Vibration, Acoustics and Sensors Solutions for Machine Condition Monitoring
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: 30 November 2024 | Viewed by 87
Special Issue Editor
Special Issue Information
Dear Colleagues,
The field of machine condition monitoring, using vibrations and acoustics signals, has progressed at a high rate, emerging from the mere use of traditional signal processing techniques to the application of advanced signal processing algorithms and the utilization of machine learning and artificial intelligence applications for incipient fault detection, diagnosis, and prognosis. This, along with the availability of high-tech sensors, high-power processing capability, and digital twins, has contributed extensively to the vital area of predictive maintenance (PM) and to the health and usage monitoring systems (HUMs) of assets.
This Special Issue aims to provide an opportunity to share some of your exciting high-quality research and innovative work on advances in machine condition monitoring to improve predictive maintenance and prognostics and health management in rotating machines.
Potential topics include, but are not limited to, the following:
- Advanced signal processing techniques to extract fault features;
- Signal processing and data fusion to detect, diagnose, and trend faults in rotating machines;
- Sensor devices and sensing applications for machine condition monitoring;
- Machine learning and artificial intelligence (AI) applications applied to vibrations and acoustics signals for predictive maintenance and prognostics and health management;
- Dynamic simulations and virtual twins for the better understanding of rotating machines and the development of health and usage monitoring systems (HUMs).
Dr. Nader Sawalhi
Guest Editor
Manuscript Submission Information
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Keywords
- vibration
- acoustics
- rotating machines
- predictive maintenance (PM)
- health and usage monitoring systems (HUMSs)
- machine learning
- digital twin
- diagnosis
- prognosis
- prognostics and health management (PHM)
- artificial intelligence (AI)
- incipient fault detection
- data fusion
