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Intelligent motorized spindle technology

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Intelligent motorized spindle technology

Record Type:	Electronic resources : Monograph/item
Title/Author:	Intelligent motorized spindle technologyby Yuhou Wu, Lixiu Zhang.
Author:	Wu, Yuhou.
other author:	Zhang, Lixiu.
Published:	Singapore :Springer Singapore :2020.
Description:	xiii, 303 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Spindles (Machine-tools)Technological innovations.
Online resource:	https://doi.org/10.1007/978-981-15-3328-0
ISBN:	9789811533280$q(electronic bk.)

Intelligent motorized spindle technology
Wu, Yuhou.

Intelligent motorized spindle technology[electronic resource] /by Yuhou Wu, Lixiu Zhang. - Singapore :Springer Singapore :2020. - xiii, 303 p. :ill., digital ;24 cm. - Springer tracts in mechanical engineering,2195-9862. - Springer tracts in mechanical engineering..

Key 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.

This 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.

ISBN: 9789811533280$q(electronic bk.)

Standard No.: 10.1007/978-981-15-3328-0doiSubjects--Topical Terms:

862780
Spindles (Machine-tools)
--Technological innovations.

LC Class. No.: TJ1187.4 / .W898 2020

Dewey Class. No.: 621.902

Intelligent motorized spindle technology
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505 0 $a Key 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 $a This 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.
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