Dec. 2018

Article Contents

Chinese Optics> 2018> 11(6): 1024-1031.

QIAN Wei-zhu, YANG Li-bao. A fiber optic gyro error compensation method based on wavelet neural network[J]. Chinese Optics, 2018, 11(6): 1024-1031. doi: 10.3788/CO.20181106.1024

Citation:

QIAN Wei-zhu, YANG Li-bao. A fiber optic gyro error compensation method based on wavelet neural network[J].Chinese Optics, 2018, 11(6): 1024-1031.doi:10.3788/CO.20181106.1024

QIAN Wei-zhu, YANG Li-bao. A fiber optic gyro error compensation method based on wavelet neural network[J]. Chinese Optics, 2018, 11(6): 1024-1031. doi: 10.3788/CO.20181106.1024

Citation:

QIAN Wei-zhu, YANG Li-bao. A fiber optic gyro error compensation method based on wavelet neural network[J].Chinese Optics, 2018, 11(6): 1024-1031.doi:10.3788/CO.20181106.1024

PDF( 2016 KB)

A fiber optic gyro error compensation method based on wavelet neural network

doi:10.3788/CO.20181106.1024

QIAN Wei-zhu^{1, 2,},
YANG Li-bao^{1, 3,,}

1.
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
2.
University of Chinese Academy of Sciences, Beijing 100039, China
3.
College of Mechanical and Electric Engineering, Changchun University of Science and Technology, Changchun 130022, China

Funds:

National Natural Science Foundation of China51275504

More Information

Corresponding author:YANG Li-bao, E-mail:yanglibao228@163.com
Received Date:11 Nov 2017
Rev Recd Date:13 Dec 2017
Publish Date:01 Dec 2018

Abstract

Abstract

In order to improve the measurement accuracy of fiber optic gyroscope, an error compensation method based on wavelet neural network(WNN) is proposed. Firstly, the main trend term in the gyro signal is extracted by the Mallat decomposition algorithm in wavelet analysis, and the error residuals are reconstructed. The reconstructed signal is then used as the target output of the wavelet neural network, and the original gyro signal is used as the training input. In order to improve the training speed of the WNN and prevent it from falling into local minimum values, the method of increasing the momentum factor and adaptively adjusting the learning rate is used. The neural network model established after training has a good ability to estimate the fiber optic gyro error. The final result shows that after the compensation by the WNN method, the output precision of the fiber optic gyroscope reaches 0.0194°/s, which improves the measurement performance of the fiber optic gyroscope.
- fiber optic gyro,
- wavelet neural network,
- wavelet analysis,
- error compensation,
- trend term extraction

FullText(HTML)

References (15)

