Research On The Demodulation Technique For Fiber Grating Sensor Based On FFP-TF

Fiber Bragg grating (FBG) sensor has a broad application prospect in many fields, and has been an important research direction in the field of modern sensing. Signal demodulation is the key to the sensor system. The performance of demodulation system directly determines the design level and practical performance of the sensing system. FBG sensor, obtaining the sensing information through the Bragg wavelength modulation, is a kind of typical wavelength modulation type fiber-optic sensors. How to accurately detect the wavelength shift of FBG sensor and then to demodulate signal effectively, is the key issue of FBG sensing system.A variety of solutions have been put forward to improve the efficiency and precision of the sensing signal demodulation. But so far, not yet a demodulation method can satisfy the wide-range, high-resolution, quasi-distributed and low-cost practical requirements. In order to further promote the FBG sensing technology application in engineering, the existing many kinds of FBG demodulation methods are classified and compared in this paper, and a set of FBG sensor demodulation system which can meet the demand of practical engineering is designed based on FFP-TF.The structure, principle and sensing properties of FBG are studied firstly, and then the technical solution of FBG sensing demodulation based on FFP-TF is designed. The nonlinear error of FFP-TF caused by hysteresis effect and temperature characteristic is analyzed, and the reference channel composed of athermal F-P etalon and reference grating is designed, and the calculation method of transmission spectrum peak wavelength of F-P etalon is analyzed, and then the real-time calibration of FFP-TF is realized.Accurate peak extraction using peak-detection algorithms is absolutely essential to improve the wavelength resolution and the accuracy of sensing system. There are many algorithms for peak detection, but the optimization of threshold value is not fully considered in existing comparisons of different algorithms. According to the characteristics of the reflection spectrum of FBG, the influence of power threshold value upon five kinds of typical peak-detection algorithms is studied, and the threshold value of each algorithm is optimized. Then the five algorithms are compared and analyzed from the error of peak detection and the operational efficiency by selecting different sampling intervals. Experiments show that the relationship between each peak-detection algorithm and power thresholds are different, and select the appropriate power threshold for each peak-detection algorithm can reduce their error effectively, and then can improve the resolution and accuracy of wavelength of FBG sensing system. Except centroid detection algorithm, increasing the sampling interval does not improve the operational efficiency of each algorithm significantly. Having optimized the power threshold respectively, Gaussian fitting algorithm has the smallest error and the best stability, and is appropriate for the demodulation of static signal and low-frequency dynamic signal. Centroid detection algorithm has the highest operational efficiency and relatively small error, and can be used in the demodulation of intermediate-frequency and high-frequency dynamic signal.At last, the FBG sensing demodulation system is configured, and the properties of the main components are analyzed. Moreover, the performance of the demodulation system is validated by the stability test, the repeatability test and the vibration test in the laboratory environment.