This work evaluates the uncertainty of impact force and location estimates using an entropy-based impact identification algorithm applied to a commercial wind turbine blade. The effects of sensor placement, measurement directions and distance between impacts and sensor locations are studied. Results show that impacts to a 35m long wind turbine blade can be accurately located using a single tri-axial accelerometer regardless of sensor location. Uncertainties in impact force estimates are consistent across sensor locations. When omitting acceleration information in the spanwise direction, the bias and variance of force estimates is consistent, but when a single chan- nel of acceleration data is used, both increase somewhat. Impact force identification error was found to be uncorrelated with the distance between the impact and sensor location. The entropy of the estimated force time history, an indicator of the impulsivity of the estimate, was found to be a good indicator of the quality of force estimate. The bias and variance of impact force estimation error was found to be directly correlated with the entropy of the impact force estimate. When considering validation test data from all possible sensor configurations, the entropy of the recreated force estimates was a better indicator of the force magnitude prediction interval than was the specific sensor configuration. By classifying impact force estimates based upon entropy values, impact force prediction intervals were more precisely determined than when all validation impact data were considered at once.
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