Grants and Contributions:
Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019).
Wind turbine blades operate at high relative velocities and are exposed to unsteady wind loading and harshx000D
environmental conditions, including rain, hail, lightning, etc. As a consequence, blades are damaged frequentlyx000D
and the associated repairs amount for the second largest downtime in turbine maintenance. Thus, routinex000D
inspections are required to identify blade damage in a timely fashion, so that required repairs can be performedx000D
in time to prevent further damage and/or catastrophic failure. Such inspections are commonly performed byx000D
specialized technical staff, adding significant cost to operation and maintenance of wind farms. This proposalx000D
will enable the use of a portable instrument platform involving high definition imaging in visible and infraredx000D
ranges to assess blades health on an operating turbine, minimizing the required time and avoiding anyx000D
downtime for inspections. The work will involve controlled experiments in a wind tunnel facilities as well asx000D
analysis of field data to help develop effective algorithms for robust blade damage detection.