Advances in Condition Monitoring of Machinery in Non-Stationary Operations (inbunden)
Format
Inbunden (Hardback)
Språk
Engelska
Antal sidor
423
Utgivningsdatum
2019-02-08
Upplaga
1st ed. 2019
Förlag
Springer Nature Switzerland AG
Medarbetare
Fernandez Del Rincon, Alfonso (ed.), Viadero Rueda, Fernando (ed.), Chaari, Fakher (ed.), Zimroz, Radoslaw (ed.), Haddar, Mohamed (ed.)
Illustratör/Fotograf
Bibliographie 100 farbige Abbildungen
Illustrationer
100 Tables, color; 218 Illustrations, color; 56 Illustrations, black and white; XI, 423 p. 274 illus
Dimensioner
234 x 156 x 24 mm
Vikt
785 g
Antal komponenter
1
Komponenter
1 Hardback
ISBN
9783030112196
Advances in Condition Monitoring of Machinery in Non-Stationary Operations (inbunden)

Advances in Condition Monitoring of Machinery in Non-Stationary Operations

Proceedings of the 6th International Conference on Condition Monitoring of Machinery in Non-Stationary Operations, CMMNO'2018, 20-22 June 2018, Santander, Spain

Inbunden Engelska, 2019-02-08
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This book is aimed at researchers, industry professionals and students interested in the broad ranges of disciplines related to condition monitoring of machinery working in non-stationary conditions. Each chapter, accepted after a rigorous peer-review process, reports on a selected, original piece of work presented and discussed at the International Conference on Condition Monitoring of Machinery in Non-stationary Operations, CMMNO'2018, held on June 20 - 22, 2018, in Santander, Spain. The book describes both theoretical developments and a number of industrial case studies, which cover different topics, such as: noise and vibrations in machinery, conditioning monitoring in non-stationary operations, vibro-acoustic diagnosis of machinery, signal processing, application of pattern recognition and data mining, monitoring and diagnostic systems, faults detection, dynamics of structures and machinery, and mechatronic machinery diagnostics.
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Innehållsförteckning

Condition Monitoring in Non-Stationary Operations.- Extraction of Weak Bearing Fault Signatures from Non-Stationary Signals Using Parallel Wavelet Denoising.- Neighbor Retrieval Visualizer for Monitoring Lifting Cranes.- Monitoring and Diagnostic Systems.- Convolutional Neural Networks for Fault Diagnosis Using Rotating Speed Normalized Vibration.- Monitoring of a High-Speed Train Bogie Using the EMD Technique.- Default Detection in a Back-To-Back Planetary Gear-Box through Current and Vibration Signals.- Noise and Vibration in Machines.- Identification of Torsional Vibration Modal Parameters: Application on a Ferrari Engine Crankshaft.- Experimental Characterization of Metal-Mesh Isolators Damping Capacity by Constitutive Mechanical Model.- Signal Processing.- Separation of Impulse from Oscillation for Detection of Bearing Defect in the Vibration Signal.- Vibro-Acoustic Diagnosis of Machinery.- Cyclo-Non-Stationary Based Bearing Diagnostics of Planetary Gearboxes.- Cyclostationary Approach for Long Term Vibration Data Analysis.- Monitoring of Soil Density During Compaction Processes.