A Review on Data-driven Predictive Maintenance Approach for Hydro Turbines/Generators
- Shewei Wang, Kesheng Wang, Zhe Li
- Corresponding Author
- Shewei Wang
Available Online November 2016.
- https://doi.org/10.2991/iwama-16.2016.6How to use a DOI?
- predictive maintenance; hydro turbines generators; data-driven model; data mining
- Hydroelectricity as a renewable energy to respond the increasing population and environment crisis is widely used in the world. With the Hydro Turbines/Generators (HTG) being more and more complicated, the maintenance play a more and more important role in the production management in the hydro power plant. Many researches had concentrated on the predictive maintenance for the HTG in recent years. From the perspective of data-driven, this paper reviews and summarizes the key techniques regarding data acquisition, data processing, data analysis and data mining for the predictive maintenance of HTG. Especially, it place emphasis on the data-driven models for the diagnostics and prognostics. Finally, the paper concludes the current practices and presents a future research work.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Shewei Wang AU - Kesheng Wang AU - Zhe Li PY - 2016/11 DA - 2016/11 TI - A Review on Data-driven Predictive Maintenance Approach for Hydro Turbines/Generators BT - 6th International Workshop of Advanced Manufacturing and Automation PB - Atlantis Press SN - 2352-5428 UR - https://doi.org/10.2991/iwama-16.2016.6 DO - https://doi.org/10.2991/iwama-16.2016.6 ID - Wang2016/11 ER -