Research Will Help Improve Blades’ Structural Safety and Reliability
By Edwin L. Aguirre
The U.S. Department of Energy (DOE) has awarded a two-year, $1.4 million grant to Mechanical Engineering Asst. Prof. Murat Inalpolat to develop and test a new, sound-based sensor system for monitoring the structural health and integrity of wind turbine blades.
“Our proposed monitoring system is low-cost, reliable and robust and it can be installed on both new and existing wind turbines,” says Inalpolat. “There is no other technology in today’s market that can monitor the condition and safety of turbine blades while they are operating.”
Commercial wind turbine blades, which are made of fiberglass composite, can measure 200 feet or more in length and weigh many tons.
“Because of continually varying operating conditions, all blades will experience splits, cracks or holes along their edges. These are currently not detectable except by visual inspection or after a blade has failed,” notes Inalpolat.
His system will use low-cost, low-maintenance wireless microphones mounted inside the blade’s structural cavity to passively monitor blade damage, while wireless speakers inside the cavity, along with a nearby external microphone, will be used for active monitoring.
Overall, Inalpolat has received about $2.5 million in funding for his acoustic research. In addition to the $1.4 million from the DOE, he was awarded about $1.1 million by the National Science Foundation, the university’s WindSTAR Center, the Massachusetts Clean Energy Center and internal grants.
Worldwide, wind capacity is growing. According to a recent report from the Global Wind Energy Council (GWEC), 2019 was the second biggest year for wind power, with installations of 60.4 gigawatts of new capacity worldwide and year-on-year growth of 19 percent. In the U.S., there are nearly 60,000 wind turbines, according to the U.S. Geological Survey. Globally, there are more than 341,000, according to GWEC.
Clean, Renewable Energy
Assisting Inalpolat on the project are Ph.D. students Jaclyn Solimine ’17 and Caleb Traylor.
“If we catch the damage in time, we can prevent it from progressing into a catastrophic failure of the blade and can then schedule repair or maintenance at an appropriate time,” she says.
Solimine and Traylor are collecting and analyzing preliminary acoustic data.
“We take the sound measurements we collect from actual, full-size wind turbine blades being tested at the state Wind Technology Testing Center in Charlestown and find out which features or characteristics of the sound will be most useful in detecting damage,” Solimine explains. “I have also been developing machine learning algorithms to train the computer to automatically detect anomalies in the data.
“This research has the potential to greatly increase the profitability of wind energy, which will help to ease our transition to renewable energy and create a considerable number of jobs in the wind energy sector.”