Research On Extraction Of Sensing Information In Brillouin Scattering Distributed Fiber Optic Sensing System

As the economic development, the pursuit of material life continuously has beenimproved, especially the demands for the vehicles. People are increasingly concernedabout the safety and reliability since there is a growing number of security risks in theuse of the bridge, coupled with frequently occurrence of catastrophic geological disastersuch as landslides, mudslides and so on. Therefore, the diagnosis and prevention ofhidden dangers have an extremely actual significance.Brillouin Distributed Optical Fiber Sensing Technology with the advantages ofwide dynamic range, high accuracy is one of the major technical monitoring technology.So this paper mainly studies on the application of Brillouin Scattering SensingTechnology. Firstly, the paper analyses the linear relationship between the Brillouinfrequency shift and temperature and stress, and the linear relationship between theBrillouin signal intensity and temperature and stress. Secondly, it studies advantagesand disadvantages of the popular BOTDR detection system and does a comparison.Thirdly, it analyses and summarizes the factors that affect system performance.Therefore, the above studies provide the theory basis for constructing the BOTDRsystem and extracting the sensing information of BOTDR system.According to the signal characteristics of Brillouin scattering sensing in microwaveheterodyne BOTDR system, the paper mainly studies the principle of superimposedaverage depth algorithm, envelope demodulation of different wavelet functions ofMorlet wavelet, envelope demodulation of Harmonic wavelet, and LM algorithm. Thensimulates the process of extracting signal with these algorithm in the LabVIEWplatform.It can be seen from the simulation results that the superimposed average algorithmcan completely extract the signal from the strong noise signal, but it takes a longer time;the envelope demodulation function of different wavelet basis functions of Morletwavelet can extract the signal envelope, and there is no loss of protruding characteristicsin signal envelope，but the filtering function for noise to be further strengthened; TheHarmonic wavelet can also extracts the envelope of the signal, and the projectioncharacteristics, furthermore, it can strongly eliminate noise; LM algorithm canaccurately estimate the values of the parameters in the model of the Brillouin scattering signal, then can fit the Brillouin scattering signal spectrum, thus the paper can parse thesensing formation in Brillouin scattering signal. The above results have provided animportant reference for practical applications of the Brillouin distributed fiber sensingsystems.