Multi-type sensor placement for optimal modal reconstruction of offshore wind turbine blades

A three-stage sensor placement framework is proposed to optimise the type combination, number, and positions of multi-type sensors for modal reconstruction of offshore wind turbine blades. A noise-weighted generalised sensitivity matrix is first constructed in state-space form based on estimation theory. Next, a global observability indicator is developed to identify the optimal combination of sensor types. An additional information gain indicator is integrated into the Non-dominated Sorting Genetic Algorithm Ⅱ to determine the optimal number of sensors. Finally, the sensor positions are determined from the Pareto set corresponding to the optimal number of sensors by maximising the average information gain. The feasibility of the proposed approach is validated on a numerical case study of an overhanging beam and an engineering case study of a 5 MW offshore wind turbine blade. A comparative analysis is conducted to demonstrate the superiority of the proposed method over conventional methods. Overall, the proposed method extends predefined multi-type sensor placement schemes into a systematic optimisation framework and provides enhanced capacity for response-field reconstruction of offshore wind turbine blade structures under limited measurement availability.