Details

Intelligent Motorized Spindle Technology

Springer Tracts in Mechanical Engineering

von: Yuhou Wu, Lixiu Zhang
CHF 118.00
Verlag:	Springer
Format:	PDF
Veröffentl.:	22.02.2020
ISBN/EAN:	9789811533280
Sprache:	englisch

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Beschreibungen

Titelbeschreibung

<div>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. </div><div>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. </div>

Inhaltsverzeichnis

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.<p></p>

Autorenportrait

Professor Wu Yuhou is currently the Director of the National and Local Joint Engineering Laboratory of “High-grade Stone NC Processing Equipment and Technology” and the Director of the International Cooperation Joint Laboratory of Modern Construction Engineering Equipment and Technology of the Ministry of Education. He was selected as one of the first academician candidates in Liaoning Province; his main interests are engineering ceramics precision machining and application, CNC machine tool spindle systems, CNC machine tool research and development, ceramic bearings, ceramic electric spindle design and manufacturing assembly and control, stone CNC machining technology development and equipment design and manufacturing. The design theory and processing technology presented were awarded the second prize for national technology invention. <p></p>

<p>Professor Zhang Lixiu is the Head of Liaoning Key Laboratory of CNC Machine Spindle Systems. Her main research direction is the key technology of motorized spindles. With the support of the National Natural Science Foundation of China and the Natural Science Foundation of Liaoning Province of China, she has investigated temperature rise prediction methods in motorized spindles, stator resistance identification of motorized spindles and on-line dynamic balance technology of motorized spindles. Her findings have been published 52 academic papers and 2 monographs. She has been granted 6 national invention patents and 4 software copyrights and won several awards.</p>

Back cover copy

<div><div>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. </div><div>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. </div></div>

Sonderbeitrag

Represents the first book on electric spindle technology in intelligent manufacturing Highlights a variety of intelligent methods for the application of motorized spindle technology Features extensive experimental data on the dynamic performance of motorized spindles, especially ceramic motorized spindles