Muñoz Felipe, Urricelqui Javier, Soto Marcelo A, Jimenez-Rodriguez Marco
Uptech Sensing SL, 31192 Mutilva Baja, Spain.
Department of Electronic Engineering, Universidad Técnica Federico Santa María, Valparaíso 2390123, Chile.
Sensors (Basel). 2023 Jul 22;23(14):6599. doi: 10.3390/s23146599.
Distributed acoustic sensors (DAS) utilize optical fibers to monitor vibrations across thousands of independent locations. However, the measured acoustic waveforms experience significant variations along the sensing fiber. These differences primarily arise from changes in coupling between the fiber and its surrounding medium as well as acoustic interferences. Here, a correlation-based method is proposed to automatically find the spatial locations of DAS where temporal waveforms are repeatable. Signal repeatability is directly associated with spatial monitoring locations with both good coupling and low acoustic interference. The DAS interrogator employed is connected to an over 30-year-old optical fiber installed alongside a railway track. Thus, the optical fiber exhibits large coupling changes and different installation types along its path. The results indicate that spatial monitoring locations with good temporal waveform repeatability can be automatically discriminated using the proposed method. The correlation between the temporal waveforms acquired at locations selected by the algorithm proved to be very high considering measurements taken for three days, the first two on consecutive days and the third one a month after the first measurement.
分布式声学传感器(DAS)利用光纤来监测数千个独立位置的振动。然而,所测量的声学波形在传感光纤上会经历显著变化。这些差异主要源于光纤与其周围介质之间耦合的变化以及声学干扰。在此,提出了一种基于相关性的方法,以自动找到DAS中时间波形可重复的空间位置。信号可重复性与具有良好耦合和低声学干扰的空间监测位置直接相关。所使用的DAS询问器连接到一条与铁轨并行安装了30多年的光纤上。因此,该光纤在其路径上呈现出较大的耦合变化和不同的安装类型。结果表明,使用所提出的方法可以自动区分具有良好时间波形可重复性的空间监测位置。考虑到连续两天进行的前两次测量以及第一次测量一个月后进行的第三次测量,算法选择的位置所采集的时间波形之间的相关性被证明非常高。