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Science/Engineering Condition Monitoring and Control for Intelligent Manufacturing

Posted on 2010-03-15




Name:Science/Engineering Condition Monitoring and Control for Intelligent Manufacturing
ASIN/ISBN:1846282683
Language:English
File size:6 Mb
   Science/Engineering Condition Monitoring and Control for Intelligent Manufacturing

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Condition Monitoring and Control for Intelligent Manufacturing



ISBN: 1846282683

Title: Condition Monitoring and Control for Intelligent Manufacturing (Springer Series in Advanced Manufacturing)

Author: I.Wang, Lihui II.Gao, Robert X

Publisher: Springer

Publication Date: 2006-05-23

Number Of Pages: 399

Book Description

Manufacturing systems and processes are becoming increasingly complex, making more rational decision-making in process control a necessity. Better information gathering and analysis techniques are needed and condition-based monitoring is gaining attention from researchers worldwide as a framework that will enable these improvements. Condition Monitoring and Control for Intelligent Manufacturing brings together the world’s authorities on condition-based monitoring to provide a broad treatment of the subject accessible to researchers and practitioners in manufacturing industry. The book presents a wide and comprehensive review of the key areas of research in machine condition monitoring and control, before focusing on an in-depth treatment of each important technique, from multi-domain signal processing for defect diagnosis to web-based information delivery for real-time control. Condition Monitoring and Control for Intelligent Manufacturing is a valuable resource for researchers in manufacturing and control engineering, as well as practising engineers in industries from automotive to packaging manufacturing.

Table of Contents

1 Monitoring and control of machining 1

2 Precision manufacturing process monitoring with acoustic emission 33

3 Tool condition monitoring in machining 55

4 Monitoring systems for grinding processes 83

5 Condition monitoring of rotary machines 109

6 Advanced diagnostic and prognostic techniques for rolling element bearings 137

7 Sensor placement and signal processing for bearing condition monitoring 167

8 Monitoring and diagnosis of sheet metal stamping processes 193

9 Robust state indicators of gearboxes using adaptive parametric modeling 219

10 Signal processing in manufacturing monitoring 245

11 Autonomous active-sensor networks for high-accuracy monitoring in manufacturing 267

12 Remote monitoring and control in a distributed manufacturing environment 289

13 An intelligent nanofabrication probe for surface displacement/profile measurement 315

14 Smart transducer interface standards for condition monitoring and control of machines 347

15 Rocket testing and integrated system health management 373

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