For reliable structural health monitoring and possible lifetime extension of offshore wind turbine support structures, accurate predictions of the response of these structures at all critical locations are required. Response predictions in offshore wind applications are, howev
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For reliable structural health monitoring and possible lifetime extension of offshore wind turbine support structures, accurate predictions of the response of these structures at all critical locations are required. Response predictions in offshore wind applications are, however, affected by large uncertainties on environmental (wind/wave/soil) as well as system parameters (eigenfrequencies/damping). As a first step towards robust health monitoring in the presence of these uncertainties, a methodology for simultaneous estimation of a response equivalent hydrodynamic loading and a system parameter from measured vibration signals is proposed. Use is made of a recently proposed coupled input-state-parameter estimation technique based on the Extended Kalman filter. The identification process is driven by a limited set of artificially generated vibration response data in combination with an approximate reduced-order model of the support structure. The results show that the proposed method is capable of tracking both the response equivalent hydrodynamic loading and a parameter that is related to the stiffness of the substructure.
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