Type of Document Dissertation Author Ma, Cheng Author's Email Address firstname.lastname@example.org URN etd-09252012-225720 Title Modeling and Signal Processing of Low-Finesse Fabry-Perot Interferometric Fiber Optic Sensors Degree PhD Department Electrical and Computer Engineering Advisory Committee
Advisor Name Title Wang, Anbo Committee Chair Heflin, James R. Committee Member Pickrell, Gary R. Committee Member Poon, Ting Chung Committee Member Xu, Yong Committee Member Keywords
- Fiber Optic Sensors
- Fiber Optics
- White-Light Interferometry
Date of Defense 2012-09-04 Availability unrestricted AbstractThis dissertation addresses several theoretical issues in low-finesse fiber optic Fabry-Perot Interferometric (FPI) sensors. The work is divided into two levels: modeling of the sensors, and signal processing based on White-Light-Interferometry (WLI).
In the first chapter, the technical background of the low-finesse FPI sensor is briefly reviewed and the problems to be solved are highlighted.
A model for low finesse Extrinsic FPI (EFPI) is developed in Chapter 2. The theory is experimentally proven using both single-mode and multimode fiber based EFPIs. The fringe visibility and the additional phase in the spectrum are found to be strongly influenced by the optical path difference (OPD), the output spatial power distribution and the working wavelength; however they are not directly related to the light coherence.
In Chapter 3, the Single-Multi-Single-mode Intrinsic FPI (SMS-IFPI) is theoretically and experimentally studied. Reflectivity, cavity refocusing, and the additional phase in the sensor spectrum are modeled. The multiplexing capacity of the sensor is dramatically increased by promoting light refocusing. Similar to EFPIs, wave-front distortion generates an additional phase in the interference spectrogram. The resultant non-constant phase plays an important role in causing abrupt jumps in the demodulated OPD.
WLI-based signal processing of the low-finesse FP sensor is studied in Chapter 4. The lower bounds of the OPD estimation are calculated, the bounds are applied to evaluate OPD demodulation algorithms. Two types of algorithms (TYPE I & II) are studied and compared. The TYPE I estimations suffice if the requirement for resolution is relatively low. TYPE II estimation has dramatically reduced error, however, at the expense of potential demodulation jumps. If the additional phase is reliably dependent on OPD, it can be calibrated to minimize the occurrence of such jumps.
In Chapter 5, the work is summarized and suggestions for future studies are given.
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