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Diagnostics of Rotating Machinery through Vibration Monitoring: Signal Processing and Pattern Analysis.

Authors :
Daga, Alessandro Paolo
Garibaldi, Luigi
Source :
Applied Sciences (2076-3417); Oct2024, Vol. 14 Issue 20, p9276, 5p
Publication Year :
2024

Abstract

The document discusses the importance of vibration monitoring in diagnosing faults in rotating machinery, emphasizing the role of signal processing and pattern analysis. Vibration monitoring involves measuring mechanical oscillations in machinery components to detect faults early. Signal processing techniques are used to extract meaningful information from raw vibration data, while pattern analysis techniques help diagnose specific faults. The integration of vibration monitoring with signal processing and pattern analysis offers benefits such as early fault detection, improved reliability, and data-driven maintenance decisions. Challenges include the complexity of machinery, variability of operating conditions, and the gap between research advancements and industrial adoption. The document also highlights the use of benchmark datasets for research and the application of machine learning in fault detection and machinery health monitoring. [Extracted from the article]

Details

Language :
English
ISSN :
20763417
Volume :
14
Issue :
20
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
180527891
Full Text :
https://doi.org/10.3390/app14209276