AI for optical sensor

Fiber Bragg gratings (FBG) sensors are widely used to measure different parameters including temperature, pressure, electrical-field, and strain due to its unique characteristics and the ability to detect directional changes. The main objective of this project is focused on getting the separated wav...

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Main Author: Zuo, MengTing
Other Authors: Wei Lei
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/145540
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1455402023-07-07T17:51:09Z AI for optical sensor Zuo, MengTing Wei Lei School of Electrical and Electronic Engineering wei.lei@ntu.edu.sg Engineering::Electrical and electronic engineering Fiber Bragg gratings (FBG) sensors are widely used to measure different parameters including temperature, pressure, electrical-field, and strain due to its unique characteristics and the ability to detect directional changes. The main objective of this project is focused on getting the separated waveforms of each FBG sensor in the overlapped condition as the Spectrum Analyzer can only get the combined waveform in a multiplexing FBG sensor network. The machine learning method Least Square approach and the deep learning method Convolutional Neural Network (CNN) is applied to train the detection model and the central Bragg wavelength of each FBG sensor can be identified from the overlapped spectrum. The result shows that it effectively improves the average testing time and root mean square (RMS) by using the CNN model. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-12-28T03:55:00Z 2020-12-28T03:55:00Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/145540 en P3024-191 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
spellingShingle Engineering::Electrical and electronic engineering
Zuo, MengTing
AI for optical sensor
description Fiber Bragg gratings (FBG) sensors are widely used to measure different parameters including temperature, pressure, electrical-field, and strain due to its unique characteristics and the ability to detect directional changes. The main objective of this project is focused on getting the separated waveforms of each FBG sensor in the overlapped condition as the Spectrum Analyzer can only get the combined waveform in a multiplexing FBG sensor network. The machine learning method Least Square approach and the deep learning method Convolutional Neural Network (CNN) is applied to train the detection model and the central Bragg wavelength of each FBG sensor can be identified from the overlapped spectrum. The result shows that it effectively improves the average testing time and root mean square (RMS) by using the CNN model.
author2 Wei Lei
author_facet Wei Lei
Zuo, MengTing
format Final Year Project
author Zuo, MengTing
author_sort Zuo, MengTing
title AI for optical sensor
title_short AI for optical sensor
title_full AI for optical sensor
title_fullStr AI for optical sensor
title_full_unstemmed AI for optical sensor
title_sort ai for optical sensor
publisher Nanyang Technological University
publishDate 2020
url https://hdl.handle.net/10356/145540
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