DocumentCode :
3218769
Title :
Countermeasures of fast location of pipe bursts in Guangzhou based on neural network technology
Author :
Shen, Wang ; Yu, Tu ; Zhihong, Wang ; Yuli, Chen ; Wen, Sun
Author_Institution :
Sch. of Civil & Transp. Eng., Guangdong Univ. of Technol., Guangzhou, China
fYear :
2011
fDate :
22-24 April 2011
Firstpage :
5824
Lastpage :
5828
Abstract :
Recently, with the wide use of on-line monitoring technique in urban water supply networks, pipe network crack diagnosis based on pressure and (or) flow analysis has become a major development direction home and abroad. Meanwhile, in order to solve complex pipe network problems, neural network technology has gained more and more public attention. This paper, in accordance with the actual situations in Guangzhou, through the analysis of the, function, advantages and the results of relevant research of the neural network structure, elaborates the feasibility of its application in the development of the fast locating technology of burst pipes, providing the technical implementation measures for demonstration project.
Keywords :
cracks; monitoring; neural nets; pipes; water supply; Guangzhou; flow analysis; neural network technology; online monitoring; pipe bursts; pipe network crack diagnosis; urban water supply networks; Accidents; Analytical models; Artificial neural networks; Biological neural networks; Monitoring; Pipelines; Water pollution; fast location of pipe bursts; neural network technology; water supply network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electric Technology and Civil Engineering (ICETCE), 2011 International Conference on
Conference_Location :
Lushan
Print_ISBN :
978-1-4577-0289-1
Type :
conf
DOI :
10.1109/ICETCE.2011.5774400
Filename :
5774400
Link To Document :
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