000 02582nam a22002777a 4500
003 OSt
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008 220601b |||||||| |||| 00| 0 eng d
020 _a9783030878788
020 _a9783030878771
020 _a9783030878788 (eBook)
040 _c0
082 _a671.35 ZHU
092 _20
100 _aZhu, Kunpeng
245 _aSmart machining systems
_bmodelling, monitoring and informatics
_cKunpeng Zhu
260 _aCham
_bSpringer
_c2022
300 _axviii, 407 pages
_billustrations (some color)
_c25 cm
490 _aSpringer series in advanced manufacturing.
504 _aIncludes bibliographical references (p. 405-406)
505 _a Part I: Fundamentals -- Chapter 1. Introduction -- Chapter 2. Modeling of Machining Process -- Chapter 3. Tool Wear Modelling -- Chapter 4. Mathematical Fundamentals of Condition Monitoring -- Chapter 5. Signal Processing for Condition Monitoring -- Chapter 6. The Framework of TCM from Machine Learning View -- Part II: Applications -- Chapter 7. Sensory Signal De-noising and Pre-processing -- Chapter 8. TCM with Sparse Decomposition -- Chapter 9. The Monitoring of Tool Conditions with Computer Vision -- Chapter 10. Diagnosis and Prognosis of Machining Degradation Process -- Chapter 11. Sensor Fusion Approached to TCM -- Chapter 12. Big Data Orientated CNC Machining TXM Monitoring System -- Chapter 13. CPPS Framework of Smart CNC Machining Monitoring System.
520 _a This book provides the tools to enhance the precision, automation and intelligence of modern CNC machining systems. Based on a detailed description of the technical foundations of the machining monitoring system, it develops the general idea of design and implementation of smart machining monitoring systems, focusing on the tool condition monitoring system. The book is structured in two parts. Part I discusses the fundamentals of machining systems, including modeling of machining processes, mathematical basics of condition monitoring and the framework of TCM from a machine learning perspective. Part II is then focused on the applications of these theories. It explains sensory signal processing and feature extraction, as well as the cyber-physical system of the smart machining system. Its utilisation of numerous illustrations and diagrams explain the ideas presented in a clear way, making this book a valuable reference for researchers, graduate students and engineers alike.
650 _aMachining
_xMachinery
650 _aMonitoring.
_xMachine learning.
942 _2ddc
_cBK
_n0
999 _c275
_d275