Multi-Objective Particle Swarm Optimization of Sensor Distribution Scheme with Consideration of the Accuracy and the Robustness for Deformation Reconstruction
Multi-Objective Particle Swarm Optimization of Sensor Distribution Scheme with Consideration of the Accuracy and the Robustness for Deformation Reconstruction
复制标题
考虑变形重建精度和鲁棒性的传感器分布方案多目标粒子群优化
DOI：
10.3390/s19061306
复制
发表时间：
2019-03-02
期刊：
影响因子：
3.9
通讯作者：
Xu, Qian
中科院分区：
文献类型：
--
作者：
Zhao, Feifei;Bao, Hong;Xu, Qian
对于逆有限元法（iFEM），应变传感器分布方案不合理会导致变形重建精度的严重下降。应变-位移传递关系的鲁棒性和重建位移的准确性是影响重建精度的两个关键因素。以往的研究主要集中在对应变-位移传递关系的鲁棒性进行单目标优化。然而，研究人员发现，使用单目标优化很难在鲁棒性和准确性之间达到相互平衡。为了解决这一问题，本文提出了一种传感器分布方案的双目标优化模型，其中采用多目标粒子群优化（MOPSO）对传感器分布方案的鲁棒性和精度进行优化。最初，一个空心圆梁受到各种载荷作为一个案例进行静力分析。其次，建立了优化模型，得到了两种不同的应变传感器方案。最后，本文提出的方案在仿真计算和实验测试中均取得了成功。结果表明，本文提出的优化模型的结果对于应变传感器分布方案的选择是一个很有前途的工具。
For the inverse finite element method (iFEM), an inappropriate scheme of strain senor distribution would cause severe degradation of the deformation reconstruction accuracy. The robustness of the strain-displacement transfer relationship and the accuracy of reconstruction displacement are the two key factors of reconstruction accuracy. Previous research studies have been focused on single-objective optimization for the robustness of the strain-displacement transfer relationship. However, researchers found that it was difficult to reach a mutual balance between robustness and accuracy using single-objective optimization. In order to solve this problem, a bi-objective optimal model for the scheme of sensor distribution was proposed for this paper, where multi-objective particle swarm optimization (MOPSO) was employed to optimize the robustness and the accuracy. Initially, a hollow circular beam subjected to various loads was used as a case to perform the static analysis. Next, the optimization model was established and two different schemes of strain sensor were obtained correspondingly. Finally, the proposed schemes were successfully implemented in both the simulation calculation and the experiment test. It was found that the results from the proposed optimization model in this paper proved to be a promising tool for the selection of the scheme of strain sensor distribution.