A review of spectrally coded multiplexing techniques for fibre grating sensor systems

Childs, Paul; Wong, Anthony; Yan, Binbin; Li, Mo; Peng, Gang-Ding

doi:10.1088/0957-0233/21/9/094007

Cited by 7 publications

(5 citation statements)

References 33 publications

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“…In the second example, a new type of FBG called amplitude-modulated chirped FBGs (AMCFBGs) was designed and fabricated, and based on that, a new multiplexing technique called spectral overlap multiplexing was proposed and experimentally demonstrated (Childs et al, 2010, Wong et al, 2007a, 2007b. We show that, the DWT played a central role in the demultiplexing, demodulation and analysis of these multiplexed novel sensor signals.…”

Section: Application Case 2 -Multiplexing and Demultiplexing Of Multimentioning

confidence: 99%

Applications of Discrete Wavelet Transform in Optical Fibre Sensing

Wong¹,

Peng²

2011

Discrete Wavelet Transforms - Biomedical Applications

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This chapter presents a comprehensive review of recent advances in the applications of discrete wavelet transform (DWT) in optical fibre sensing. DWT, like Fourier transform (FT), is a versatile and powerful mathematical tool to process, extract and analyse data. In fibre sensing, DWT is particularly useful in the demodulation, demultiplexing and denoising of sensor data, as well as in the detection, extraction and interpretation of measurand-induced change from an acquired sensor signal. Both continuous and discrete has found a wide variety of applications in fibre sensing, and has been extensively used for fibre Bragg gratings (FBGs) and interferometric sensors. For example, Chan et al. (2007, 2010) used wavelet transform (both continuous and discrete) in reducing noise and increasing wavelength detection accuracy of FBGs; Jones (2000a, 2000b) used in the edge detection and crack detection of FBGs embedded in some structures; Staszewski et al. (1997) and Bang & Kim (2010) used for the detection of acoustic wave induced by impact and defect in composite plates; Gangopadhyay et al. (2005, 2006) used to extract and analyse fibre Fabry-Perot interferometer signals; Lamela-Rivera et al. (2003) used in the detection of partial discharges from high-power transformers; Tomic et al. (2010) in pressure sensing; and Wang et al. (2001) in the health monitoring of ship hull structure. This chapter begins with a brief introduction on the applications of DWT in fibre sensing. This follows by the principles and approaches of using DWT. Several important and fundamental formulations and concepts, such as the use of DWT in signal demodulation, demultiplexing and noise reduction will be presented. Next, four exemplary application cases of using DWT in fibre sensing are presented. More specifically, representative topics with regard to sensor signal analysis, signal demodulation, noise reduction and demultiplexing of multiplexed sensor systems are described in details. Finally, conclusions to summarise the chapter is given. 2. Principles and approaches In fibre sensing, there are two areas of signal analysis that DWT has been widely employed, namely sensor signal demodulation and noise reduction. The former is accomplished by the theory of Multiresolution analysis (MRA) and the latter by the wavelet denoising. This section will describe these two DWT techniques qualitatively, and all of the subsequent examples are essentially based on them. www.intechopen.com Discrete Wavelet Transforms-Biomedical Applications 222 2.1 Sensor signal demodulation The DWT demodulation technique presented here is used to demodulate and demultiplex many types of multiplexed sensor signals, and it works best with periodic sinusoidal functions, which is often the case for most interferometric signals. Excellent references in the theory and properties of wavelets can be found in (

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Section: Application Case 2 -Multiplexing and Demultiplexing Of Multimentioning

confidence: 99%

Applications of Discrete Wavelet Transform in Optical Fibre Sensing

Wong¹,

Peng²

2011

Discrete Wavelet Transforms - Biomedical Applications

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“…TDM separates each sensor in the time domain through delaying the time of arrival difference for each reflected signal [8], placing a limitation on the acquisition speed and spatial distance between individual sensors [9]. The technique of optical code division multiplexing also enable a large number of sensors be placed in a given bandwidth, however requires significant complexity in the fabrication of the FBG sensors in order to create highly specialized output spectra [10,11].…”

Section: Introductionmentioning

confidence: 99%

“…(11) where v j i represents the wavelength shift of the ith FBG (i = 1, 2, …, n) in the jth particle per increment ( j = 1, 2, …, m), based on which the total wavelength shift λ ∆ j i is updated as by equation (10). ω is a weight factor, and c 1 and c 2 are called acceleration constants.…”

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confidence: 99%

Interrogation of a spectral profile division multiplexed FBG sensor network using a modified particle swarm optimization method

Guo

Hackney

Pankow

et al. 2017

Meas. Sci. Technol.

