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Research On Key Technology Of Quasi-distributed Fiber Bragg Grating Methane Sensing Based On Optical Time Domain Reflection

Posted on:2020-01-22Degree:MasterType:Thesis
Country:ChinaCandidate:M Y WangFull Text:PDF
GTID:2392330572988986Subject:Optical engineering
Abstract/Summary:PDF Full Text Request
In the process of industrialization in China,optical fiber gas sensor is an extremely important subject in industrial safety work.Among them,the coal mine industry is a very important industry in China's industrial development,so the research of optical fiber methane gas sensor used in coal mine has a very important significance for China's safety monitoring work.Therefore,it is of great practical significance to develop a distributed methane gas sensor with easy integration,simple structure and high accuracy.The optical fiber methane sensor described in this paper is a quasi-distributed optical fiber methane sensor system based on optical time-domain reflection and time-division multiplexing technology.The signals reflected from the sensing module are transmitted to the detection and acquisition module of the system through the circle.Because of the principle of optical time-domain reflection,the methane gas in coal mine can be located by the collected signals.In addition,because of the wide bandwidth characteristic of chirped grating,the absorption spectrum of methane gas can be simulated by changing the temperature and changing the output wavelength of the laser.The concentration demodulation of methane gas in the spectrum near the central wavelength can be realized by Gauss-Newton iteration method,which improves the accuracy of the system.The system has the advantages of simple structure,low cost and high accuracy of distributed methane detection.According to the quasi-distributed optical fiber methane sensing system,the demodulation method and system performance of methane concentration are described in detail.The contents of this paper are as follows:1.Introduce the basic principle of the quasi-distributed methane detection system,the basic theory of molecular absorption spectrum and Beer-Lambert absorption law.By introducing common multiplexing methods and grating detection principle,a time division multiplexing system structure for distributed measurement is designed.2.Introduce the structure design of the quasi-distributed methane detection system and the selection standard of components in the structure,and describe the working process of the system.The system is mainly divided into four modules,light source module,modulation module,sensor module and detection and acquisition module.3.The demodulation methods of methane concentration at single wavelength and multi-wavelength of quasi-distributed methane detection are introduced.Under a single wavelength,the formula of Beer-Lambert law is transformed into a first-order function of concentration-light intensity ratio,and the optimal regression coefficient is simulated according to the linear regression analysis method,and then the methane concentration is demodulated.The absorption spectra of methane near 1653.7 nm are simulated by Gauss-Newton iteration method at multi-wavelength.The measured concentration-intensity ratios at different wavelengths are superimposed on a simulated absorption spectrum.and the methane concentration is demodulated by integrating and peak operation.4.The experimental environment of the quasi-distributed methane detection system platform is introduced,and the performance indicators of the system are qualitatively and quantitatively analyzed under this environment to verify the practicability of the system.It is proved that the loss of the system is 1/12 of the intensity by detecting the loss in the optical link of the system,which meets the application requirements.Then,the white noise is removed by the cumulative average algorithm.Finally,the repeatability and stability of the system are proved to be suitable for monitoring methane concentration for a long time in application.
Keywords/Search Tags:Quasi-distributed, methane detection, univariate linear regression analysis, Gauss-Newton iteration method
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