Paper
10 April 2014 Operational model updating of spinning finite element models for HAWT blades
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Abstract
Structural health monitoring (SHM) relies on collection and interrogation of operational data from the monitored structure. To make this data meaningful, a means of understanding how damage sensitive data features relate to the physical condition of the structure is required. Model-driven SHM applications achieve this goal through model updating. This study proposed a novel approach for updating of aero-elastic turbine blade vibrational models for operational horizontal-axis wind turbines (HAWTs). The proposed approach updates estimates of modal properties for spinning HAWT blades intended for use in SHM and load estimation of these structures. Spinning structures present additional challenges for model updating due to spinning effects, dependence of modal properties on rotational velocity, and gyroscopic effects that lead to complex mode shapes. A cyclo-stationary stochastic-based eigensystem realization algorithm (ERA) is applied to operational turbine data to identify data-driven modal properties including frequencies and mode shapes. Model-driven modal properties are derived through modal condensation of spinning finite element models with variable physical parameters. Complex modes are converted into equivalent real modes through reduction transformation. Model updating is achieved through use of an adaptive simulated annealing search process, via Modal Assurance Criterion (MAC) with complex-conjugate modes, to find the physical parameters that best match the experimentally derived data.
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Antonio Velazquez, R. Andrew Swartz, Kenneth J. Loh, Yingjun Zhao, Valeria La Saponara, Robert J. Kamisky, and Cornelis P. van Dam "Operational model updating of spinning finite element models for HAWT blades", Proc. SPIE 9061, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2014, 90610U (10 April 2014); https://doi.org/10.1117/12.2046434
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KEYWORDS
Data modeling

Algorithms

Structural health monitoring

Stochastic processes

Wind turbine technology

Matrices

System identification

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