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
1. Auflage 2019
ISBN: 978-3-030-11219-6
Verlag: Springer International Publishing

Buch, Englisch, Band 15, 423 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 816 g

Reihe: Applied Condition Monitoring

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.

Zielgruppe

Research

Autoren/Hrsg.

Fernandez Del Rincon, Alfonso

Viadero Rueda, Fernando

Haddar, Mohamed

Chaari, Fakher

Zimroz, Radoslaw

Fachgebiete

• Naturwissenschaften Physik Physik Allgemein Theoretische Physik, Mathematische Physik, Computerphysik
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Zuverlässigkeitstechnik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Signalverarbeitung
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Technische Mechanik | Werkstoffkunde Statik, Dynamik, Kinetik, Kinematik

Inhaltsverzeichnis

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.