Key Laboratory of Electronic Equipment Structure Design of Ministry of Education, Xidian University, Xi'an 710071, China.
Xinjiang Observatory, National Astronomical Observatories, Chinese Academy of Science, Urumqi 830011, China.
Sensors (Basel). 2019 Mar 15;19(6):1306. doi: 10.3390/s19061306.
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.
对于逆有限元方法 (iFEM)，应变传感器分布的不合适方案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重建精度的两个关键因素。先前的研究主要集中在应变-位移传递关系的鲁棒性的单目标优化上。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。为了解决这个问题，本文提出了一种用于传感器分布方案的双目标优化模型，采用多目标粒子群优化 (MOPSO) 来优化鲁棒性和准确性。首先，使用空心圆梁作为案例进行各种载荷下的静态分析。然后，建立了优化模型，并相应地得到了两种不同的应变传感器方案。最后，在所提出的方案中成功地进行了仿真计算和实验测试。结果表明，本文提出的优化模型的结果是选择应变传感器分布方案的一种很有前途的工具。
