Smart Monitoring of Rotating Machinery for Industry 4.0
Springer International Publishing (Verlag)
9783030795184 (ISBN)
Prof. Fakher Chaari, National School of Engineers of Sfax, Mechanics Modelling & Production Lab, Sfax, Tunisia
Prof. Xavier Chiementin, University of Reims Champagne-Ardenne, Institut de Thermique, Mécanique,Reims, France
Prof. Radoslaw Zimroz, Wroclaw University of Technology, Faculty of Geo Engineering. Mining and Geology, Wroclaw, Poland
Prof. Fabrice Bolaers, University of Reims Champagne-Ardenne, Institut de Thermique, Reims, France
Prof. Mohamed Haddar, National School of Engineers of Sfax, Sfax, Tunisia
Vulnerabilities and fruits of smart monitoring.- A tutorial on Canonical Variate Analysis for diagnosis and prognosis.- A structured approach to machine learning for condition monitoring.- A structured approach to machine learning for condition monitoring: a case study.- Dynamic Reliability Assessment of Structures and Machines Using the Probability Density Evolution Method.- Rotating machinery condition monitoring methods for applications with different kinds of available prior knowledge.- Model Based Fault Diagnosis in Bevel Gearbox.- Investigating the electro-mechanical interaction between helicoidal gears andan asynchronous geared motor.- Algebraic estimator of damping failure for au-tomotive Shock Absorber.- On the use of jerk for condition monitoring of gearboxes in non-stationary operations.- Dynamic remaining useful life estimation for a shaft bearings system.
| Erscheinungsdatum | 22.08.2021 |
|---|---|
| Reihe/Serie | Applied Condition Monitoring |
| Zusatzinfo | VI, 178 p. 107 illus., 100 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 402 g |
| Themenwelt | Technik ► Maschinenbau |
| Schlagworte | Algebraic estimator • Bevel gear modelling • Canonical Variate Analysis • Damping failure analysis • Deep Learning for smart monitoring • Gearbox monitoring • Helicoidal gear • Intelligent Prognostic Systems • Jerk monitoring • Machine learning for condition monitoring • Machinery in Non-Stationary Operations • Model Based Fault Diagnosis • Probability density evolution • Reliability Analysis • Remaining Useful Life • Rolling bearing fault • Rotating Machine • Smart health monitoring |
| ISBN-13 | 9783030795184 / 9783030795184 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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