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Condition Monitoring and Nonlinear Frequency Analysis Based Fault Detection of Mechanical Vibration Systems

Autor Hogir Rafiq
en Limba Engleză Paperback – 27 aug 2023
Hogir Rafiq proposes two approaches, the signal processing based condition monitoring approaches with applications to fault detection in gear systems, and application of deep mathematical and system theoretical methods to fault detection. The author develops the multivariate empirical mode decomposition (MEMD) algorithm to enhance the capability of extracting fault features and theoretical problems in nonlinear frequency analysis methods, respectively. The effectiveness has been demonstrated by an experimental study on a wind turbine gearbox test rig.
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Specificații

ISBN-13: 9783658424794
ISBN-10: 3658424796
Pagini: 191
Ilustrații: XXI, 191 p. 38 illus., 35 illus. in color. Textbook for German language market.
Dimensiuni: 148 x 210 mm
Greutate: 0.26 kg
Ediția:1st ed. 2023
Editura: Springer Fachmedien Wiesbaden
Colecția Springer Vieweg
Locul publicării:Wiesbaden, Germany

Cuprins

Introduction.- The basics and kinematics of gears.- Vibration signal-based analysis for gear
faults.- Frequency domain analysis for nonlinear systems.- Development of advanced signal processing based fault diagnosis.- Estimation of NOFRFs based parametric characteristic analysis.-  Conclusions and future work.- Bibliography.


Notă biografică

Hogir Rafiq received his Ph.D. degree at the Institute of Automatic Control and Complex Systems (AKS), Faculty of Engineering, University of Duisburg-Essen, Germany, in 2023, and his M.Sc. degree in Control and Systems Engineering at the department of Automatic Control and Systems Engineering (ACSE), The University of Sheffield, UK, in 2012. His research interests include condition monitoring, signal processing and data-driven fault diagnosis and nonlinear frequency analysis.

Textul de pe ultima copertă

Hogir Rafiq proposes two approaches, the signal processing based condition monitoring approaches with applications to fault detection in gear systems, and application of deep mathematical and system theoretical methods to fault detection. The author develops the multivariate empirical mode decomposition (MEMD) algorithm to enhance the capability of extracting fault features and theoretical problems in nonlinear frequency analysis methods, respectively. The effectiveness has been demonstrated by an experimental study on a wind turbine gearbox test rig.

About the author 
Hogir Rafiq received his Ph.D. degree at the Institute of Automatic Control and Complex Systems (AKS), Faculty of Engineering, University of Duisburg-Essen, Germany, in 2023, and his M.Sc. degree in Control and Systems Engineering at the department of Automatic Control and Systems Engineering (ACSE), The University of Sheffield, UK, in 2012. His research interests include condition monitoring, signal processing and data-driven fault diagnosis and nonlinear frequency analysis.