Disruptive Innovations Propel the Growth and Transformation of Distributed Fiber Optic Sensing
Machine learning and quantitative DAS driving advancements in distributed fiber optic sensing
Research Overview
Fiber optic sensing solutions utilize the light medium as the physical source to detect variations in temperature, acoustics, strain, and vibrational parameters. Fiber optic sensing uses an optical fiber cable as the sensor device to create a continuous point of sensing along the fiber cable. This method of sensing is known as distributed fiber optic sensing. Distributed temperature sensing uses the Raman scattering method, distributed strain sensing utilizes the Brillouin scattering methodology, while distributed acoustics/vibration sensing uses the Rayleigh scattering method. Since these readings are unaffected by the fiber's optical loss, they may be used to reliably measure temperature and strain over distances of hundreds of kilometers.
Distributed fiber optic sensing solution applications can be classified into optical network sensing and infrastructure monitoring sensing. In optical network sensing, the fiber optic sensing protects, inspects, and monitors the fiber optic networks, whereas, for infrastructure monitoring sensing, the fiber optic sensing detects and locates leakages, ground movement, mechanical deformation, and traces hot spots.
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