Predictive Maintenance in Dynamic Systems: Advanced Methods, Decision Support Tools and Real-World Applications

✍ Scribed by Edwin Lughofer, Moamar Sayed-Mouchaweh

• Publisher: Springer International Publishing
• Year: 2019
• Tongue: English
• Leaves: 564
• Edition: 1st ed.
• Category: Library

✦ Synopsis

This book provides a complete picture of several decision support tools for predictive maintenance. These include embedding early anomaly/fault detection, diagnosis and reasoning, remaining useful life prediction (fault prognostics), quality prediction and self-reaction, as well as optimization, control and self-healing techniques. It shows recent applications of these techniques within various types of industrial (production/utilities/equipment/plants/smart devices, etc.) systems addressing several challenges in Industry 4.0 and different tasks dealing with Big Data Streams, Internet of Things, specific infrastructures and tools, high system dynamics and non-stationary environments . Applications discussed include production and manufacturing systems, renewable energy production and management, maritime systems, power plants and turbines, conditioning systems, compressor valves, induction motors, flight simulators, railway infrastructures, mobile robots, cyber security and Internet of Things. The contributors go beyond state of the art by placing a specific focus on dynamic systems, where it is of utmost importance to update system and maintenance models on the fly to maintain their predictive power.

✦ Table of Contents

Front Matter ....Pages i-xiii
Prologue: Predictive Maintenance in Dynamic Systems (Edwin Lughofer, Moamar Sayed-Mouchaweh)....Pages 1-23
Smart Devices in Production System Maintenance (Eike Permin, Florian Lindner, Kevin Kostyszyn, Dennis Grunert, Karl Lossie, Robert Schmitt et al.)....Pages 25-51
On the Relevance of Preprocessing in Predictive Maintenance for Dynamic Systems (Carlos Cernuda)....Pages 53-93
Front Matter ....Pages 95-95
A Context-Sensitive Framework for Mining Concept Drifting Data Streams (Chamari I. Kithulgoda, Russel Pears)....Pages 97-129
Online Time Series Changes Detection Based on Neuro-Fuzzy Approach (Yevgeniy Bodyanskiy, Artem Dolotov, Dmytro Peleshko, Yuriy Rashkevych, Olena Vynokurova)....Pages 131-166
Early Fault Detection in Reciprocating Compressor Valves by Means of Vibration and pV Diagram Analysis (Kurt Pichler)....Pages 167-205
A New Hilbert-Huang Transform Technique for Fault Detection in Rolling Element Bearings (Shazali Osman, Wilson Wang)....Pages 207-230
Comparison of Genetic and Incremental Learning Methods for Neural Network-Based Electrical Machine Fault Detection (Daniel Leite)....Pages 231-268
Evolving Fuzzy Model for Fault Detection and Fault Identification of Dynamic Processes (Goran Andonovski, Sašo Blažič, Igor Škrjanc)....Pages 269-285
An Online RFID Localization in the Manufacturing Shopfloor (Andri Ashfahani, Mahardhika Pratama, Edwin Lughofer, Qing Cai, Huang Sheng)....Pages 287-309
Front Matter ....Pages 311-311
Physical Model-Based Prognostics and Health Monitoring to Enable Predictive Maintenance (Tiedo Tinga, Richard Loendersloot)....Pages 313-353
On Prognostic Algorithm Design and Fundamental Precision Limits in Long-Term Prediction (Marcos E. Orchard, David E. Acuña)....Pages 355-379
Performance Degradation Monitoring and Quantification: A Wastewater Treatment Plant Case Study (Iñigo Lecuona, Rosa Basagoiti, Gorka Urchegui, Luka Eciolaza, Urko Zurutuza, Peter Craamer)....Pages 381-401
Fuzzy Rule-Based Modeling for Interval-Valued Data: An Application to High and Low Stock Prices Forecasting (Leandro Maciel, Rosangela Ballini)....Pages 403-424
Front Matter ....Pages 425-425
Reasoning from First Principles for Self-adaptive and Autonomous Systems (Franz Wotawa)....Pages 427-460
Decentralized Modular Approach for Fault Diagnosis of a Class of Hybrid Dynamic Systems: Application to a Multicellular Converter (Moamar Sayed-Mouchaweh)....Pages 461-483
Automated Process Optimization in Manufacturing Systems Based on Static and Dynamic Prediction Models (Edwin Lughofer, Alexandru-Ciprian Zavoianu, Mahardhika Pratama, Thomas Radauer)....Pages 485-531
Distributed Chance-Constrained Model Predictive Control for Condition-Based Maintenance Planning for Railway Infrastructures (Zhou Su, Ali Jamshidi, Alfredo Núñez, Simone Baldi, Bart De Schutter)....Pages 533-554
Back Matter ....Pages 555-567

✦ Subjects

Engineering; Communications Engineering, Networks; Quality Control, Reliability, Safety and Risk; Control; Computational Intelligence; Information Systems and Communication Service