KEYWORDS: Reconstruction algorithms, Signal to noise ratio, Denoising, Interference (communication), Sensors, Matrices, Signal processing, Chemical species, Fiber Bragg gratings, Detection theory
Aiming at the noise signal caused by external environment and sensor reuse in the demodulation system of large capacity fiber grating sensor network, a Threshold Retained Orthogonal Matching Pursuit (TROMP) reconstruction algorithm is proposed based on compressed sensing theory. In this algorithm, the useful signal can be effectively recovered from the noise signal by improving the threshold setting, atom selection and iteration stop condition. Experiments show that: TROMP algorithm can achieve ideal denoising and reconstruction effect under less observation value, the SNR of the system is increased by 10 dB, the root mean square error is less than 0.0071, and the number of cross-relations can reach 0.9999. Compared with similar algorithms, the running time is shortened by more than half, and the comprehensive performance of noise signal processing for FBG sensor system is better than other reconstruction algorithms.
Aiming at the poor accuracy of traditional single peak detection algorithm in fiber grating demodulation, this paper proposes a symmetry corrected Gaussian nonlinear fitting algorithm based on Hilbert transform (HT-EXG) for multi peak detection. The algorithm uses Hilbert transform to segment the input reflection spectrum and uses exponential modified Gaussian nonlinear fitting algorithm to correct and optimize its peak position, so as to achieve accurate positioning of the reflection spectrum. The experimental results show that the proposed HT-EXG algorithm improves the accuracy of FBG peak demodulation and the stability of the system. The average error of peak detection is less than 3 pm, and the system stability is better than 0.5 pm. It provides an accurate demodulation method for FBG sensor network peak detection.
At present, temperature sensors are relatively mature, and commercial sensors are mainly thermistors and thermocouples, which have the advantages of low cost and large temperature range. However, it is difficult to meet the requirements of some special occasions, such as strong electromagnetic interference, strong corrosiveness and other environments, and high-precision temperature measurement cannot be performed. Fiber Bragg grating is a kind of fiber optic sensor, which has the advantages of anti-electromagnetic interference resistance, corrosion resistance and high sensitivity. The fiber Bragg grating obtains sensing information by modulating the Bragg wavelength of the fiber through the change of the external temperature parameter, and can automatically monitor the temperature change of the object to be measured. In this paper, the temperature sensing test experiment of fiber Bragg grating is carried out. The results show that the center wavelength of the grating has a good linear response to the temperature of the object to be measured, and the temperature error is within ±0.5℃. temperature sensing.
This paper proposes a snake scanning focus-spot reconstruction method based on multi-pixel information fusion, which can detect the centroid-position and relative-intensity distribution of small-scale focus-spots. The theoretical analysis is consistent with the experimental results.
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