Localized Pipeline Encroachment Detector System Using Sensor Network

Detection of encroachment on pipeline right-of-way is important for pipeline safety. An effective system can provide on-time warning while reducing the probability of false alarms. There are a number of industry and academic developments to tackle this problem. This thesis is the first to study the...

Full description

Bibliographic Details
Main Author: Ou, Xiaoxi 1986-
Other Authors: Lu, Mi
Format: Others
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-10170
http://hdl.handle.net/1969.1/150952
id ndltd-tamu.edu-oai-repository.tamu.edu-1969.1-150952
record_format oai_dc
spelling ndltd-tamu.edu-oai-repository.tamu.edu-1969.1-1509522013-12-18T03:55:04ZLocalized Pipeline Encroachment Detector System Using Sensor NetworkOu, Xiaoxi 1986-Wireless Sensor NetworkPipeline SafetyDetection of encroachment on pipeline right-of-way is important for pipeline safety. An effective system can provide on-time warning while reducing the probability of false alarms. There are a number of industry and academic developments to tackle this problem. This thesis is the first to study the use of a wireless sensor network for pipeline right-of-way encroachment detection. In the proposed method, each sensor node in the network is responsible for detecting and transmitting vibration signals caused by encroachment activities to a base station (computer center). The base station monitors and analyzes the signals. If an encroachment activity is detected, the base station will send a warning signal. We describe such a platform with hardware configuration and software controls, and the results demonstrate that the platform is able to report our preliminary experiments in detecting digging activities by a tiller in the natural and automotive noise.Lu, MiJi, Jim XChan, AndrewWilliams, Tiffani2013-12-16T19:55:28Z2013-12-16T19:55:28Z2011-082011-08-08August 20112013-12-16T19:55:29ZThesistextapplication/pdfhttp://hdl.handle.net/1969.1/ETD-TAMU-2011-08-10170http://hdl.handle.net/1969.1/150952
collection NDLTD
format Others
sources NDLTD
topic Wireless Sensor Network
Pipeline Safety
spellingShingle Wireless Sensor Network
Pipeline Safety
Ou, Xiaoxi 1986-
Localized Pipeline Encroachment Detector System Using Sensor Network
description Detection of encroachment on pipeline right-of-way is important for pipeline safety. An effective system can provide on-time warning while reducing the probability of false alarms. There are a number of industry and academic developments to tackle this problem. This thesis is the first to study the use of a wireless sensor network for pipeline right-of-way encroachment detection. In the proposed method, each sensor node in the network is responsible for detecting and transmitting vibration signals caused by encroachment activities to a base station (computer center). The base station monitors and analyzes the signals. If an encroachment activity is detected, the base station will send a warning signal. We describe such a platform with hardware configuration and software controls, and the results demonstrate that the platform is able to report our preliminary experiments in detecting digging activities by a tiller in the natural and automotive noise.
author2 Lu, Mi
author_facet Lu, Mi
Ou, Xiaoxi 1986-
author Ou, Xiaoxi 1986-
author_sort Ou, Xiaoxi 1986-
title Localized Pipeline Encroachment Detector System Using Sensor Network
title_short Localized Pipeline Encroachment Detector System Using Sensor Network
title_full Localized Pipeline Encroachment Detector System Using Sensor Network
title_fullStr Localized Pipeline Encroachment Detector System Using Sensor Network
title_full_unstemmed Localized Pipeline Encroachment Detector System Using Sensor Network
title_sort localized pipeline encroachment detector system using sensor network
publishDate 2013
url http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-10170
http://hdl.handle.net/1969.1/150952
work_keys_str_mv AT ouxiaoxi1986 localizedpipelineencroachmentdetectorsystemusingsensornetwork
_version_ 1716620434528534528