Improved KLT Algorithm for High-Precision Wavelength Tracking of Optical Fiber Bragg Grating Sensors

Abstract

Fiber Bragg Gratings (FBGs) are among the most popular optical fiber sensors. FBGs are well suited for direct detection of temperature and strain and can be functionalized for pressure, humidity, and refractive index sensing. Commercial setups for FBG interrogation are based on white-light sources and spectrometer detectors, which are capable of decoding the spectrum of an FBG array. Low-cost spectrometers record the spectrum on a coarse wavelength grid (typically 78–156 pm), whereas wavelength shifts of 1 pm or lower are required by most of the applications. Several algorithms have been presented for detection of small wavelength shift, even with coarse wavelength sampling; most notably, the Karhunen-Loeve Transform (KLT) was demonstrated. In this paper, an improved algorithm based on KLT is proposed, which is capable of further expanding the performances. Simulations show that, reproducing a commercial spectrometer with 156 pm grid, the algorithm estimates wavelength shift with accuracy well below 1 pm. In typical signal-to-noise ratio (SNR) conditions, the root mean square error is 22–220 fm, while the accuracy is 0.22 pm, despite the coarse sampling. Results have been also validated through experimental characterization. The proposed method allows achieving exceptional accuracy in wavelength tracking, beating the picometer level resolution proposed in most commercial and research software, and, due to fast operation (>5 kHz), is compatible also with structural health monitoring and acoustics.

Review and Analysis of Peak Tracking Techniques for Fiber Bragg Grating Sensors

“…The Capon-KLT method [ 68 ] is similar to the KLT, maintaining the calculations in Equations (37)–(39). The FFT in Equation (36) is replaced with a Capon frequency estimation [ 92 , 93 ]: the Capon algorithm allows achieving an improved estimate of the power spectral density of the input signal, and is not limited by the resolution as the FFT [ 92 ].…”

“…The method implemented in [ 68 ] for fast computation sets T = 5, and f k = [0.1, 0.125, 0.15, 0.175, 0.2].…”

Research on FBG-Based Sensor Networks and Their Coexistence with Fiber Optical Transmission Systems

“…For example, with passive FBG sensor solution, where multiple sensors are embedded in different layers of the road pavement, it is possible to monitor road condition during its lifetime. In addition, research of [19] also support the FBG technology topicality in relation to fiber optical sensors in SHM applications and especially highlighting different algorithm tests for detection of tiny wavelength shifts, hence pointing out the importance of an efficient available frequency spectrum and FBG application improvements. Considering that IoT and SHM field develops a closer connection with fiber optical sensors' field [20], therefore it is important to research FBG sensor coexistence with typical fiber optical transmission network infrastructure, starting from combined network architecture and ending with spectrum allocation and minimal spacing between sensors and data transmission channels.…”

Multichannel Approach for Arrayed Waveguide Grating-Based FBG Interrogation Systems

“…In several works [ 21 , 22 , 23 ], many changes in either the optoelectronic section or the detection algorithm have been implemented using, in some cases, an optical filter. This approach poses limitations to the speed and the robustness of the system since the optical filter needs a control signal to be operated.…”