{'fraction_non_alphanumeric': 0.017670682730923693, 'fraction_numerical': 0.0, 'mean_word_length': 5.592592592592593, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Shape reconstruction of composite structures with monitoring of modeling changes using Brillouin scattering based distributed optical fiber strain sensor network

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.