Multi-objective layout optimization of structural deformation monitoring sensor combining with weight factor and sensing coverage

This study proposes a multi-objective sensor layout optimization method combining weight factor and sensing coverage, which aims to solve the problem that the uneven distribution of sensor layout for deformation monitoring of large composite structures in assembly leads to redundancy of monitoring coverage and fails to accurately reflect the global deformation of structures. First, a modal metric function model was established to determine the optimal number of sensors, and the optimal modal function was identified for layout optimization. Second, a functional model incorporating perceptual coverage, weight factor, and overlap was established. Using the weight factor and perceptual overlap as constraints and aiming for optimal modal and perceptual coverage rate, a statistical method was employed to allocate deformation weight factors, and the perceptual range was introduced to optimize layout angles, addressing uneven sensor distribution and redundant coverage while optimizing sensor placement. Finally, the feasibility of structural deformation monitoring was validated through comparative analysis by integrating the vision measurement system based on the optimization results. The results demonstrated that the relative error of deformation monitoring was within 6.47%, the root mean square error was 0.066 mm, and the reconstruction error rate was reduced by 26.16%. Based on the premise of lightweight sensors, this method allocates weight factors according to deformation trends, optimizes sensor positions and angles in combination with sensing coverage, effectively ensures the reliability of global deformation monitoring, and offers a novel approach for optimizing damage evolution sensor layouts.