University of Cincinnati research has led to cutting-edge software that will monitor wind turbine health, allowing the machines to work as efficiently as possible.
Students and faculty at UC's Center for Intelligence Maintenance Systems
are testing an early version of the software, based on real-world data from commercial wind farms near Shanghai, China, and in Taiwan and North America.
The software is potentially groundbreaking because most wind turbine performance figures are based on computer models. Since the technology is so new, there is still much unknown about the real-life, long-term performance life and maintenance needs of these high-priced energy generators.
"This is a very closed community. It's tough to get them to open up. We were very lucky to get the (real-world) wind data," says UC doctoral student Edzel Lapira, who co-authored "Wind Turbine Performance Assessment using Multi-regime Modeling Approach." His paper, which was recently published in the Journal of Renewable Energy, analyzed two years’ of operating and environmental data from commercial wind turbines, as well as information on the maintenance software.
This data in essence drives the software, which has several aims, according to UC:
- To predict maintenance needs so a wind turbine experiences near-zero downtime for repairs.
- To aid just-in-time maintenance functions and delivery of needed parts.
- To decrease spare-parts inventory.
- To ultimately predict and foster needed redesigns for wind turbines and their parts.
The team behind the research includes engineering master’s student Dustin Brisset, engineering doctoral students Hossein Davari and David Siegel, and Ohio Eminent Scholar Ohio in Advanced Manufacturing Jay Lee, professor of engineering.
The group continues working on the software, while seeking a wider community of wind farms to test, Lapira says.
"Prediction, that is the overall goal," Lapira says. "Eventually the software will predict that there is a fault, where it is and what part would be needed to fix it. Right now (turbine) manufactures will look at a large number of systems and if they see something wrong, call the operator who will look into it. It's still manual and takes expert knowledge. We are trying to automate that expert knowledge."
By Feoshia Henderson
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