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Condition Monitoring of Machinery in Non-Stationary Operations: Proceedings of the Second International Conference "Condition Monitoring of Machinery in Non-Stationnary Operations" CMMNO’2012

Condition Monitoring of Machinery in Non-Stationary Operations: Proceedings of the Second International Conference "Condition Monitoring of Machinery in Non-Stationnary Operations" CMMNO’2012
Kataloginformation
Feldname Details
Vorliegende Sprache eng
Hinweise auf parallele Ausgaben 36616712X Buchausg. u.d.T.: ‡Condition monitoring of machinery in non-stationary operations
ISBN 978-3-642-28767-1
Name Fakhfakh, Tahar
Bartelmus, Walter
Name ANZEIGE DER KETTE Bartelmus, Walter
Name Chaari, Fakher
Zimroz, Radoslaw
Haddar, Mohamed
T I T E L Condition Monitoring of Machinery in Non-Stationary Operations
Zusatz zum Titel Proceedings of the Second International Conference "Condition Monitoring of Machinery in Non-Stationnary Operations" CMMNO’2012
Verlagsort Berlin, Heidelberg
Verlag Springer Berlin Heidelberg
Erscheinungsjahr 2012
2012
Umfang Online-Ressource (XIV, 638p. 388 illus., 253 illus. in color, digital)
Reihe SpringerLink. Bücher
Notiz / Fußnoten Description based upon print version of record
Weiterer Inhalt Title; Contents; Chapter 1 Condition Monitoring in Non-stationary Operations; Separation of Gear and Bearing Fault Signals from a Wind Turbine Transmission underVarying Speed and Load; Introduction; Typical Diagnosis of Wind Turbine Transmission Faults; Conclusion; References; Object and Operation Factor OrientedDiagnostics; Introduction; Factors Influencing Vibration Signal; Influence of Design Factors - Object Orientation; Interaction of Gearbox Elements; Planetary Gearbox Condition Monitoring; Load Susceptibility - Computer Simulations; Wind Turbine Condition Monitoring; Conclusions. ReferencesR\'{e}nyi Entropy Based Statistical Complexity Analysis for Gear Fault Prognostics under Variable Load; Introduction; Statistical Complexity; Complexity of Gear Vibrations; Wavelet Based Calculation of the Statistical Complexity; Monitoring the Natural Gear Surface Fault Progress inOne-Stage Gearbox; Conclusions; References; Non Linear Transient Response of a FlexibleShaft Controlled by Electro-rheological Hydrostatic Squeeze Film Dampers; Introduction; Negative Electro-Rheological Fluids; Mathematical Modeling; Shaft Mode; Forces Hydrostatics Bearings; Numerical Results. Control Method for an NER Hydrostatic Journal BearingConclusion; References; STFT Based Approach for Ball Bearing FaultDetection in a Varying Speed Motor; Introduction; Test Machine and Signal Presentation; Condition Monitoring Procedure; Segmentation of Vibration Signal According to MachineCycle; STFT of Every Residual Signal; Average of the STFT Spectrograms; Marginal Time Integration; Results; Conclusions; References; Kurtosis over Energy Distribution Approach for STFT Enhancement in Ball BearingDiagnostics; Introduction; Short Time Fourier Transform Enhancement; STFT Spectrogram. Spectral KurtosisEnergy Distribution; Kurtosis over Energy; Results; Conclusion; References; Detecting AE Signals from Natural Degradationof Slow Speed Rolling Element Bearings; Introduction; Test Rig Layout and Experimental Procedure; Bearing Test; Fault Index Extraction Techniques; Conclusion; References; Leak Detection in Viscoelastic Pipeby Transient Analysis; Introduction; Water Hammer Model; Basic Equations; Leak Modeling; Numerical Resolution; Initial Conditions; Boundary Conditions; Application and Results; Conclusion; References. Gear Fault Detection under FluctuatingOperating Conditions by Means of Discrepancy AnalysisIntroduction; Methodology; Piecewise Signal Evaluation; Autoencoder; Experimental Setup; Implementation; Experimental Results; Conclusion; References; Bearing Fault Diagnosis Using Neural Networkand Genetic Algorithms with the Trace Criterion; Introduction; Artificial Neural Network; Genetic Algorithms (GA); Coding of Chromosomes; Generating the Initial Population; The Fitness Function; Stopping Criterion; Selecting Individual for Reproduction; Vibration Data; Features Extraction; Statistical Features. Spectral Features
Titelhinweis Buchausg. u.d.T.: ‡Condition monitoring of machinery in non-stationary operations
ISBN ISBN 978-3-642-28768-8
Klassifikation TGBN
TEC046000
621.8
621.8/16
TA213-215
Kurzbeschreibung Mohamed Haddar
2. Kurzbeschreibung Condition monitoring of machines in non-stationary operations (CMMNO) can be seen as the major challenge for research in the field of machinery diagnostics. Condition monitoring of machines in non-stationary operations is the title of the presented book and the title of the Conference held in Hammamet - Tunisia March 26 - 28, 2012. It is the second conference under this title, first took place in Wroclaw - Poland , March 2011. The subject CMMNO comes directly from industry needs and observation of real objects. Most monitored and diagnosed objects used in industry works in non-stationary operations condition. The non-stationary operations come from fulfillment of machinery tasks, for which they are designed for. All machinery used in different kind of mines, transport systems, vehicles like: cars, buses etc, helicopters, ships and battleships and so on work in non-stationary operations. The papers included in the book are shaped by the organizing board of the conference and authors of the papers. The papers are divided into five sections, namely: Condition monitoring of machines in non-stationary operationsModeling of dynamics and fault in systems Signal processing and Pattern recognition Monitoring and diagnostic systems Noise and vibration of machinesThe presented book gives the back ground to the main objective of the CMMNO 2012 conference that is to bring together scientific community to discuss the major advances in the field of machinery condition monitoring in non-stationary conditions.
1. Schlagwortkette Technisches System
Instationärer Zustand
Fehlererkennung
Diagnosesystem
Zustandsüberwachung
Kongress
1. Schlagwortkette ANZEIGE DER KETTE Technisches System -- Instationärer Zustand -- Fehlererkennung -- Diagnosesystem -- Zustandsüberwachung -- Kongress
2. Schlagwortkette Maschinendynamik
Maschinenschwingung
Maschinenlärm
Zustandsüberwachung
Signalverarbeitung
Mustererkennung
SWB-Titel-Idn 363410732
Signatur Springer E-Book
Bemerkungen Elektronischer Volltext - Campuslizenz
Elektronische Adresse $uhttp://dx.doi.org/10.1007/978-3-642-28768-8
Internetseite / Link Volltext
Siehe auch Inhaltsverzeichnis
Siehe auch Inhaltstext
Siehe auch Volltext
Kataloginformation500169719 Datensatzanfang . Kataloginformation500169719 Seitenanfang .
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