latest tools for designing, testing and implementing intelligent motorized spindle systems in terms of the basic theory, technological applications and future prospects, and offers a wealth of practical information for researchers in mechanical engineering, especially in the area of control systems. .
988			_aSpringer_Robotics_31032020
650		7	_aControl automático _2embne _9405125
700	1		_aZhang, Lixiu _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _9673848
710	2		_aSpringerLink (Online service) _9106996
776	0	8	_iPrinted edition: _z9789811533273
776	0	8	_iPrinted edition: _z9789811533297
776	0	8	_iPrinted edition: _z9789811533303
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-15-3328-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b05/2020 _dz _eh _zSI