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Intrinsic Fabry-Perot Interferometric Fiber Sensor Based on Ultra-Short Bragg Gratings for Quasi-Distributed Strain and Temperature Measurements
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The health monitoring of smart structures in civil engineering is becoming more and more important as in-situ structural monitoring would greatly reduce structure life-cycle costs and improve reliability. The distributed strain and temperature sensing is highly desired in large structures where strain and temperature at over thousand points need to be measured simultaneously. It is difficult to carry out this task using conventional electrical strain sensors. Fiber optic sensors provide an excellent opportunity to fulfill this need due to their capability to multiplex many sensors along a single fiber cable. Numerous research studies have been conducted in past decades to increase the number of sensors to be multiplexed in a distributed sensor network. This dissertation presents detailed research work on the analysis, design, fabrication, testing, and evaluation of an intrinsic Fabry-Perot fiber optic sensor for quasi-distributed strain and temperature measurements. The sensor is based on two ultra-short and broadband reflection fiber Bragg gratings. One distinct feature of this sensor is its ultra low optical insertion loss, which allows a significant increase in the sensor multiplexing capability. Using a simple integrated sensor interrogation unit and an optical spectrum based signal processing algorithm, many sensors can be interrogated along a single optical fiber with high accuracy, high resolution and large dynamic range. Based on the experimental results and theoretical analysis, it is expected that more than 500 sensors can be multiplexed with little crosstalk using a frequency-division multiplexing technology. With this research, it is possible to build an easy fabrication, robust, high sensitivity and quasi-distributed fiber optic sensor network that can be operated reliably even in harsh environments or extended structures. This research was supported in part by U.S. National Science Foundation under grant CMS-0427951.
- Doctoral Dissertations