Pressure monitoring has an important significance in fields such as petrochemical, energy, and power engineering. Compared to electronic pressure sensors, fiber optic grating pressure sensors have the advantages of small size, simple structure, and anti-electromagnetic interference. This paper proposes a polymer encapsulated fiber Bragg grating (FBG) dynamic pressure sensor and uses a semiconductor optical amplifier (SOA) - fiber ring laser (FRL) and an array waveguide grating (AWG) demodulator to form a fiber Bragg grating dynamic pressure sensing demodulation system. The experimental results show that the laser output of the SOA-FRL system is stable; in the fiber Bragg grating pressure test, the pressure sensitivity of the dynamic pressure sensor based on SOA-FRL can reach -33.17 pm/MPa at two pressure environments of 1~ 20 MPa and 0.1~0.8 MPa. The temperature dependence test shows that the sensitivity of the dynamic pressure sensor is 8.14 pm/℃ in the temperature range of 23 ~ 60℃. The temperature sensitivity of the dynamic pressure sensor is slightly lower than that of the reference FBG sensor (9.79 pm/℃). In addition, the effects of different sensitizing materials on the sensitivity of the pressure sensor are compared. The results show that the sensitivity of polymer materials is higher than that of metal materials. Because the proposed dynamic pressure sensor system based on fiber ring laser and array waveguide grating demodulator has the characteristics of high sensitivity, simple structure, and the demodulation of dynamic signals, it has a promising application prospect in oil exploitation, transportation, structural monitoring and other fields.
Distributed sensing technology provides engineers with powerful tools for position sensing, 3D sensing, shape sensing, and model validation applications. A new method for fiber-optic 3D shape sensing that can be used in minimally invasive biomedical devices is presented. A shape sensor was made using a heat-shrink tube, a Teflon hard tube and three strings of fiber Bragg grating (FBG). The sensor has compact structure, good flexibility. Besides, a shape reconstruction algorithm is established, for the location of each FBG array on the sensor, the calculation method of curvature and torsion is designed, and the continuous functions of curvature and torsion are constructed by cubic spline interpolation. The shape reconstruction under different bending conditions is realized by using the coordinate system rotation method. In the error analysis stage, the curvature error and torsion angle error of the sensor are optimized by introducing the scale factor. The results show that the optimized algorithm has good shape reconstruction effect.
Acoustic emission (AE) is an effective technology that can be used for structural health monitoring. One of the most attractive features is the ability to locate AE sources. Characteristic parameters of waveform importing Artificial Neural Network (ANN) model is proposed for acoustic emission source location. The waveform of AE signal is apperceived by sensors, and decreases dispersion effect by wavelet transform. Input of ANN includes characteristic parameters of AE signal, waveform data and characteristic quantities which have been preprocessed. Time difference of signals and other parameters acts as sample which can decrease the influence of wave speed. Based on the agreement that ANN has the ability approximate any nonlinear mapping, it is feasible to build a model of time difference of signals and other characteristics with AE source position. This locating method can be widely used in AE source location on account of high accuracy, practicality and reliability.
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