Frequency-estimation-based signal-processing algorithm for white-light optical fiber Fabry–Perot interferometers

Shen, Fengyu; Wang, Anbo

doi:10.1364/ao.44.005206

Cited by 109 publications

(53 citation statements)

References 17 publications

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“…The low frequency component is mainly due to the DC offset in the reflection spectrum. A band pass filter is able to efficiently separate the fiber cavity signal from the lower frequency signal and higher frequency harmonics [171]. Finite impulse response (FIR) filters were selected due to the linear phase response to the frequency.…”

Section: Signal Analysis 331 Single-cavity Sensormentioning

confidence: 99%

Miniature fiber-optic multicavity Fabry–Perot interferometric biosensor

et al. 2005

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(ABSTRACT)Fiber-optic Fabry-Perot interferometric (FFPI) sensors have been widely used due to their high sensitivity, ease of fabrication, miniature size, and capability for multiplexing. However, direct measurement of self-assembled thin films, receptor immobilization process or biological reaction is limited in the FFPI technique due to the difficulty of forming Fabry-Perot cavities by the thin film itself. Novel methods are needed to provide an accurate and reliable measurement for monitoring the thin-film growth in the nanometer range and under various conditions. In this work, two types of fiber-optic multicavity Fabry-Perot interferometric (MFPI) sensors with built-in temperature compensation were designed and fabricated for thin-film measurement, with applications in chemical and biological sensing. Both the tubing-based MFPI sensor and microgap MFPI sensor provide simple, yet high performance solutions for thin-film sensing. The temperature dependence of the sensing cavity is compensated by extracting the temperature information from a second multiplexed cavity. This provides the opportunity to examine the thin-film characteristics under different environment temperatures.To demonstrate the potential of this structure for practical applications, immunosensors were fabricated and tested using these structures. Self-assembled polyelectrolytes served as a precursor film for immobilization of antibodies to ensure they retain their biological activity. This not only provides a convenient method for protein immobilization but also presents the possibility of increasing the binding capacity

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Section: Signal Analysis 331 Single-cavity Sensormentioning

confidence: 99%

Miniature fiber-optic multicavity Fabry–Perot interferometric biosensor

et al. 2005

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“…Non-constant phase-induced OPD demodulation jumps To interrogate a low-finesse FP sensor, the phase of the periodic fringe pattern is measured at either a fraction or all of the sampling points in the spectrogram [20,21,22,23]. This interference spectrum is represented by S(k)  cos[Φ(k)], where k=2π/λ is the optical wavenumber, λ is the wavelength, Φ(k) is the total interferogram phase which is expressed as Φ(k) = k  OPD + φ 0 , where φ 0 is an additional phase term caused by beam reflection and propagation [19,24].…”

Section: Sensor Signal Processing and The Total Phase Approachmentioning

confidence: 99%

“…This interference spectrum is represented by S(k)  cos[Φ(k)], where k=2π/λ is the optical wavenumber, λ is the wavelength, Φ(k) is the total interferogram phase which is expressed as Φ(k) = k  OPD + φ 0 , where φ 0 is an additional phase term caused by beam reflection and propagation [19,24]. In traditional OPD-based demodulation, the additional phase term φ 0 is usually assumed to be constant during measurement process and needs to be pre-calibrated [21,22]. However, physical changes in IFPI sensors can cause this term to vary during measurement (as discussed in Section 3.3.1, and in Ref [19,24] The SMS-IFPI sensors were typically interrogated using a swept-laser interrogation system (Micron Optics Si-720) over a spectral range of 1520-1570nm with spectral resolution of 2.5pm, dynamic range of 70dB, and a scanning rate of 0.5Hz.…”

Section: Sensor Signal Processing and The Total Phase Approachmentioning

confidence: 99%

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Multiplexed Optical Fiber Sensors for Coal Fired Advanced Fossil Energy Systems

Wang¹,

Pickrell²

2012

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This three-year project started on October 1, 2008. In the project, a fiber optical sensing system based on intrinsic Fabry-Perot Interferometer (IFPI) was developed for strain and temperature measurements for Ultra Supercritical boiler condition assessment. Investigations were focused on sensor design, fabrication, attachment techniques and novel materials for high temperature and strain measurements.At the start of the project, the technical requirements for the sensing technology were determined together with our industrial partner Alstom Power. As is demonstrated in Chapter 4, all the technical requirements are successfully met. The success of the technology extended beyond laboratory test; its capability was further validated through the field test at DOE NETL, in which the sensors yielded distributed temperature mapping of a testing coupon installed in the turbine test rig. The measurement results agreed well with prior results generated with thermocouples.In this project, significant improvements were made to the IFPI sensor technology by splicing condition optimization, transmission loss reduction, sensor signal demodulation and sensor system design. These innovations have yielded three journal publications and two conference papers.

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“…White-light interferometry [7], in which the interferometer is illuminated either by a broadband optical source or a wavelength-tunable laser and its reflected spectrum is analyzed, has shown promising advantages over other interrogation counterparts in terms of demodulation accuracy, absolute measurement and immunity to optical power instability. In order to make accurate and reliable measurements, the sensor spectrum needs to be characterized carefully, some advanced signal processing algorithms have been developed to this end [7][8][9]. While it is well understood that the demodulation error scales with noise power in the spectrum [10], the demand for high fringe visibility becomes crucial, especially if a multimode fiber (MMF) is used for excitation.…”

Section: Introductionmentioning

confidence: 99%

Decoding the spectra of low-finesse extrinsic optical fiber Fabry-Perot interferometers

Ma¹,

Dong²,

Gong³

et al. 2011

Opt. Express

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A theoretical model is developed to address the fringe visibility and additional phase in the interference spectra of low-finesse extrinsic optical fiber excited Fabry-Pérot interferometers. The model described in the paper applies to both single-mode and multimode fiber excitations; according to the theory, the fringe visibility and additional phase term are primarily determined by the working wavelength and angular power density distribution outputting from the excitation fiber, rather than based on spatial and temporal degree of coherence. Under certain approximations, the output interference intensity and the spatial power density distribution projected onto the fiber axis form a Fourier-transform pair, which potentially provides a tool for spatial density distribution analysis of fiber output. With excellent agreement with experiments, the theory presented in this paper leads to design guidelines for Fabry-Pérot interferometric sensors and insightful physical understanding of such devices. Interferometric Optical Fiber Sensor Using Kirchhoff's Diffraction Formalism," Opt. Fiber Technol. 1(4), 380-384 (1995). 14. F. Pérennès, P. C. Beard, and T. N. Mills, "Analysis of a low-finesse Fabry-Perot sensing interferometer illuminated by a multimode optical fiber," Appl. Opt. 38(34), 7026-7034 (1999 Optical Society of America. Cheng Ma, Bo Dong, Jianmin Gong, and Anbo Wang, "Decoding the spectra of low-finesse extrinsic optical fiber Fabry-Perot interferometers," Opt. Express 19, 23727-23742 (2011 ©2011 Optical Society of America

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Frequency-estimation-based signal-processing algorithm for white-light optical fiber Fabry–Perot interferometers

Cited by 109 publications

References 17 publications

Miniature fiber-optic multicavity Fabry–Perot interferometric biosensor

Miniature fiber-optic multicavity Fabry–Perot interferometric biosensor

Multiplexed Optical Fiber Sensors for Coal Fired Advanced Fossil Energy Systems

Decoding the spectra of low-finesse extrinsic optical fiber Fabry-Perot interferometers

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