Trackside Optical Fibre Acoustic Sensing (TOFAS)

分布式光纤声学和动态应变传感在安全、能源、环境和运输行业中具有重要的应用。此类应用的示例包括入侵者检测、石油/天然气管道和核电反应堆系统中的泄漏检测、监测由水力压裂引起的冲击波以及跟踪和收听移动的火车。全分布式光纤传感的主要优点是可以在光纤沿着的每个点检测被测对象。通过这种方式，大量的离散传感器可以简单地由单个光纤代替。基本操作是基于沿光学传感纤维发送光脉冲并检测由待测量参数引起的后向散射光的变化。瑞利后向散射光对声压引起的光纤应变敏感。由于瑞利反向散射迹线上的每个点对应于感测纤维的一个部分，因此可以通过以规则的间隔将光脉冲发射到感测纤维中并监测反向散射迹线中的变化来映射沿着感测纤维沿着的声波场。利用我们已经开发的适当的光学设置和数字信号处理，可以沿着传感光纤的整个长度在空间上分辨声致应变的频率、相位和幅度。脉冲的重复率确定重复测量的频率，并因此确定声信号的检测带宽。本质上，单根光纤可以执行与多个（~10000个）麦克风相同的功能，但成本和安装复杂性大大降低。 拟议的研究是开发一种分布式光纤声学和动态应变传感器技术，其能力远远超过目前已经实现的能力，以提高其对一些关键应用的适用性，特别是对轨道运输行业的适用性，以监测轨道和列车的健康状况。改进将源于光学配置的修改和数据处理和处理的新硬件和软件的引入。虽然未来铁路旅行的预测增长将不可避免地要求铁路基础设施的额外增长，但该行业必须继续努力提高现有列车服务的效率，同时保持最高的安全标准。该建议涉及发展最先进的分布式光纤声学感测，并且目标是实现i）准确确定列车的位置和速度，这将允许优化列车密度; ii）检测异常声音，提供潜在问题的早期指示，例如入侵者、电缆被盗、松动和嘎嘎作响的部件等，促进及时的维护或预防措施，以尽量减少中断; andiii）轨道旁机械的状态，如平交道口电机和远程发电机，应被监控，以确保安全和有效的运行。实现这些目标将有助于提供安全，高效可靠的铁路运输，最大限度地提高现有基础设施的能力。

Distributed fibre optic acoustic and dynamic strain sensing has important applications in the security, energy, environment and transport industries. Examples of such applications include intruder detection, leak detection in oil/gas pipelines and nuclear power reactor systems, monitoring shock waves caused by fracking, and tracking and listening to moving trains. The key advantage of all distributed fibre optic sensing is that a measurand can be detected at every point along the fibre. In this way a large number of discrete sensors can be simply replaced by a single optical fibre. The basic operation is based on sending pulses of light down the optical sensing fibre and detecting the changes in the backscattered light, caused by the parameters to be measured. The Rayleigh backscattered light is sensitive to the sound pressure induced strain on the fibre. Since each point on the Rayleigh backscattered trace corresponds to one section of the sensing fibre, the acoustic wave field along the sensing fibre can be mapped by launching optical pulses into the sensing fibre at a regular intervals and monitoring the changes in the backscattered traces. With the appropriate optical setup and the digital signal processing that we have developed, the acoustically induced strain in terms of its frequency, phase and amplitude can be spatially resolved along the entire length of the sensing fibre. The repetition rate of the pulses determines the frequency at which the measurement is repeated and hence the detection bandwidth of the acoustic signal. In essence, the single optical fibre can perform the same function as multiple (~10000) microphones but with much reduced cost and complexity of installation. The proposed research is to develop a distributed fibre optic acoustic and dynamic strain sensor technology with capabilities far in excess of what has currently been achieved in order to improve its applicability to a number of key applications, but in particular to the rail transport industry for monitoring the health of track and trains. The improvement will stem from modification of the optical configuration and introduction of new hardware and software for data handling and processing. Whilst future predicted growth in rail travel will inevitably require additional growth in rail infrastructure, it is imperative that the industry continues to strive to improve the efficiency of existing train services, whilst maintaining the highest of safety standards. This proposal is concerned with developing the state of the art distributed fibre optic acoustic sensing and with the goal of enablingi) Accurate determination of the location and speed of trains which will allow train density to be optimised; ii) Abnormal sounds to be detected, providing early indication of potential problems such as intruders, cable theft, loose and rattling components, etc, facilitating timely maintenance or preventative action to minimize disruptions; andiii) The condition of track-side machines such as level crossing motors and remote generators to be monitored, ensuring safe and efficient operation.Achieving these goals will help to provide safe, efficient and reliable rail transport that maximises the capacity of the existing infrastructure.