Deformation Reconstruction and Sensor Optimal Layout of Large-Span Spatial Structures Based on the Kalman Filter Method

With the continuous breakthroughs in modern construction technology, large-span spatial structures hold promise for urban construction. However, the great responsibility borne by such buildings makes their structural health crucial. Therefore, it is necessary to carry out the structural health condition monitoring of large-span spatial structures. First, this study proposes a structural response reconstruction technique for reconstructing key response information using a small amount of measurement information. Considering the model and measurement errors, the structural response reconstruction technique is investigated, and a reconstruction measurement theory with multiple types of sensors is proposed for practical engineering to meet the requirements of deformation monitoring. Through several simulation experiments, the results show that the reconstruction method proposed in this study achieves a better result in reconstruction accuracy than the traditional reconstruction method. In addition, the optimal layout of sensors is also a key issue for health monitoring, and this article proposes optimizing the layout of strain sensors and accelerometers using an improved genetic algorithm. The results of simulation experiments show that the number of strain sensors and accelerometers is reduced by half by this optimization method, which greatly reduces the cost and has a certain guiding significance for practical engineering.