References

[1]	徐丽娜, 邓正隆.SINS初始对准中光纤陀螺EMD滤波[J].中国光学, 2015, 8(6):933-941. //www.illord.com/CN/abstract/abstract9365.shtml XU L N, DENG ZH L. EMD filtering of fiber gyro in initial alignment of SINS[J]. Chinese Optics, 2015, 8(6):933-941.(in Chinese) //www.illord.com/CN/abstract/abstract9365.shtml
[2]	钱华明, 夏全喜, 阙兴涛, 等.基于Kalman滤波MEMS陀螺仪滤波算法[J].哈尔滨工程大学学报, 2010, 31(9):1217-1221. doi:10.3969/j.issn.1006-7043.2010.09.015 QIAN H M, XIA Q X, QU X T, et al.. Algorithm for a MEMS gyroscope based on Kalman filter[J]. Journal of Harbin Engineering University, 2010, 31(9):1217-1221.(in Chinese) doi:10.3969/j.issn.1006-7043.2010.09.015
[3]	林旻序, 汪永阳, 戴明, 等.线性加速度计在压电陀螺卡尔曼滤波技术中的应用[J].中国光学, 2011, 4(6):600-605. doi:10.3969/j.issn.2095-1531.2011.06.009 LIN M X, WANG Y Y, DAI M, et al.. Application of linear accelerometer to Kalman filter for piezoelectric gyro[J]. Chinese Optics, 2011, 4(6):600-605.(in Chinese) doi:10.3969/j.issn.2095-1531.2011.06.009
[4]	金靖, 张忠钢, 王峥, 等.基于RBF神经网络的数字闭环光纤陀螺温度误差补偿[J].光学精密工程, 2008, 16(2):235-240. http://d.old.wanfangdata.com.cn/Periodical/gxjmgc200802010 JIN J, ZHANG ZH G, WANG ZH, et al.. Temperature error compensation for digital closed-loop fiber optic gyroscope based on RBF neural network[J]. Opt. Precision Eng., 2008, 16(2):235-240.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/gxjmgc200802010
[5]	徐清雷, 邓正隆, 张传斌.光纤陀螺刻度因子的建模方法[J].光电工程, 2004, 31(12):4-7. doi:10.3969/j.issn.1003-501X.2004.12.002 XU Q L, DENG ZH L, ZHANG CH B. Modeling method for scale factor of fiber optic gyroscope[J]. Opto-Electronic Engineering, 2004, 31(12):4-7.(in Chinese) doi:10.3969/j.issn.1003-501X.2004.12.002
[6]	李颖, 陈兴林, 宋申民, 等.小波神经网络用于光纤陀螺漂移度误差辨识[J].光学精密工程, 2007, 15(5):773-778. doi:10.3321/j.issn:1004-924X.2007.05.025 LI Y, CHEN X L, SONG SH M, et al.. Application of wavelet neural network for identification of drifts errors in fiber optical gyroscope[J]. Opt. Precision Eng., 2007, 15(5):773-778.(in Chinese) doi:10.3321/j.issn:1004-924X.2007.05.025
[7]	NAVID GHAFFARZADEH. A new wavelet network based method to estimate the lighting-related risk of failure of power system apparatus[J]. Electrical Power and Energy System, 2016, 78:375-384. doi:10.1016/j.ijepes.2015.11.109
[8]	汤霞清, 程旭伟, 郭礼斌, 等.小波分析和灰色神经网络融合的光纤陀螺误差建模与补偿[J].中国 , 2012, 39(10):235-240. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK201204843711 TANG X Q, CHENG X W, GUO L B, et al.. Error modeling and compensation of fiber optic gyro scope based on wavelet analysis and grey neural network[J]. Chinese J. Lasers, 2012, 39(10):235-240.(in Chinese) http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK201204843711
[9]	ZHANG Q H, BENVENSITE A. Wavelet Networks[J]. IEEE Transactions on Neural Networks, 1992, 3(6):889-898. doi:10.1109/72.165591
[10]	丁玉美, 阔永红, 高新波.数字信号处理-时域离散随机信号处理[M].西安:西安电子科技大学出版社, 2002. DING Y M, KUO Y H, GAO X B. Digital Signal Processing-discrete Time Domain Random Signal Processing[M]. Xi'an:Xidian University Press, 2002.(in Chinese)
[11]	周哲, 庄良杰, 熊正南, 等.基于小波分析的陀螺漂移趋势项提取[J].中国惯性技术学报, 1999, 7(4):58-60, 69. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK199900835912 ZHOU ZH, ZHUANG L J, XIONG ZH N, et al.. Trend extraction of gyro's drift based on wavelet analysis[J]. Journal of Chinese Inertial Technology, 1999, 7(4):58-60, 69.(in Chinese) http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK199900835912
[12]	方琳, 申冲, 陈熙源.基于小波多尺度变换的光纤陀螺振动误差与补偿[J].传感技术学报, 2012, 25(7):902-906. doi:10.3969/j.issn.1004-1699.2012.07.007 FANG L, SHEN CH, CHEN X Y. Error analysis and compensation for fiber optic gyroscope under vibration based on wavelet multi-scale analysis[J]. Chinese Journal of Sensors and Actuators, 2012, 25(7):902-906.(in Chinese) doi:10.3969/j.issn.1004-1699.2012.07.007
[13]	徐丽娜, 邓正隆.陀螺漂移特性的小波分析[J].中国惯性技术学报, 2001, 9(3):57-60. doi:10.3969/j.issn.1005-6734.2001.03.012 XU L N, DENG ZH L. Wavelet analysis on gyro drift rate[J]. Journal of Chinese Inertial Technology, 2001, 9(3):57-60.(in Chinese) doi:10.3969/j.issn.1005-6734.2001.03.012
[14]	高宁.陀螺漂移信号的小波去噪及其误差模型的研究[D].天津: 天津大学, 2003. http://cdmd.cnki.com.cn/Article/CDMD-10056-2004075085.htm GAO N. Research on the wavelet denosing and error modeling of gyro drift signal[D]. Tianjin: Tianjin University, 2003.(in Chinese) http://cdmd.cnki.com.cn/Article/CDMD-10056-2004075085.htm
[15]	高鹏毅.BP神经网络分类器优化技术研究[D].武汉: 华中科技大学, 2012. http://www.wanfangdata.com.cn/details/detail.do?_type=degree&id=D298043 GAO P Y. Study on the optimization of backpropagation neural network classifier[D]. Wuhan: Huazhong University of Science and Technology, 2012.(in Chinese) http://www.wanfangdata.com.cn/details/detail.do?_type=degree&id=D298043