我国大型基础设施的建设规模已多年位居世界之首,分布式光纤传感技术(DOFS)作为大型基础设施健康状态实时监测最有潜力的技术,近年来得到了迅速发展。针对DOFS在技术和应用的突破上面临的挑战,在介绍DOFS各技术基本工作原理、发展历史、现状以及典型应用原理和方案等的基础上,对其工作新机理、系统设计方案、研究发展方向等进行了阐述和讨论。 

分布式光纤传感技术研究和应用的现状及未来

In this paper, a novel distributed optical fiber temperature sensor based on Raman anti-Stokes scattering light is proposed and experimentally demonstrated. The Raman anti-Stokes scattering light is sensitive to temperature parameters that are detected by the fiber under test conditions (FUT), and this allowed the temperature demodulation algorithm to be obtained through the relationship between the temperature and the power of the back-scattered Raman anti-Stokes light. In addition, we propose a new temperature calibration method to ensure accurate temperature measurement, which is greatly affected by the stability of a pulse laser. The experimental system is constructed with an optical fiber length of approximately 3.5 km. The proposed system obtains a 24 dB dynamic range with a pulse width of 20 ns and temperature testing ranges of 30.0 °C to 80.0 °C. The results demonstrate that the maximum temperature deviation range is −1.5 °C to +1.6 °C and the root mean square (RMS) error of the whole temperature range is 0.3 °C, which means it has the potential for practical engineering applications. More importantly, it avoids the walk-off effect that must be corrected in commonly used temperature demodulation schemes adopting both Raman Stokes light and anti-Stokes light. It also saves a signal channel, which is more suitable for the integration of hybrid distributed optical fiber sensing systems for multi-parameter monitoring.

A Novel Distributed Optical Fiber Temperature Sensor Based on Raman anti-Stokes Scattering Light

The conventional distributed fiber optic positioning system (DFOPS) employing a single pulse working has a mutually constrained relationship between resolution and measurement distance, thereby imposing severe limitations on the advancement of DFOPS development. To solve this problem, we propose a strain and vibration event positioning system by employing correlated positioning techniques, pulse coding techniques, a broadband light source, and arrays of weakly reflective fiber gratings. To further improve the positioning accuracy of the system, the chip subdivision method and correlation prediction method are used to achieve centimeter-level localization accuracy in this study. In addition to correlation localization, we also propose a superposition signal decomposition model to achieve vibration event localization. Finally, to determine the most appropriate coding method for the system, a comparative analysis is performed to evaluate different coding methods in terms of coding gain, transmission time, and decoding complexity. We hope that the system and methods presented in this paper can serve as a valuable reference in the field of distributed fiber optic sensing with grating arrays for vibration detection. 

High-Precision distributed fiber optic vibration positioning system with grating array

拉曼分布式光纤温度传感(RDTS)系统因其长期稳定性成为最早商业化的光纤传感产品之一,尤其在油气勘探传感的巨大市场中占据半壁江山。数十年来其技术发展日新月异,本文简述了RDTS的基本原理,着重分析了近年来领域内优化和提升RDTS的方法,分别从系统结构、部件优化、解调方式和智能信号处理等方面系统性地总结了最新研究进展,并通过走访调研了RDTS的全球市场概况及其在各工程领域的典型应用,旨在为分布式温度传感技术的同仁提供有益的参考。 

拉曼分布式光纤温度传感：技术发展与应用综述

Raman distributed temperature sensing (RDTS) systems monitor temperature variation regions (TVRs) that are less than the shortest fiber length required to accurately measure the temperature, and using conventional temperature demodulation methods will result in inaccurate temperature measurements. The most cost-effective solution is to construct the relation curve between the temperature and the characteristics of the temperature rise curve for different TVR lengths, but this increases the workload of temperature calibration, and the unstable linearity in the relation curves constructed under the measured TVR lengths will bring errors to the temperature demodulation. To solve this problem, this article proposes to use the Raman intensity of each sampling point in the temperature rise curve to construct a temperature rise curve with a spatial resolution of the length and use the maximum intensity of the reconstructed temperature rise curve to calibrate with the temperature at one time to realize the temperature sensing of the TVR with a length of centimeter scale. The experimental results well demonstrate that the proposed method can accurately realize the temperature sensing of TVR with a length of 30 cm with a temperature error of ±0.73 °C. The proposed method allows accurate monitoring of anomalous temperatures of TVRs of arbitrary length, such as fires, through a high spatial resolution determined by the sampling spacing without changing the internal structure of a conventional RDTS system.

High Spatial Resolution Temperature S ensing Determined by Sampli ng Spacing with RDTS Syste m

A submetric spatial resolution Raman optical time-domain reflectometry (ROTDR) temperature sensor assisted by the Wiener deconvolution postprocessing algorithm has been proposed and experimentally demonstrated. Without modifying the typical configuration of the ROTDR sensor and the adopted pump pulse width, the Wiener demodulation algorithm is able to recover temperature perturbations of a smaller spatial scale by deconvoluting the acquired Stokes and anti-Stokes signals. Numerical simulations have been conducted to analyze the spatial resolution achieved by the algorithm. Assisted by the algorithm, a typical ROTDR sensor adopting pump pulses of 20 ns width can realize the distributed temperature sensing with a spatial resolution of 0.5 m and temperature accuracy of 1.99 °C over a 2.1-km sensing fiber.

/pdf/submetric-spatial-resolution-rotdr-temperature-sensor-1i2qle6h.pdf

Submetric Spatial Resolution ROTDR Temperature Sensor Assisted by Wiener Deconvolution

Popular Tasks used by Researchers

How can I help with your research?

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

We encountered an error while loading the panel. Please try refreshing the page.

Something went wrong

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

Anyone with the link can view this chat. You can switch it back to private anytime.

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Meiting Zhou

Author Tools

Chat about Author

Papers

Submetric Spatial Resolution ROTDR Temperature Sensor Assisted by Wiener Deconvolution