by Jaime Valls Miro*, Jeya Rajalingam**, Teresa Vidal-Calleja*, Freek de Bruijn*, Roger Wood**, Dammika Vitanage**, Nalika Ulapane*, Buddhi Wijerathna* and Daoblige Su*
* Centre for Autonomous Systems, University of Technology, Sydney
(E-mail: {Jaime.VallsMiro, Teresa.VidalCalleja, Freek.deBruijn}@uts.edu.au {Nalika,Buddhi,Su}@student.uts.edu.au )
** Sydney Water, 1 Smith Street, Parramatta, NSW 2150
(E-mail: {Jeya.Rajalingam Roger.Wood, Dammika.Vitanage} @sydneywater.com.au)
Conference:
Strategic Asset Management of Water and Wastewater Infrastructure: Leading Edge Strategic Asset Management (LESAM13)
Date of Conference:
9 – 12 September 2013
Conference Location :
Sydney, Australia
Abstract
The prediction of a pipe’s remaining life, especially for critical watermains, is important for developing effective renewals programs to manage pipe infrastructure and reducing the incidence of catastrophic failures, which impacts communities. A better understanding of the current condition and performance of buried water mains and sewer pressure mains is an important first step to help achieve improved understanding of remaining life. This has been identified by WSAA members as a high priority for research and collaboration. Despite this, one of the key factors impacting on condition assessment is the lack of data on large pipes. This is not only an issue for Sydney Water and other Australian water utilities, it is an international challenge. An experimental test-bed has been established as part of a larger collaborative research team of Australian and international researchers and a consortium of national and international agencies to improve the technological and financial management of buried water mains. To this end, the test-bed is being used for parallel research activities to deliver essential knowledge and guidance on the cause/effect of failure and for corrosion modelling. The test bed will address a number of knowledge gaps by generating data under controlled conditions. A verification method based on high-resolution geometric 3D laser scans of the exhumed and grit-blasted pipes together with algorithms to extract the pipe wall thickness out of the 3D geometric models, combined with lower-resolution ultrasonic measurements, is proposed to accurately determine the actual thickness of the pipes at a large scale. The set-up has allowed different condition assessment techniques to be applied to understand how their measurements relate to the pipe condition in terms of pitting, corrosion, structure etc., and to enhance their data interpretation with novel data mining techniques. The pipe used for the test-bed is a 1.5 km long section of 600mm cement lined cast iron pipe at Strathfield, Sydney, which was decommissioned due to poor condition. Examples from a number of large pipe segments from the test-bed will demonstrate the effectiveness of the proposed methodologies.
Keywords
Emerging trends, asset optimisation, intelligent networks