Development of an intelligent data analytics system for real-time condition monitoring of gas pipes

Objective: Gas pipes are laid underground where soil texture and temperature changes. The Fiber Bragg Grating sensor is kind of sensor which can get first-hand reliable data from complicated situation. Methods: Doing FBG sensor experiment (especially the data of the temperature and strain) to collec...

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Main Author: Wang, Zuyuan
Other Authors: So Ping Lam
Format: Theses and Dissertations
Language:English
Published: 2016
Subjects:
Online Access:http://hdl.handle.net/10356/66285
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-662852023-07-04T15:03:39Z Development of an intelligent data analytics system for real-time condition monitoring of gas pipes Wang, Zuyuan So Ping Lam School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Objective: Gas pipes are laid underground where soil texture and temperature changes. The Fiber Bragg Grating sensor is kind of sensor which can get first-hand reliable data from complicated situation. Methods: Doing FBG sensor experiment (especially the data of the temperature and strain) to collect FBG data of sensor network of FBG sensing system. And using Artificial Neural Network to analyze the data to get the relation between the measurand and the wavelength shift. Results: Verify the dual sensitivity of FBG sensors to temperature and strain. Extension guesses about the three-sensitivity of FBG sensors to temperature, strain and acoustic effect. Build up BP training neural network with good performance.Conclusion: FBG sensor is an ideal senor in monitoring of gas-pipe and it is in the development of the present age. Artificial Neural Network is a good approach to analyze the monitor data of FBG system. Master of Science (Power Engineering) 2016-03-23T03:31:25Z 2016-03-23T03:31:25Z 2016 Thesis http://hdl.handle.net/10356/66285 en 68 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Wang, Zuyuan
Development of an intelligent data analytics system for real-time condition monitoring of gas pipes
description Objective: Gas pipes are laid underground where soil texture and temperature changes. The Fiber Bragg Grating sensor is kind of sensor which can get first-hand reliable data from complicated situation. Methods: Doing FBG sensor experiment (especially the data of the temperature and strain) to collect FBG data of sensor network of FBG sensing system. And using Artificial Neural Network to analyze the data to get the relation between the measurand and the wavelength shift. Results: Verify the dual sensitivity of FBG sensors to temperature and strain. Extension guesses about the three-sensitivity of FBG sensors to temperature, strain and acoustic effect. Build up BP training neural network with good performance.Conclusion: FBG sensor is an ideal senor in monitoring of gas-pipe and it is in the development of the present age. Artificial Neural Network is a good approach to analyze the monitor data of FBG system.
author2 So Ping Lam
author_facet So Ping Lam
Wang, Zuyuan
format Theses and Dissertations
author Wang, Zuyuan
author_sort Wang, Zuyuan
title Development of an intelligent data analytics system for real-time condition monitoring of gas pipes
title_short Development of an intelligent data analytics system for real-time condition monitoring of gas pipes
title_full Development of an intelligent data analytics system for real-time condition monitoring of gas pipes
title_fullStr Development of an intelligent data analytics system for real-time condition monitoring of gas pipes
title_full_unstemmed Development of an intelligent data analytics system for real-time condition monitoring of gas pipes
title_sort development of an intelligent data analytics system for real-time condition monitoring of gas pipes
publishDate 2016
url http://hdl.handle.net/10356/66285
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