Research And Realization Of Novel Optical Fiber Sensing Systems

Optical fiber sensing system is becoming large-scale and intelligent.To realize practical large scale intelligent optical fiber sensing system,this dissertation focus on coherent FBG group sensing system,MZI fiber sensing system and auto-recognition of fiber sensing signals.The work is supported by the Foundation of Beijing Jiaotong University(2006XZ010).And the main achievements of the dissertation are listed as follows:●The performances of coherent FBG group sensing system are investigated. Based on the improved coupled-mode theory and Rouard method,the influence of the initial phase of FBG on the spectrum of coherent FBG group is proved.Simplified formulas are derived for the estimation of FSR for coherent FBG group formed by both uniform FBG and chirped FBG,and the estimation results are in good agreement with those calculated by more complicated numerical methods.The frequency limitation for measurement of time-varying signals by coherent FBG group is studied. Desensiblization is implemented by increasing the distance and the frequency of the vibration signal is demodulated more accurately.The frequency measurement results of coherent FBG group from 100Hz to 150000Hz consist with those of PZT sensor,and the sensing performance of coherent FBG group at high frequency band is even better than that of PZT sensor.The influence of the line width of laser on the sensitivity of coherent FBG group is studied from both phase fluctuation and frequency distribution. Theoretical and experimental analysis both prove that a better sensing performance is achieved when the ratio of laser FWHM and coherent FBG group FSR is smaller than 1%.●A bidirectional MZI distributed fiber sensing system with demodulation by 3×3 coupler and location by cross correlation is constructed,and both its sensing and location performances are investigated.The possible errors induced by the imperfect 3×3 coupler and by the improper sampling rate and nonsynchronous of the DAQ device are studied in detail.A method of initial calibration by signals that fluctuate strongly is proposed,and the calibration signal is selected by the number of extreme points of a single period of each branch,by which the demodulation error is greatly reduced.An empirical formula is proposed to estimate the highest frequency of interference signal. Based on the structure of the bidirectional MZI sensor system,the cross-correlation is limited within a short time series and the calculation amount is decreased.The smooth filter is adopted for noise reduction based on contrast experiments,and the cross-correlation is normalized,periodized and minimized,all of which increase the accuracy of the location.●The auto-recognition of fiber sensing signals is realized.Special structures for coherent FBG group and fiber MZI sensors are designed.For weak signals or strongly interferenced signals,winding method,flat layout method,special coated fiber method or spring separation method,solid separation method are proposed,and the recognition ability for object signals is improved.The physical features of the object signals are extracted from various aspects by the parameters analysis such as maximum amplitude, RMS,ringing count,pulse count,event count and duration,by the waveform transform analysis such as Fourier analysis,AR spectrum analysis and joint-time-frequency analysis,and by statistic analysis of the parameters analysis results or waveform transform analysis results.And the features of different object signals are extracted when the optical fiber sensing systems are applied for railway location,axel counter, fence destruction monitoring and pipe destruction monitoring.Auto-recognition of the railway location signals with coherent FBG sensing system is realized by a linear discrimination function based on Fisher criterion.And auto-recognition of the fence destruction signals with a MZI sensing system demodulated by a 3×3 coupler is realized by a LMBP neural network.