Smart Monitoring of Rotating Machinery for Industry 4.0
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Smart Monitoring of Rotating Machinery for Industry 4.0

Smart Monitoring of Rotating Machinery for Industry 4.0


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About the Book

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.
About the Author: 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


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Product Details
  • ISBN-13: 9783030795184
  • Publisher: Springer International Publishing
  • Publisher Imprint: Springer
  • Height: 234 mm
  • No of Pages: 188
  • Series Title: Applied Condition Monitoring
  • Weight: 489 gr
  • ISBN-10: 3030795187
  • Publisher Date: 10 Sep 2021
  • Binding: Hardback
  • Language: English
  • Returnable: Y
  • Spine Width: 13 mm
  • Width: 156 mm


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