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This paper applies the concept of spectral profile division multiplexing to track each Bragg wavelength shift in a serially multiplexed fiber Bragg grating (FBG) network. Each sensor in the network is uniquely characterized by its own reflected spectrum shape, thus spectral overlapping is allowed in the wavelength domain. In contrast to the previous literature, spectral distortion caused by multiple reflections and spectral shadowing between FBG sensors, that occur in serial topology sensor networks, are considered in the identification algorithm. To detect the Bragg wavelength shift of each FBG, a nonlinear optimization function based on the output spectrum is constructed and a modified dynamic multi-swarm particle swarm optimizer is employed. The multiplexing approach is experimentally demonstrated on data from multiplexed sensor networks with up to four sensors. The wavelength prediction results show that the method can efficiently interrogate the multiplexed network in these overlapped situations. Specifically, the maximum error in a fully overlapped situation in the specific four sensor network demonstrated here was only 110 pm. A more general analysis of the prediction error and guidelines to optimize the sensor network are the subject of future work.

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“…The study of fiber optics sensors started no later than 1977 [ 1 – 4 ], and since the nnumerous novel types of fiber optics sensors have been studied and demonstrated. So far, some kinds of fiber optics sensors have already been commercialized for industry applications, e.g., FBGs have been successfully applied for structure health monitoring (SHM) of large-scale civil infrastructures like bridges, dams and tunnels, and performance monitoring of key equipment and machinery and so on [ 5 ].Technologies for sensing networks, including interrogation and multiplexing techniques have also been studied intensively, aiming for high channel count, fast system response and better long term performance with low cost, e.g., spectrally coded multiplexing techniques [ 5 ], fiber loop ring down cavity sensing systems [ 6 ], etc. Nowadays, with the dramatically increasing research on fiber technology, the research on some advanced photonic technologies such as fiber lasers and microwave photonics technology has started to help realize novel fiber optic sensing applications.…”

Section: Introductionmentioning

confidence: 99%

Fiber Sensor Systems Based on Fiber Laser and Microwave Photonic Technologies

Chen

Cai

2012

Sensors

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Fiber-optic sensors, especially fiber Bragg grating (FBG) sensors are very attractive due to their numerous advantages over traditional sensors, such as light weight, high sensitivity, cost-effectiveness, immunity to electromagnetic interference, ease of multiplexing and so on. Therefore, fiber-optic sensors have been intensively studied during the last several decades. Nowadays, with the development of novel fiber technology, more and more newly invented fiber technologies bring better and superior performance to fiber-optic sensing networks. In this paper, the applications of some advanced photonic technologies including fiber lasers and microwave photonic technologies for fiber sensing applications are reviewed. FBG interrogations based on several kinds of fiber lasers, especially the novel Fourier domain mode locking fiber laser, have been introduced; for the application of microwave photonic technology, examples of microwave photonic filtering utilized as a FBG sensing interrogator and microwave signal generation acting as a transversal loading sensor have been given. Both theoretical analysis and experimental demonstrations have been carried out. The comparison of these advanced photonic technologies for the applications of fiber sensing is carried out and important issues related to the applications have been addressed and the suitable and potential application examples have also been discussed in this paper.

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A review of spectrally coded multiplexing techniques for fibre grating sensor systems

Cited by 7 publications

References 33 publications

Applications of Discrete Wavelet Transform in Optical Fibre Sensing

Applications of Discrete Wavelet Transform in Optical Fibre Sensing

Interrogation of a spectral profile division multiplexed FBG sensor network using a modified particle swarm optimization method

Fiber Sensor Systems Based on Fiber Laser and Microwave Photonic Technologies

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