Performance Enhancement in Distributed Fiber Sensing by Noise Reduction

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As a key enabling factor for Industry 4.0 and smart city, the Internet of things (IoT) is forecasted to have a market over $ 7,000 billion and connect nearly 30 billion devices by 2020. Sensors account for a large number of the connected devices and act as a fundamental pillar of IoT. Optical fiber sensing has been a driving force for the IoT, mainly due to the unique properties of the optical fiber, i.e. being small size, chemically inert, and immune to electromagnetic interference. Furthermore, distributed fiber sensors (DFSs) offer economic solutions due to their low-cost per sensing points. The performance of DFS is defined by the signal-to-noise ratio (SNR) of the sensing system. Current research focuses on signal enhancement to improve the SNR. The reported methods often need costly and power-consuming equipment. Furthermore, the progress of the SNR improvement seems to be insufficient for the fast development and deployment of IoT. The limited sensing distance of current DFSs (usually < 100 km) without inline amplification, is far from enough, compared with the 1,222 km pipeline length under the Baltic Sea between Germany and Russia (North Stream 2 project) or the 500,000 km gas network just in Germany. To answer to the need for excellent distributed sensing performance particularly over long distances, the proposal ambitions to significantly enhance the SNR from the other direction—by reducing noise. By a fundamental understanding of the origin of different noise sources in distributed sensing, the main objective of the proposal is to investigate different methods to reduce the noise and to enhance the performance of the sensors. If the aim is achieved, the SNR can be enhanced by at least four orders of magnitude in a more cost-effective and energy efficient way, doubling the performance of the state-of-the-art sensors.