[1] Lei Cuihong, Zou Pinghua,. Application of neural networkin heating network leakage fault diagnosis [J]. Journal of Southeast University (English Edition), 2010, 26 (2): 173-176. [doi:10.3969/j.issn.1003-7985.2010.02.006]

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Application of neural networkin heating network leakage fault diagnosis()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

26

Issue:

2010 2

Page:

173-176

Research Field:

Civil Engineering

Publishing date:

2010-06-30

Info

Title:

Application of neural networkin heating network leakage fault diagnosis

Author(s):

Lei Cuihong;  Zou Pinghua

School of Municipal and Environmental Engineering, Harbin Institute of Technology, Harbin 150090, China

Keywords:

heating network;  fault;  diagnosis;  artificial neural network

PACS:

TU995

DOI:

10.3969/j.issn.1003-7985.2010.02.006

Abstract:

In order to investigate the leak detection strategy of a heating network, a space-based simulation mathematical model for the heating network under leakage conditions is built by graph theory.The pressure changes of all the nodes in the heating network are obtained from node leak and pipe leak conditions.Then, a leakage diagnosis system based on the back propagation(BP)neural network is established.This diagnosis system can predict the leakage pipe by collecting the pressure change data of the monitoring points, which can preliminary estimate the leak location.The usefulness of this system is proved by an example.The experimental results show that the forecast accuracy by this diagnosis system can reach 100%.

References:

[1] Zhou J H, Qu S L, Zhao H B.A model for pressure-dependent leakage in water distribution network[J].Water & Wastewater Engineering, 2005, 31(8):94-97.(in Chinese)
[2] Lei C H, Zou P H.Investigation and analysis for failure of heat-supply networks in Heilongjiang province[J].District Heating, 2008(5):15-20.(in Chinese)
[3] Belsito S, Lombardi P, Andreussi P, et al.Leak detection in liquefied gas pipelines by artificial neural networks [J].AICHE Journal, 1998, 44(12):2675-2688.
[4] Zhou Z J, Hu C H, Yang J B, et al.Online updating belief rule based system for pipeline leak detection under expert intervention [J].Expert Systems with Applications, 2009, 36(4):7700-7709.
[5] Li L H.The study and analysis of makeup water constant press and leakage condition on hot water pipe network[D].Harbin:School of Municipal and Environmental Engineering of Harbin Institute of Technology, 2008.(in Chinese)
[6] Ministry of Construction.CJJ34—2002 design code of district heating network[S].Beijing:China Architecture & Building Press, 2002.(in Chinese)
[7] Xu J M.Graph theory and application[M].Beijing:University of Science and Technology of China, 1998.(in Chinese)
[8] Хасилева В Я, Меленкова А П. Методы и алгоритмы расчёта тепловых сетей[M]. Масква: Энергия, 1978.
[9] Wang X X, Liu M J, Zou P H.Effect of failure scheduling scheme to reliability of complicated heat-supply network[C]//Proceedings of the 2nd International Conference on Built Environment and Public Health.Shantou, China, 2004:455-461.

Memo

Memo:

Biographies: Lei Cuihong(1981—), female, graduate;Zou Pinghua(corresponding author), female, professor, zph@hit.edu.cn.
Foundation item: The National Natural Science Foundation of China(No.50378029).
Citation: Lei Cuihong, Zou Pinghua.Application of neural network in heating network leakage fault diagnosis[J].Journal of Southeast University(English Edition), 2010, 26(2):173-176.

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