Optical Time Domain Reflectometry
Optical Time Domain Reflectometry (OTDR) is a technique used to characterize and monitor fiber optic cables by analyzing backscattered light signals, primarily aiming for fault detection and localization. Current research heavily emphasizes improving the accuracy and robustness of OTDR analysis, particularly in noisy environments, using advanced signal processing techniques such as convolutional neural networks (CNNs) and long short-term memory (LSTM) networks to identify and classify reflective events. These advancements are crucial for enhancing the reliability and efficiency of fiber optic networks, impacting both telecommunications infrastructure maintenance and various sensing applications, including subsurface material characterization and shape sensing of flexible robots.
Papers
Convolutional Neural Networks for Reflective Event Detection and Characterization in Fiber Optical Links Given Noisy OTDR Signals
Khouloud Abdelli, Helmut Griesser, Stephan Pachnicke
Reflective Fiber Faults Detection and Characterization Using Long-Short-Term Memory
Khouloud Abdelli, Helmut Griesser, Peter Ehrle, Carsten Tropschug, Stephan Pachnicke
Optical Fiber Fault Detection and Localization in a Noisy OTDR Trace Based on Denoising Convolutional Autoencoder and Bidirectional Long Short-Term Memory
Khouloud Abdelli, Helmut Griesser, Carsten Tropschug, Stephan Pachnicke