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Reseach Article

A New Image Model for Predicting Cracks in Sewer Pipes based on Time

by Iraky Khalifa, Amal Elsayed Aboutabl, Gamal S Abdel Aziz Barakat
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 87 - Number 9
Year of Publication: 2014
Authors: Iraky Khalifa, Amal Elsayed Aboutabl, Gamal S Abdel Aziz Barakat
10.5120/15238-3779

Iraky Khalifa, Amal Elsayed Aboutabl, Gamal S Abdel Aziz Barakat . A New Image Model for Predicting Cracks in Sewer Pipes based on Time. International Journal of Computer Applications. 87, 9 ( February 2014), 25-32. DOI=10.5120/15238-3779

@article{ 10.5120/15238-3779,
author = { Iraky Khalifa, Amal Elsayed Aboutabl, Gamal S Abdel Aziz Barakat },
title = { A New Image Model for Predicting Cracks in Sewer Pipes based on Time },
journal = { International Journal of Computer Applications },
issue_date = { February 2014 },
volume = { 87 },
number = { 9 },
month = { February },
year = { 2014 },
issn = { 0975-8887 },
pages = { 25-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume87/number9/15238-3779/ },
doi = { 10.5120/15238-3779 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:06:27.226472+05:30
%A Iraky Khalifa
%A Amal Elsayed Aboutabl
%A Gamal S Abdel Aziz Barakat
%T A New Image Model for Predicting Cracks in Sewer Pipes based on Time
%J International Journal of Computer Applications
%@ 0975-8887
%V 87
%N 9
%P 25-32
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Sewer overflows may cause communities to be vulnerable to various health problems and other monetary losses. This puts a lot of burden on responsible to minimize end user complaints. Therefore, crack prediction would be helpful to facilitate decision makers to control sewer overflow problems and prioritize inspection and rehabilitation needs . The accurate prediction of current underground sewer pipe cracks must be done before any pipe crashing with enough period of time to enable rehabilitation and replacement intervals, appropriate remedial methods and preventing sewer pipes crashing. Unfortunately, traditional technologies and models approaches have been limited to predict the development of sewer pipe cracks. In this paper, we address the problem of crack prediction of such cracks. This paper provides a proposed model which predict crack and cracks developments in any period of time that may occur in weak areas of a network of pipes. . We evaluate our results by comparing them with those obtained by many other models. The accuracy percentage of this model exceeds 90% and outperforms other approaches.

References
  1. Ruwanpura J, Ariaratnam, S, and El-Assaly, A, (2004), "Prediction Models for Sewer Infrastructure Utilizing Rule-Based Simulation", Journal of Civil Engineering and Environmental Systems, volume 21, No 3, Page 169-185
  2. Holding company for water and waste water, Japanese Agency for International Cooperation ,'General master plan for Cairo & El Gisa governorates' ,2013 http://www. cairofuturevision. gov. eg/Uploads/IssueUpload/45/%D8%A7%D9%84%D9%85%D9%8A%D8%A7%D9%87%20%D9%88%D8%A7%D9%84%D8%B5%D8%B1%D9%81%20%D8%A7%D9%84%D8%B5%D8%AD%D9%8A. pdf
  3. Ministry of Finance :PPP Central Unit, retrieved on July 23, 2011, http://www. almasryalyoum. com/News/Index?tag=159433.
  4. Fenner, R. A. (2000). Approaches to sewer maintenance: a review. Urban Water, 2(4), 343–356.
  5. Moselhi, O and Shehab-Eldeen, T, (2000), "Classification of Defects in Sewer Pipes using Neural Networks", ASCE Journal of Infrastructures System, Volume 06, Number 03, September, 2000
  6. Chae, M and Abraham, M, (2001), "Neuro-Fuzzy Approaches for Sanitary Sewer Pipeline Condition Assessment", ASCE Journal of Computing in Civil Engineering, Volume 15, Number 1, January, 2011
  7. Hasegawa, K, Wada, Y & Miura, H, (1999), "New Assessment System for Premeditated Management and Maintenance of Sewer Pipe Networks", Proceedings of 8th International Conference on Urban Storm Drainage, Page 586-593, Sydney, Australia
  8. Ariaratnam, S, El-Assaly, A & Yang, Y, (2001), "Assessment of Infrastructure Inspection Needs using Logistic Models", ASCE Journal of Infrastructure Systems, Volume 7, No 4, December 2001
  9. McDonald, S & Zhao, J, (2001), "Condition Assessment and Rehabilitation of Large Sewers", Proceedings of International Conference on Underground Infrastructure Research, page 361-369, Waterloo, Canada
  10. Baur, R & Herz, R, (2002), "Selective Inspection Planning with Ageing Forecast for Sewer Types", International Water Association (IWA) Journal of Water Science and Technology, Volume 46, No 6-7, page 389-396
  11. Yan J & Vairavamoorthy, K, (2003), "Fuzzy Approach for Pipe Condition Assessment", Proceedings of the American Society of Civil Engineers (ASCE) International Pipeline Conference, USA
  12. Ruwanpura J, Ariaratnam, S, and El-Assaly, A, (2004), "Prediction Models for Sewer Infrastructure Utilizing Rule-Based Simulation", Journal of Civil Engineering and Environmental Systems, volume 21, No 3, Page 169-185
  13. Najafi M & Kulandaivel G, (2005), "Pipeline Condition Prediction Using Neural Network Models", Proceedings of the American Society of Civil Engineers (ASCE) International Pipeline Conference, USA
  14. Kompetenzzentrum Wasser Berlin, " REVIEW OF SEWER DETERIORATION MODELS Cicerostraße 24, 10709 Berlin, Germany,2013
  15. PIKS Scientific Inside, WILLIAM K. PRATT ,DIGITAL IMAGE PROCESSING, Los Altos, California, A John Wiley & Sons, Inc,2007
  16. Sinha, S. K. , & Fieguth, P. W. (2006). Segmentation of buried concrete pipe images. Automation in Construction, 15(1), 47–57.
  17. Dingus, M. , Haven, J. , and Russell, A. _2002_. Nondestructive, noninvasive assessment of underground pipelines, AWWA Research Foundation, Denver
  18. Yan, H. (1996). Unified formulation of a class of image thresholding techniques. Pattern Recognition, 29(12), 2025–2032
  19. Umbaugh Scot E, Computer Vision and Image Processing, Prentice Hall, NJ, 1998, ISBN 0-13-264599-8
  20. Gonzalez and Woods Prentice Hall ,Errata and Clarifications Digital Image Processing 3rd Edition © 2008 September 10, 2008 CORRECTIONS
Index Terms

Computer Science
Information Sciences

Keywords

Pipe crashing Sewer pipes rehabilitation Crack prediction cracks developments sewer pipe inspection sewage rehabilitation