PMID: 30226706Nov 1, 2016Paper

Combined Transmission Laser Spectrum of Core-Offset Fiber and BP Neural Network for Temperature Sensing Research

Guang pu xue yu guang pu fen xi = Guang pu
Fang WangYu-fang Liu

Abstract

When studying the wavelength response to the temperature of the single mode fiber interference laser spectrum, a three layer BP neural network model is built to solve the problem of high complexity and low accuracy of temperature measurement system. With the Discussion of the parameters of network model, we obtain the optimal network structure by comparing the data acquisition which is the laser wavelength corresponding to its temperature trained by BP neural network. With network training completed and the wavelength of input laser reached the specified value, the corresponding temperature prediction can be obtained from the output layer. In conclusion, it shows a clear correlation between the predictive value and the actual value, i.e. the former is approximately equal to the latter. The correlation coefficients of the calibration and prediction are 0.999 61 and 0.979 27, respectively; while the standard errors of the calibration and prediction are 0.017 5 and 0.144 0, respectively, and the average relative error of prediction set is 0.17%. The residual predictive deviation (RPD), obtained theoretically, is 5.258 3. RPD>3. It indicates that the calibration effect is good, and the model can be used for practical testing. In ad...Continue Reading

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