Structural shape identification using distributed strain data from PPP-BOTDA

M. Nishio; T. Mizutani; N. Takeda

doi:10.1117/12.715342

10 April 2007 Structural shape identification using distributed strain data from PPP-BOTDA

M. Nishio, T. Mizutani, N. Takeda

Proceedings Volume 6530, Sensor Systems and Networks: Phenomena, Technology, and Applications for NDE and Health Monitoring 2007; 65301J (2007) https://doi.org/10.1117/12.715342
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2007, San Diego, California, United States

Abstract

The accurate shape sensing method is expected to be useful for large scaled structural health monitoring of aircraft structures. This research is trying to construct a high-accuracy structural shape identification method using distributed strain data from an optical fiber strain sensing system; pulse-prepump Brillouin optical time domain analysis (PPP-BOTDA) system. In addition, the optical fiber can be embedded in composite material, which has recently been applied for the structural material of aircrafts or some other large-scaled structures. In this paper, we carried out an experiment using composite specimen with an embedded optical fiber to show the characteristics of distributed data from PPP-BOTDA system. Moreover, a simple inverse analysis, which derives deformation from measured distributed strain data, was also carried out. From results of these verifications, the strain data from PPP-BOTDA system showed reasonable distributions suitable to the deformation of specimen. At the same time, it was also shown that, in using the distributed strain data for shape identification algorithm, we have to consider the changes in distribution profile at the discontinuous points of strain distribution along the fiber.

Citation Download Citation

M. Nishio, T. Mizutani, and N. Takeda "Structural shape identification using distributed strain data from PPP-BOTDA", Proc. SPIE 6530, Sensor Systems and Networks: Phenomena, Technology, and Applications for NDE and Health Monitoring 2007, 65301J (10 April 2007); https://doi.org/10.1117/12.715342

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