Sensor placement optimization for composite aircraft structures: A multi-objective Kriging-based approach

Abstract

Efficient sensor placement is critical for optimizing structural health monitoring (SHM) systems, particularly for composite aircraft structures. The challenge lies in determining the optimal number and positions of sensors to balance monitoring accuracy with resource efficiency. This study proposes a novel multi-objective optimization methodology that integrates Kriging interpolation for mode shape reconstruction with the Lichtenberg algorithm for sensor placement optimization. The approach minimizes the number of sensors while maximizing signal quality and minimizing interpolation error. The methodology is validated on both composite plates and the main rotor blade of an AS-350 helicopter using finite element modal analysis data. The results demonstrate significant reductions in the number of sensors required while maintaining high accuracy in capturing the structure’s dynamic response, showing the effectiveness of the proposed method for SHM applications in complex composite structures.