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Smart machining systemsmodelling, monitoring and informatics /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Smart machining systemsby Kunpeng Zhu.
其他題名:	modelling, monitoring and informatics /
作者:	Zhu, Kunpeng.
出版者:	Cham :Springer International Publishing :2022.
面頁冊數:	xviii, 407 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Machining.
電子資源:	https://doi.org/10.1007/978-3-030-87878-8
ISBN:	9783030878788$q(electronic bk.)

Smart machining systemsmodelling, monitoring and informatics /
Zhu, Kunpeng.

Smart machining systemsmodelling, monitoring and informatics /[electronic resource] :by Kunpeng Zhu. - Cham :Springer International Publishing :2022. - xviii, 407 p. :ill. (some col.), digital ;24 cm. - Springer series in advanced manufacturing,2196-1735. - Springer series in advanced manufacturing..

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.

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.

ISBN: 9783030878788$q(electronic bk.)

Standard No.: 10.1007/978-3-030-87878-8doiSubjects--Topical Terms:

206812
Machining.

LC Class. No.: TJ1185 / .Z58 2022

Dewey Class. No.: 671.35

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505 0 $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.
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