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M. R. Zhou and Y. Zhang, “Application of Artificial Neural Network BP Algorithm in Near Infrared Spectroscopy,” Infrared, Vol. 11, 2006, pp. 1-4.

has been cited by the following article:

• TITLE: Application of the Spectrum Peak Positioning Technology Based on BP Neural Network in Demodulation of Cavity Length of EFPI Fiber Optical Sensor

  AUTHORS: Mengran Zhou, Mengya Nie

  KEYWORDS: EFPI Fiber Optical Sensor; The Demodulation of Cavity Length; BP Neural Network; The Peak Positioning Technology

  JOURNAL NAME: Journal of Computer and Communications, Vol.1 No.7, December 2, 2013

  ABSTRACT: An Extrinsic Fabry-Perot Interferometric (EFPI) fiber optical sensor system is an online testing system for the gas density. The system achieves the measurement of gas density information mainly by demodulating the cavity length of EF- PI fiber optical sensor. There are many ways to achieve the demodulation of the cavity length. For shortcomings of the big intensity demodulation error and complex structure of phase demodulation, this paper proposes that BP neural net-work is used to locate the special peak points in normalized interference spectrum and combining the advantages of the unimodal and bimodal measurement achieves the demodulation of the cavity length. Through online simulation and actual measurement, the results show that the peak positioning technology based on BP neural network can not only achieve high-precision demodulation of the cavity length, but also achieve an absolute measurement of cavity length in large dynamic range.