Prognostics and Health Management (PHM) of Wind Turbines
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A3: Wind, Wave and Tidal Energy".
Deadline for manuscript submissions: closed (18 November 2023) | Viewed by 175
Special Issue Editor
Special Issue Information
Dear Colleagues,
Prognostics and health management (PHM) of mechanical equipment is an important technology to ensure the safe operation of equipment and improve its economic benefits. Nowadays, in most countries, key mechanical equipment such as wind turbines has gradually moved from the research and development stage to the operation and maintenance stage. As a result, research and application of PHM technologies for wind turbine equipment have received extensive attention in academia and industry. In recent years, with the rapid development of emerging technologies such as information technology and artificial intelligence, the research of PHM for wind turbines reaching a climax, scholars at home and abroad have achieved a series of innovative results in dynamics modeling, monitoring signal analysis, intelligent fault diagnosis, and remaining useful life prediction of mechanical equipment.
To comprehensively report on research progress in this field, disseminate excellent research outcomes, and promote the development and application of PHM technologies for wind turbine equipment, this Special Issue focuses on presenting novel ideas, methods, and applications for advancing this field.
Topics of interest for publication include, but are not limited to:
- Dynamical modeling approaches for wind turbines
- Monitored signal processing technologies for wind turbines
- Intelligent fault diagnosis methodologies for wind turbines
- Remaining useful life prediction methods for wind turbines
- Safety and reliability assessment approaches for wind turbines
- Quantitative condition assessment techniques for wind turbines
- Repair and maintenance strategies for wind turbines
- Prognostics and health management systems for wind turbines
Prof. Dr. Hongli Gao
Guest Editor
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Keywords
- prognostics and health management
- dynamical modeling
- signal processing
- fault diagnosis
- remaining useful life prediction
- quantitative condition assessment
- maintenance strategies
- reliability analysis
- wind turbines
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