• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

用于光纤分布式声学传感中噪声抑制的自适应时间匹配滤波

Adaptive Temporal Matched Filtering for Noise Suppression in Fiber Optic Distributed Acoustic Sensing.

作者信息

Ölçer İbrahim, Öncü Ahmet

机构信息

TÜBİTAK BİLGEM, Barış Mah., Dr. Zeki Acar Cad., Gebze 41470, Kocaeli, Turkey.

Electrical & Electronics Engineering Department, Boğaziçi University, Bebek, İstanbul 34342, Turkey.

出版信息

Sensors (Basel). 2017 Jun 5;17(6):1288. doi: 10.3390/s17061288.

DOI:10.3390/s17061288
PMID:28587240
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5492096/
Abstract

Distributed vibration sensing based on phase-sensitive optical time domain reflectometry ( ϕ -OTDR) is being widely used in several applications. However, one of the main challenges in coherent detection-based ϕ -OTDR systems is the fading noise, which impacts the detection performance. In addition, typical signal averaging and differentiating techniques are not suitable for detecting high frequency events. This paper presents a new approach for reducing the effect of fading noise in fiber optic distributed acoustic vibration sensing systems without any impact on the frequency response of the detection system. The method is based on temporal adaptive processing of ϕ -OTDR signals. The fundamental theory underlying the algorithm, which is based on signal-to-noise ratio (SNR) maximization, is presented, and the efficacy of our algorithm is demonstrated with laboratory experiments and field tests. With the proposed digital processing technique, the results show that more than 10 dB of SNR values can be achieved without any reduction in the system bandwidth and without using additional optical amplifier stages in the hardware. We believe that our proposed adaptive processing approach can be effectively used to develop fiber optic-based distributed acoustic vibration sensing systems.

摘要

基于相敏光时域反射仪（ϕ -OTDR）的分布式振动传感正广泛应用于多个领域。然而，基于相干检测的ϕ -OTDR系统面临的主要挑战之一是衰落噪声，它会影响检测性能。此外，典型的信号平均和微分技术不适用于检测高频事件。本文提出了一种新方法，可降低光纤分布式声学振动传感系统中衰落噪声的影响，且不会对检测系统的频率响应产生任何影响。该方法基于ϕ -OTDR信号的时间自适应处理。介绍了基于信噪比（SNR）最大化的算法基本理论，并通过实验室实验和现场测试证明了我们算法的有效性。采用所提出的数字处理技术，结果表明，无需在硬件中使用额外的光放大器级，也无需降低系统带宽，即可实现超过10 dB的SNR值。我们相信，我们提出的自适应处理方法可有效用于开发基于光纤的分布式声学振动传感系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/d10ec41ff9ab/sensors-17-01288-g023.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/d5363d119e3e/sensors-17-01288-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/7e616f6d7072/sensors-17-01288-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/6950770d7149/sensors-17-01288-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/67b245fc9e9b/sensors-17-01288-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/d3cc6eca98d4/sensors-17-01288-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/7df804c36f4e/sensors-17-01288-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/a6f9a9b1da01/sensors-17-01288-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/92d4e5b53027/sensors-17-01288-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/1f0f807cec6e/sensors-17-01288-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/af65eaaaf326/sensors-17-01288-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/ab3d0de48186/sensors-17-01288-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/e7bbe036e823/sensors-17-01288-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/1acf9729198e/sensors-17-01288-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/e3f0959805b2/sensors-17-01288-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/0acdc8a33b10/sensors-17-01288-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/8714857a41f8/sensors-17-01288-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/b95f6a8588df/sensors-17-01288-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/ce354f00a57c/sensors-17-01288-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/8dfa3263b6ce/sensors-17-01288-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/8cd5af9b334d/sensors-17-01288-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/56e4a125b6f1/sensors-17-01288-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/2f6cc8578773/sensors-17-01288-g022.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/d10ec41ff9ab/sensors-17-01288-g023.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/d5363d119e3e/sensors-17-01288-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/7e616f6d7072/sensors-17-01288-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/6950770d7149/sensors-17-01288-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/67b245fc9e9b/sensors-17-01288-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/d3cc6eca98d4/sensors-17-01288-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/7df804c36f4e/sensors-17-01288-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/a6f9a9b1da01/sensors-17-01288-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/92d4e5b53027/sensors-17-01288-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/1f0f807cec6e/sensors-17-01288-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/af65eaaaf326/sensors-17-01288-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/ab3d0de48186/sensors-17-01288-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/e7bbe036e823/sensors-17-01288-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/1acf9729198e/sensors-17-01288-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/e3f0959805b2/sensors-17-01288-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/0acdc8a33b10/sensors-17-01288-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/8714857a41f8/sensors-17-01288-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/b95f6a8588df/sensors-17-01288-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/ce354f00a57c/sensors-17-01288-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/8dfa3263b6ce/sensors-17-01288-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/8cd5af9b334d/sensors-17-01288-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/56e4a125b6f1/sensors-17-01288-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/2f6cc8578773/sensors-17-01288-g022.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8470/5492096/d10ec41ff9ab/sensors-17-01288-g023.jpg

