Optical fiber perimeter vibration signal recognition based on SVD and MPSO-SVM

被引：6
|
作者：
Ma Y. [1 ]
Wang Q. [1 ]
Wang R. [1 ]
Xiong X. [1 ]
机构：
[1] Tianjin Key Laboratory for Advanced Signal Processing, Civil Aviation University of China, Tianjin
来源：
| 1652年 / Chinese Institute of Electronics卷 / 42期
关键词：
Fiber optics; Particle swarm optimization (PSO); Signal recognition; Singular value decomposition (SVD); Support vector machine (SVM);
D O I：
10.3969/j.issn.1001-506X.2020.08.02
中图分类号：
学科分类号：
摘要：
A recognition method based on singular value decomposition (SVD) and modified particle swarm optimization support vector machine (MPSO-SVM) is proposed for the optical fiber vibration signals with noise interference, low accuracy and long recognition time. Firstly, SVD is used to denoise the signal, and the rank order of signal reconstruction is determined according to the single-side minimum principle of second-order difference spectrum of singular value sequence. Secondly, the vibration signal features are extracted and a set of feature vectors is constructed by means of serial feature fusion (SFF). Finally, MPSO-SVM is used for classification and recognition to improve the accuracy and efficiency of the algorithm. The measured signal is used for verification. The results show that the signal to noise ratio is significantly improved, and the average recognition rate is 5% higher than that of PSO-SVM. This method performs better than the traditional neural network recognition method and has the practical application value. © 2020, Editorial Office of Systems Engineering and Electronics. All right reserved.
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收藏
页码：1652 / 1661
页数：9
相关论文
共 26 条
  • [1] PEI L, WENG S J, WU L Y, Et al., Progress in optical fiber laser sensing system, Chinese Journal of Lasers, 43, 7, pp. 7-13, (2016)
  • [2] YE Q, PAN Z Q, WANG Z Y, Et al., Research and application progress of phase sensitive optical time domain reflectometer, Chinese Journal of Lasers, 44, 6, pp. 7-20, (2017)
  • [3] RAO Y J., Research progress of long-distance distributed optical fiber sensing technology, Acta Physica Sinica, 66, 7, pp. 158-176, (2017)
  • [4] ALLWOOD G, WILD G, HINCKLEY S., Optical fiber sensors in physical intrusion detection systems: a review, IEEE Sensors Journal, 16, 14, pp. 5497-5509, (2016)
  • [5] MAHMOUD S S, KATISFOLIS J., Real-timedistributed fiber optic sensor for security systems: performance, event classification and nuisance mitigation, Photonic Sensors, 2, 3, pp. 225-236, (2012)
  • [6] QADEER M A, ISLAM J, RIZVI S, Et al., Design and implementation of a fiber optic perimeter intrusion detection system, Proc.of the International Bhurban Conference on Applied Sciences & Technology, pp. 48-50, (2016)
  • [7] XIN L, JIN B Q, BAI Q, Et al., Distributed fiber-optic sensors for vibration detection, Sensors, 16, 8, (2016)
  • [8] JIANG J F, AN J C, LIU K, Et al., A fast positioning algorithm for the asymmetric dual Mach-Zehnder interferometric infrared fiber vibration sensor, Infrared Physics & Technology, 85, pp. 359-363, (2017)
  • [9] MA C Y, LIU T G, LIU K, Et al., Long range distributed fiber vibration sensor using an asymmetric dual Mach-Zehnder interferometers, Journal of Lightwave Technology, 34, 9, pp. 2235-2239, (2016)
  • [10] TAO W, LIU T G, LIU K, Et al., An EMD-based filtering algorithm for the fiber-optic SPR sensor[J], IEEE Photonics Journal, 8, 3, pp. 1-8, (2016)
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