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基于新型分布式光纤智能织物与光频域反射计(OFDR)的结构健康监测:以人行桥为例。

Structural Health Monitoring Using a New Type of Distributed Fiber Optic Smart Textiles in Combination with Optical Frequency Domain Reflectometry (OFDR): Taking a Pedestrian Bridge as Case Study.

机构信息

Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, MA 01854, USA.

出版信息

Sensors (Basel). 2023 Feb 1;23(3):1591. doi: 10.3390/s23031591.

Abstract

Distributed fiber optic sensors (DFOS) have become a new method for continuously monitoring infrastructure status. However, the fiber's fragility and the installation's complexity are some of the main drawbacks of this monitoring approach. This paper aims to overcome this limitation by embedding a fiber optic sensor into a textile for a faster and easier installation process. To demonstrate its feasibility, the smart textile was installed on a pedestrian bridge at the University of Massachusetts Lowell. In addition, dynamic strain data were collected for two different years (2021 and 2022) using Optical Frequency Domain Reflectometry (OFDR) and compared, to determine the variability of the data after one year of installation. We determined that no significant change was observed in the response pattern, and the difference between the amplitude of both datasets was 14% (one person jumping on the bridge) and 43% (two people jumping) at the first frequency band. This result shows the proposed system's functionality after one year of installation, as well as its potential use for traffic monitoring.

摘要

分布式光纤传感器(DFOS)已成为一种连续监测基础设施状态的新方法。然而,光纤的脆弱性和安装的复杂性是这种监测方法的一些主要缺点。本文旨在通过将光纤传感器嵌入纺织品中,来克服这一限制,从而实现更快、更简单的安装过程。为了证明其可行性,该智能纺织品被安装在马萨诸塞大学洛厄尔分校的一座人行桥上。此外,还使用光频域反射计(OFDR)收集了两年(2021 年和 2022 年)的动态应变数据,并进行了比较,以确定安装一年后数据的可变性。我们确定,在响应模式上没有观察到明显的变化,并且在第一个频带中,两个数据集之间的幅度差异为 14%(一个人在桥上跳跃)和 43%(两个人在桥上跳跃)。这一结果表明,该系统在安装一年后仍具有功能性,并且可能用于交通监测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cb3/9921771/0f85f7ff6c00/sensors-23-01591-g001.jpg

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