| Distributed optical fiber sensing technology has attracted widespread attention due to its unique advantages such as intrinsic safety,anti-electromagnetic interference,long service life and corrosion resistance.After more than 30 years of development,the technology has been widely used in various industrial infrastructure safety monitoring.Compared with other sensing technologies,optical fiber sensing technology uses optical fiber as the sensing medium and transmission medium,so it can realize continuous distributed monitoring of physical quantities such as temperature,stress and vibration along the sensing fiber.Distributed optical fiber Raman temperature sensing technology is based on Raman scattering temperature effect.It is an optical fiber sensing system for real-time measurement of space temperature fields,such as traffic tunnel fire monitoring,gas pipeline leakage monitoring,and intelligent dam water level temperature monitoring.However,the existing distributed optical fiber Raman temperature sensing technology has low temperature measurement accuracy,limited sensing distance.In addition,the temperature along the fiber is displayed as “list” mode or one-dimensional “temperature-distance” curve in conventional systems,this temperature display method cannot quickly locate the regions where temperature changes rapidly(such as local fire)into the actual three-dimensional(3D)environment.The above-mentioned defects limit the engineering applicability of distributed optical fiber Raman temperature sensing technology to a certain extent.Based on this,this paper proposes two novel temperature demodulation methods to optimize system performance indicators,which effectively improve the temperature measurement accuracy and temperature resolution.In addition,aiming at the defects of the existing Raman temperature sensing technology in the location of temperature rapid change regions,a temperature visual localization technology is proposed to realize the rapid and visual location of temperature rapid change region along the fiber.Finally,an upper computer operating system for tunnel fire monitoring is designed.The main research contents of this paper are as follows:(1)The influence of laser output power instability on the system performance is analyzed theoretically,and optical dynamic differential compensation technique is proposed.This technology effectively optimizes the temperature measurement accuracy of the system by compensating for the unstable output power of the laser during the calibration and measurement stages.After compensating for laser power fluctuations,at the sensing distances of 9.60 km and 18.27 km,the temperature measurement accuracy of the system is optimized from 9.2 ° C to 1.1 ° C,and 7.0 ° C to 1.9 ° C.(2)The effect of Rayleigh noise on system performance is theoretically analyzed and verified,and a Rayleigh noise suppression method is proposed to eliminate the redundant Rayleigh noise in Raman backscattered light.This method is based on two temperature calibration processes to eliminate Rayleigh noise crosstalk and effectively improve the signal-to-noise ratio of the system.The experimental results show that the system temperature accuracy is optimized from 6.2 °C to 1.7 °C at a sensing distance of 9.1 km,and the system temperature resolution is improved by 1.5 °C at a sensing distance of 10.0 km.(3)Aiming at the defects of the existing distributed optical fiber Raman temperature sensing technology in the long-distance tunnel fire location,a temperature visual localization technology was proposed.This technology is based on parametric modeling software Solidworks(SW),virtual instrument software Lab VIEW,and data processing platform MATLAB,which can quickly locate temperature rapid change regions along the one-dimensional sensing fiber to the actual three-dimensional space environment.Finally,a temperature visualization upper computer operating system for traffic tunnel fire monitoring is developed,and simulation experiments are designed to verify the feasibility of the system in visual localization. |
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