In order to find a more accurate center wavelength detection fitting algorithm for fiber Bragg grating (FBG) reflection spectrum, Based on the theory of neural network, we designed different neural network to study and fit the spectral data which has been acquired from FBG.In this paper,we have studied BP,RBFand wavelet neural network structure,comparing the network training time and the result of fitting curves ,wavelet neural network is proved to be the best fitting algorithm.
This paper is aimed at designing a special pulse power amplification system for an ultrahigh-speed pulser that is used in Brillouin optical fiber sensing system. This amplification system consists of three parts, that is, signal receiving part, power amplifying part and 180 degree phase shifting part. Considering the fact that signals produced by the pulser are 1.2V differential PCML square wave signals and have ultrafast rising and falling transition time, high speed op-amps were adopted to receive signals and isolate pulser and amplifier. Since square wave signals have ultralow duty ratio, the power amplifier was designed with only one transistor working in switch-mode. As the effective frequency component of the pulse is up to 1500MHz, this design made use of a high speed high voltage operational amplifier to shift phase for signals. The eventually result indicates that, this amplification system can amplify square wave signals whose pulse width ranges from 2ns to 5ns, and voltage amplitude 1V of square wave signals with maximum duty ratio 5:105and minimum duty ratio 1:106up to 8V.
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