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

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 o...

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Bibliographic Details
Other Authors: Fernandez Del Rincon, Alfonso (Editor), Viadero Rueda, Fernando (Editor), Chaari, Fakher (Editor), Zimroz, Radoslaw (Editor)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2019, 2019
Edition:1st ed. 2019
Series:Applied Condition Monitoring
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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245 0 0 |a Advances in Condition Monitoring of Machinery in Non-Stationary Operations  |h Elektronische Ressource  |b Proceedings of the 6th International Conference on Condition Monitoring of Machinery in Non-Stationary Operations, CMMNO’2018, 20-22 June 2018, Santander, Spain  |c edited by Alfonso Fernandez Del Rincon, Fernando Viadero Rueda, Fakher Chaari, Radoslaw Zimroz, Mohamed Haddar 
250 |a 1st ed. 2019 
260 |a Cham  |b Springer International Publishing  |c 2019, 2019 
300 |a XI, 423 p. 274 illus., 218 illus. in color  |b online resource 
505 0 |a 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 
653 |a Mechanics, Applied 
653 |a Machines, Tools, Processes 
653 |a Manufactures 
653 |a Multibody Systems and Mechanical Vibrations 
653 |a Signal, Speech and Image Processing 
653 |a Vibration 
653 |a Mathematical physics 
653 |a Signal processing 
653 |a Multibody systems 
653 |a Theoretical, Mathematical and Computational Physics 
700 1 |a Viadero Rueda, Fernando  |e [editor] 
700 1 |a Chaari, Fakher  |e [editor] 
700 1 |a Zimroz, Radoslaw  |e [editor] 
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989 |b Springer  |a Springer eBooks 2005- 
490 0 |a Applied Condition Monitoring 
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082 0 |a 670 
520 |a 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