DocumentCode :
1576657
Title :
Multisensor data fusion for the simultaneous location and condition assessment of underground water pipelines
Author :
Abdel-Aleem, Mostafa ; Chibelushi, Claude C. ; Moniri, Mansour
Author_Institution :
Fac. of Comput., Eng., & Technol., Staffordshire Univ., Stafford, UK
fYear :
2011
Firstpage :
416
Lastpage :
421
Abstract :
Underground water and waste-water pipelines are essential arteries and veins of developed cities and countries. Being hidden under the surface of the earth, these pipelines are at risk of being abandoned or damaged by “blind” construction machines digging the ground to place new utilities or undertake road or other construction works. Moreover, due to the high costs associated with the inspection and condition assessment of water pipelines, which can require the pipeline to be drained, water utility companies are often reluctant to inspect them. With the introduction of new and increasingly strict rules and regulations imposed by governments, the safety, security, structural integrity, and sustainability in operation of water pipelines are becoming strategic factors for utility companies in their quest to offer low failure probabilities under controlled and optimized costs. This paper, therefore, reviews the state-of-the-art techniques and sensor technologies currently used for either the location or the condition assessment of underground pipelines. It also introduces a new multisensor tool, typically employing ground penetrating radar and electromagnetic induction sensors, intended to simultaneously locate and assess the condition of underground pipelines from above the ground, hence minimizing the costs and reducing the problems associated with in-line inspections. Moreover, a novel multisensor data fusion system and architecture will also be introduced to fuse the information acquired from the utilized sensors. This novel architecture is designed within a heuristic framework, typically employing an artificial neural network at its heart.
Keywords :
automatic optical inspection; condition monitoring; electromagnetic induction; failure analysis; ground penetrating radar; groundwater; mechanical engineering computing; neural nets; pipelines; sensor fusion; wastewater; arteries; artificial neural network; condition assessment; construction machines; earth surface; electromagnetic induction sensors; failure probabilities; ground digging; ground penetrating radar; inspection; location assessment; multisensor data fusion; multisensor tool; structural integrity; sustainability; underground water pipelines; waste-water pipelines; water utility companies; Acoustics; Electromagnetic interference; Feature extraction; Ground penetrating radar; Inspection; Pipelines; Robot sensing systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Networking, Sensing and Control (ICNSC), 2011 IEEE International Conference on
Conference_Location :
Delft
Print_ISBN :
978-1-4244-9570-2
Type :
conf
DOI :
10.1109/ICNSC.2011.5874937
Filename :
5874937
Link To Document :
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