Research On Data Processing And Management Technique For Distributed Optical Fiber Vibration Sensing System

With the advantages of high sensitivity,large space dynamic range and high location accuracy etc.,distributed optical fiber vibration sensing system has been widely applied in various kinds of fields,including perimeter security,pipeline defense and communication fiber malfunction detection.Researches on data processing and management technique for distributed optical fiber vibration sensing system developed by our research group are carried out in this paper.Firstly,Optical time domain reflectometry(OTDR)technology is introduced.Sensing theories and performances of distributed optical fiber vibration sensing system based on Rayleigh scattering are analyzed.The mechanism and performances of distributed optical fiber sensing based on nonlinear scattering are briefly introduced.Successively the characteristic of disturbance pulses on the backscatter signal is analized and the distribution of disturbance pulses is explored.A disturbance localization algorithm is put forward which ground on the result that the location of disturbance pulse is normal distribution.Results show that the accuracy of localization is increased from ±20 m to ±4 m by means of the algorithm and the standard deviation of disturbance location is reduced from 6 to 1.5,which is reduced by 3/4.Then the data processing and management software is designed and the function is introduced.The software is developed with C# programming language and Mysql database management system.The priority-based data sorting algorithm of distributed optical fiber integrated sensing system has been proposed.Finally,experimentals on a testing system and an engineeing application system based on distributed optical fiber vibration sensing technologies are carried out.The experimental results demonstrate that the system can detect and locate the disturbance signals in every place of the sensing cable,and save alarm information into the database,which fits the needs of data processing and management.