Application of Neural Network Technology in Optical Fiber Fault Early Warning System Simulation
Shuyu Li · Jisuanji fangzhen · 2012
Research warning timeliness problem of optical fiber fault early warning system.Due to the increase of fiber carrying portfolio,fiber optic lines have a lot of light power alarm information,which brings huge warning system data burden and influencing warning timeliness.Traditional database method for each optical power alarm information to process warning analysis one by one,can not quickly get warning factor,causing the problem of low warning timeliness.In order to solve this problem,this paper put forward a neural network technology application in optical fiber fault early warning system.Through the neural network technology a data mining model was built.A large mount of light power information were inputted to the alarm model to process data analysis,digging out the biggest decision value data and rapidly extract the warning factor,avoiding the low extraction efficiency problem of one by one to the early warning factor analysis.Finally,the warning factors were used to quickly finish early warning.Simulation results show that this method can quickly acquire warning factor from a large number of light power information,and timely complete the early warning of optical fiber fault.