相似文献

1
Adaptive Temporal Matched Filtering for Noise Suppression in Fiber Optic Distributed Acoustic Sensing.用于光纤分布式声学传感中噪声抑制的自适应时间匹配滤波
Sensors (Basel). 2017 Jun 5;17(6):1288. doi: 10.3390/s17061288.
2
A Review of Hybrid Fiber-Optic Distributed Simultaneous Vibration and Temperature Sensing Technology and Its Geophysical Applications.混合光纤分布式同步振动与温度传感技术及其地球物理应用综述
Sensors (Basel). 2017 Nov 1;17(11):2511. doi: 10.3390/s17112511.
3
Undersampling for fiber distributed acoustic sensing based on coherent phase-OTDR.基于相干相位光时域反射仪的光纤分布式声学传感欠采样
Opt Lett. 2019 Feb 15;44(4):911-914. doi: 10.1364/OL.44.000911.
4
Optical Fiber Vibration Sensor Using Least Mean Square Error Algorithm.基于最小均方误差算法的光纤振动传感器
Sensors (Basel). 2020 Apr 2;20(7):2000. doi: 10.3390/s20072000.
5
Enhanced Distributed Fiber Optic Vibration Sensing and Simultaneous Temperature Gradient Sensing Using Traditional C-OTDR and Structured Fiber with Scattering Dots.采用传统 C-OTDR 和带散射点结构光纤实现增强分布式光纤振动传感和同时温度梯度传感。
Sensors (Basel). 2019 Sep 23;19(19):4114. doi: 10.3390/s19194114.
6
Fiber-optic distributed acoustic sensor based on a chirped pulse and a non-matched filter.基于啁啾脉冲和非匹配滤波器的光纤分布式声学传感器。
Opt Express. 2019 Sep 30;27(20):29415-29424. doi: 10.1364/OE.27.029415.
7
Localization and Discrimination of the Perturbation Signals in Fiber Distributed Acoustic Sensing Systems Using Spatial Average Kurtosis.利用空间平均峰度对光纤分布式声学传感系统中的扰动信号进行定位和甄别。
Sensors (Basel). 2018 Aug 28;18(9):2839. doi: 10.3390/s18092839.
8
Signal-to-Noise Ratio Enhancement Based on Empirical Mode Decomposition in Phase-Sensitive Optical Time Domain Reflectometry Systems.基于经验模态分解的相敏光时域反射仪系统信噪比增强
Sensors (Basel). 2017 Aug 14;17(8):1870. doi: 10.3390/s17081870.
9
Hybrid B-OTDR/Φ-OTDR for multi-parameter measurement from a single end of fiber.用于从光纤单端进行多参数测量的混合B-OTDR/Φ-OTDR。
Opt Express. 2022 Aug 1;30(16):29117-29127. doi: 10.1364/OE.463127.
10
Recent Progress in the Performance Enhancement of Phase-Sensitive OTDR Vibration Sensing Systems.近年来，相位敏感光时域反射计（OTDR）振动传感系统性能提升的研究进展。
Sensors (Basel). 2019 Apr 10;19(7):1709. doi: 10.3390/s19071709.

引用本文的文献

1
Quasi-Distributed Fiber Sensor-Based Approach for Pipeline Health Monitoring: Generating and Analyzing Physics-Based Simulation Datasets for Classification.基于准分布式光纤传感器的管道健康监测方法：用于分类的基于物理的仿真数据集的生成和分析。
Sensors (Basel). 2023 Jun 7;23(12):5410. doi: 10.3390/s23125410.
2
A Space-Division Multiplexing Method for Fading Noise Suppression in the Φ-OTDR System.一种用于Φ-OTDR系统中衰落噪声抑制的空分复用方法。
Sensors (Basel). 2021 Mar 1;21(5):1694. doi: 10.3390/s21051694.
3
Comparative Study on Noise Reduction Effect of Fiber Optic Hydrophone Based on LMS and NLMS Algorithm.

本文引用的文献

1
Distributed Fiber-Optic Sensors for Vibration Detection.用于振动检测的分布式光纤传感器
Sensors (Basel). 2016 Jul 26;16(8):1164. doi: 10.3390/s16081164.
2
Structural health monitoring of civil infrastructure using optical fiber sensing technology: a comprehensive review.基于光纤传感技术的民用基础设施结构健康监测：全面综述
ScientificWorldJournal. 2014;2014:652329. doi: 10.1155/2014/652329. Epub 2014 Jul 14.
3
Recent progress in distributed fiber optic sensors.分布式光纤传感器的最新进展。
基于 LMS 和 NLMS 算法的光纤水听器降噪效果的对比研究。
Sensors (Basel). 2020 Jan 5;20(1):301. doi: 10.3390/s20010301.
4
Ensemble Learning with Stochastic Configuration Network for Noisy Optical Fiber Vibration Signal Recognition.基于随机配置网络的集成学习用于噪声光纤振动信号识别
Sensors (Basel). 2019 Jul 26;19(15):3293. doi: 10.3390/s19153293.
5
Performance Optimization for Phase-Sensitive OTDR Sensing System Based on Multi-Spatial Resolution Analysis.基于多空间分辨率分析的相敏光时域反射（OTDR）传感系统的性能优化。
Sensors (Basel). 2018 Dec 27;19(1):83. doi: 10.3390/s19010083.
6
Localization and Discrimination of the Perturbation Signals in Fiber Distributed Acoustic Sensing Systems Using Spatial Average Kurtosis.利用空间平均峰度对光纤分布式声学传感系统中的扰动信号进行定位和甄别。
Sensors (Basel). 2018 Aug 28;18(9):2839. doi: 10.3390/s18092839.
Sensors (Basel). 2012;12(7):8601-39. doi: 10.3390/s120708601. Epub 2012 Jun 26.
4
Field test of a distributed fiber-optic intrusion sensor system for long perimeters.用于长距离周界的分布式光纤入侵传感器系统的现场测试
Appl Opt. 2007 Apr 10;46(11):1968-71. doi: 10.1364/ao.46.001968.
5
Polarization discrimination in a phase-sensitive optical time-domain reflectometer intrusion-sensor system.相敏光时域反射仪入侵传感器系统中的偏振鉴别
Opt Lett. 2005 Dec 15;30(24):3284-6. doi: 10.1364/ol.30.003284.