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Predictive Maintenance in Dynamic Systems

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Cover of 'Predictive Maintenance in Dynamic Systems'

Table of Contents

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    Book Overview
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    Chapter 1 Prologue: Predictive Maintenance in Dynamic Systems
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    Chapter 2 Smart Devices in Production System Maintenance
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    Chapter 3 On the Relevance of Preprocessing in Predictive Maintenance for Dynamic Systems
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    Chapter 4 A Context-Sensitive Framework for Mining Concept Drifting Data Streams
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    Chapter 5 Online Time Series Changes Detection Based on Neuro-Fuzzy Approach
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    Chapter 6 Early Fault Detection in Reciprocating Compressor Valves by Means of Vibration and pV Diagram Analysis
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    Chapter 7 A New Hilbert-Huang Transform Technique for Fault Detection in Rolling Element Bearings
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    Chapter 8 Comparison of Genetic and Incremental Learning Methods for Neural Network-Based Electrical Machine Fault Detection
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    Chapter 9 Evolving Fuzzy Model for Fault Detection and Fault Identification of Dynamic Processes
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    Chapter 10 An Online RFID Localization in the Manufacturing Shopfloor
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    Chapter 11 Physical Model-Based Prognostics and Health Monitoring to Enable Predictive Maintenance
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    Chapter 12 On Prognostic Algorithm Design and Fundamental Precision Limits in Long-Term Prediction
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    Chapter 13 Performance Degradation Monitoring and Quantification: A Wastewater Treatment Plant Case Study
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    Chapter 14 Fuzzy Rule-Based Modeling for Interval-Valued Data: An Application to High and Low Stock Prices Forecasting
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    Chapter 15 Reasoning from First Principles for Self-adaptive and Autonomous Systems
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    Chapter 16 Decentralized Modular Approach for Fault Diagnosis of a Class of Hybrid Dynamic Systems: Application to a Multicellular Converter
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    Chapter 17 Automated Process Optimization in Manufacturing Systems Based on Static and Dynamic Prediction Models
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    Chapter 18 Distributed Chance-Constrained Model Predictive Control for Condition-Based Maintenance Planning for Railway Infrastructures
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Citations

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Title
Predictive Maintenance in Dynamic Systems
Published by
Springer International Publishing, February 2019
DOI 10.1007/978-3-030-05645-2
ISBNs
978-3-03-005644-5, 978-3-03-005645-2
Editors

Lughofer, Edwin, Sayed-Mouchaweh, Moamar

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X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 117 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 17 15%
Student > Ph. D. Student 13 11%
Student > Master 13 11%
Other 4 3%
Researcher 3 3%
Other 6 5%
Unknown 61 52%
Readers by discipline Count As %
Engineering 38 32%
Computer Science 14 12%
Business, Management and Accounting 2 2%
Social Sciences 1 <1%
Economics, Econometrics and Finance 1 <1%
Other 0 0%
Unknown 61 52%