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Journal of Intelligent Material Systems and Structures
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1045389X09352813v1
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Article

Detecting Water Accumulation in Honeycomb Sandwich Structures by Optical-fiber-based Distributed Temperature Measurement

Shu Minakuchi1*, Haruka Tsukamoto2, and Nobuo Takeda1

1 Department of Advanced Energy, Graduate School of Frontier Sciences, The University of Tokyo, Japan
2 Department of Aeronautics and Astronautics, School of Engineering, The University of Tokyo, Japan

* To whom correspondence should be addressed. E-mail: minakuchi{at}smart.k.u-tokyo.ac.jp.


   Abstract

Water accumulation in honeycomb sandwich structures is a perceived problem for aircraft operators since it significantly degrades the structural integrity. The authors developed a fiber-optic-based technique to detect water accumulation in large-scale aircraft honeycomb sandwich structures. An optical-fiber network was formed in the adhesive layer and a Brillouin-based sensing system with high spatial resolution (specifically, pre-pump pulse Brillouin optical time domain analysis (PPP-BOTDA)) was utilized to detect the non-uniform internal temperature distribution during cooling in aircraft ascent. First, the temperature change during the ascent was investigated to evaluate the feasibility of the proposed technique. A verification test was then conducted using a Nomex honeycomb sandwich panel. The non-uniform temperature induced by water accumulation was detected from the peak-frequency distributions and the width of the Brillouin gain spectrum, which is the output of the PPP-BOTDA. The spectrum width, which represents the temperature non-uniformity within the spatial resolution of the PPP-BOTDA, could indicate the presence of smaller water accumulations compared to the peak frequency, which represents the temperature averaged over the spatial resolution, thus confirming the importance of evaluating the spectrum width. The developed system is quite useful for continuously monitoring large-scale aircraft sandwich structures.

First published on October 27, 2009, doi:10.1177/1045389X09352813

Journal of Intelligent Material Systems and Structures 2009;20:2249.

A more recent version of this article appeared on December 1, 2009


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