Advances in Condition Monitoring of Machinery in Non-Stationary Operations

Beschreibung

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.
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.
Reports on the latest research and industrial case studies Describes advanced signal processing methods for the analysis of non-stationary processes Covers a wide range of models, including dynamic, neural networks and probabilistic models

Autor*in

Alfonso Fernandez Del Rincon

Themen in »Advances in Condition Monitoring of Machinery in Non-Stationary Operations«

Fault Detection in Rotating Machineries Vibration Monitoring Variable Speed Wind Turbines Diagnostics of Variable Speed Machines Rotational Synchronous Component Weak Fault Signature Extraction Envelope Analysis Condition Monitoring of Transportation Systems Rotor Dynamics Torsional Vibration Analysis Torsional Models Machine Learning In Fault Diagnostics Temperature Monitoring of Electric Motors Fleet Analysis Bearing Fault Model

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