Chinese Journal of Lasers, Volume. 39, Issue 4, 402007(2012)

Detection Method of Laser Gyroscope Cavity Adjustment Based on Momentum BP Neural Network

Ma Li1、*, Xu Cixiong1, Ouyang Hangkong1, Rong Weibin2, and Sun Lining2
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  • 1[in Chinese]
  • 2[in Chinese]
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    In order to solve the manual detection drawbacks of laser gyroscope cavity adjustment, such as low quality and low efficiency, a multi-sensor information fusion detection method is proposed using a CCD camera and a photomultiplier. The center of the facula and the diaphragm and the loss of laser gyroscope are obtained and then transmitted to the fusion center. After fusion calculation, the integrated judgment is produced. The fusion system utilizes the momentum back-propagation neural network (BPNN) to fuse the multi-source information and output the final decision. And according to the modes of the detected signals and output decision, a three layers topology structure including an input layer, a hidden layer and an output layer is designed. The experimental results indicate that the accuracy of the proposed cavity adjustment detection method is 93.81%, which is higher than the manual step detection method using a single sensor about 6%.

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    Ma Li, Xu Cixiong, Ouyang Hangkong, Rong Weibin, Sun Lining. Detection Method of Laser Gyroscope Cavity Adjustment Based on Momentum BP Neural Network[J]. Chinese Journal of Lasers, 2012, 39(4): 402007

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    Paper Information

    Category: Laser physics

    Received: Nov. 8, 2011

    Accepted: --

    Published Online: Mar. 8, 2012

    The Author Email: Ma Li (malian@shu.edu.cn)

    DOI:10.3788/cjl201239.0402007

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