基于神经网络的调频连续波光纤传感器扫描非线性复原技术

Frequency-scanningnon-linearity influences range-detection accuracy of optical fiber sensors. In this paper,the influence is analyzed and a recovering technique is proposed. Non-linearity isrecovered through the learning process of backpropagation neural network. Simulationresults show that very accurate estimation is achieved even under severe non-linearity ofthe scanning source. The on-line learning of neural network is also investigated to makethis method more practical.

参考文献

[1] Koichi Iiyama, Lu-tang Wang, Ken-ichi Hayashi. Linearizing optical frequency-sweep of a laser diode for FMCW reflectometry. J. Lightwave Technol., 1996, 14(2):173～178

[2] Keigo Lizuka, Satoshi Fujii. Neural-network laser radar. Appl. Opt., 1994, 33(13):2492～2501

[3] S. A. Egorov, L. G. Likhachiev, A. N. Mamaev et al.. Signal recovering in fiber optic sensors based on nonlinear FMCW technique. Opt. Comm., 1994, 111(5,6):438～444

[4] Xiaoming Sun. Theory and Application of Interferometry using Laser Diode. Beijing: National Defence Industry Press, 1998. 15～102 (in Chinese)

[5] Dexiu Huang, Xuefeng Liu. Semiconductor Laser and Their Applications. Beijing: National Defence Industry Press, 1999. 67～112 (in Chinese)

李阳, 冯正和, 龚建敏, 肖艳红, 廖延彪. 基于神经网络的调频连续波光纤传感器扫描非线性复原技术[J]. 中国激光, 2001, 28(3): 232. 李阳, 冯正和, 龚建敏, 肖艳红, 廖延彪. Nonlinear Recovering Technique Based on Neural Network for Frequency Modulated Continuous Wave Optical Fiber Sensors[J]. Chinese Journal of Lasers, 2001, 28(3): 232.

基于神经网络的调频连续波光纤传感器扫描非线性复原技术

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