检测预应力混凝土管道中的断丝:易于安装的分布式纤维声学传感方法

Lisbel Rueda-García, Daniel Tasquer-Val, Pedro Calderón-Bofías, Pedro A Calderón
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摘要

全球某些地区的干旱导致用水压力不断增加,这突出表明必须最大限度地减少水的损失,特别是在饮用水供应网络中。实现这一目标的方法之一是改进管道监测系统,以便及早发现管道可能出现的结构性坍塌。水管中广泛使用的一种管道是预应力混凝土管,其结构失效的主要原因是预应力钢丝断裂。本研究论文分析了易于安装的分布式声学传感(DAS)监测系统利用光纤识别和定位预应力混凝土管道断丝产生的声学信号的能力,以便及早发现可能的结构故障。为此,我们建造了一条大型实验管道(直径约 1 米,长 40 米),模拟钢丝断裂的情况。对几个变量进行了研究:信号的来源(以区分钢丝断裂和类似性质的事件)、事件在管道中的位置、背景噪声的存在、内部水压、不与混凝土粘合的预应力钢丝的长度以及管道中水的存在。结果表明,DAS 系统几乎可以检测到所有事件。此外,在信号测量的多个参数中,有两个参数(过零率和短时能量)可以精确地确定信号的来源和事件的位置。测量到的另一个参数,即信号的持续时间,可以区分事件是在管道空水还是满水时发生的。本文中的这些结果和其他结果为在水管监测中使用 DAS 系统提供了一个非常有前景的视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detecting wire breaks in prestressed concrete pipes: an easy-to-install distributed fibre acoustic sensing approach
The escalating water stress resulting from drought conditions in certain global regions underscores the imperative to minimize water losses, particularly within drinking water supply networks. One way to achieve this is by improving pipe monitoring systems to allow the early detection of possible structural collapse of the pipes. One type of pipe widely used in water mains is the prestressed concrete pipe, whose main cause of structural failure is the breakage of prestressing wires. This research paper analyses the ability of an easy-to-install distributed acoustic sensing (DAS) monitoring system using fibre optics to identify and locate the acoustic signal produced by the wire breaks in prestressed concrete pipes to make early detection of possible structural failures. For this purpose, a large experimental pipeline stretch was built (approximately 1 m in diameter and 40 m long) where wire breaks were simulated. Several variables were studied: the origin of the signal (to distinguish wire breaks from events of a similar nature), the location of the event in the pipe, the presence of background noise, the internal water pressure, the length of the prestressed wire not subject to bonding with the concrete and the presence of water in the pipe. The results showed that the DAS system could detect almost all events. In addition, two of the multiple parameters measured in the signals, the zero-crossing rate and the short-time energy, made it possible to precisely determine the signal’s origin and the event’s location. Another parameter measured, the duration of the signal in this case, made it possible to differentiate whether the events had occurred when the pipe was empty or full of water. These and other results in this paper present a highly promising perspective on using this DAS system in water main monitoring.
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