Pipe network leak detection: comparison between statistical and machine learning techniques-Reference-Cited by-同舟云学术

Pipe network leak detection: comparison between statistical and machine learning techniques

Published:2018-11-26 Issue:10 Volume:15 Page:953-960
ISSN:1573-062X
Container-title:Urban Water Journal
language:en
Short-container-title:Urban Water Journal

Author:

van der Walt J. C.¹,Heyns P. S.¹,Wilke D. N.¹

Affiliation:

1. Center of Asset Integrity Management, Department of Mechanical and Aeronautical Engineering, University of Pretoria, Pretoria, South Africa

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/1573062X.2019.1597375

Reference19 articles.

1. Application of nodal pressure measurements in leak detection

2. Process Safety Progress

3. Optimal sensor placement for leak location in water distribution networks using genetic algorithms

4. De Silva, D., J. Mashford, and S. Burn. 2011. Computer aided leak location and sizing in pipe networks. Technical Report 17. Urban Water Security Research Alliance. April.

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