Automatic Strain Detection in a Brillouin Optical Time Domain Sensor Using Principal Component скачать в хорошем качестве

Automatic Strain Detection in a Brillouin Optical Time Domain Sensor Using Principal Component

This video was recorded in 2014 and posted in 2021 Sponsored by IEEE Sensors Council (https://ieee-sensors.org/) Title: Automatic Strain Detection in a Brillouin Optical Time Domain Sensor Using Principal Component Analysis and Artificial Neural Networks Author: Ruben Ruiz Lombera, Jesus Mirapeix Serrano, José Miguel López-Higuera Affiliation: Universidad de Cantabria, Spain Abstract: In this paper the performance of a distributed optical fiber sensor solution based on the Stimulated Brillouin Scattering (SBS) for dynamic strain detection is analyzed. The proposed scheme is based on the employment of Principal Component Analysis (PCA) to help in the detection and localization of the dynamic events employing the signal offered by a Brillouin Optical Time Domain Analysis (BOTDA) sensor system. Results will demonstrate that the selection of the proposed processing scheme might prove useful, allowing identification of these events using the first PCA components. IEEE Sensors Conferences (https://ieee-sensors.org/conferences/) IEEE Sensors Journal (https://ieee-sensors.org/sensors-jour...) IEEE Sensors Letters (https://ieee-sensors.org/sensors-lett...) IEEE Internet of Things Journal (https://ieee-iotj.org/) IEEE SENSORS conference proceedings (https://ieeexplore.ieee.org/xpl/conho...)