Shape reconstruction of composite structures with monitoring of modeling changes using Brillouin scattering based distributed optical fiber strain sensor network
Shape reconstruction of composite structures with monitoring of modeling changes using Brillouin scattering based distributed optical fiber strain sensor network
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DOI：
10.1117/12.815606
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发表时间：
2009-03
期刊：
影响因子：
--
通讯作者：
M. Nishio;N. Takeda
中科院分区：
文献类型：
--
作者：
M. Nishio;N. Takeda
提出了一种基于布里渊散射的分布式光纤应变传感器PPP-BOTDA系统用于复合材料结构形状重构的新方法。我们已经构建了一个位移重建算法使用的有限元模型的目标结构。该算法不仅利用原始分布应变数据，而且利用应变分布曲线的非均匀性指标--归一化拉普拉斯值（NLV），可以检测结构边界条件的变化等建模变化。在验证中，该算法被应用于复合材料层合板试件的挠度识别与嵌入光纤网络。从NLV分布，试样的固定端条件的变化进行了评估，并使用更新的有限元模型，能够重建的挠度具有高精度。结果表明，本文提出的形状重建算法对有限元模型的变化具有鲁棒性。
This research proposes a novel approach for the shape reconstruction of composite structures using one of Brillouinscattering based distributed optical fiber strain sensors, PPP-BOTDA system. We have constructed a displacement reconstruction algorithm using the finite element model of the target structure. The remarkable point is that, not only using raw distributed strain data, but using an index of the non-uniformity of strain distribution profiles, which is the normalized Laplacian value (NLV), the algorithm can detect modeling changes, such as changes in boundary conditions of the structures. In the verification, the algorithm was applied to the deflection identification of a composite laminate specimen with an embedded optical fiber network. From the NLV distribution, the change of the fixed end condition of the specimen was evaluated, and using the updated FE model, the deflection was able to be reconstructed with high accuracy. From the result, we show the validity of the proposing shape reconstruction algorithm, which has robustness against FE model changes.