Published October 31, 2022 | Version 1.0
Project deliverable Open

D7.1. Report on methodologies used to identify in-pipe defects

  • 1. University of Sheffield


This report is Deliverable 7.1 “Report on the methodologies used to identify in-pipe defects” of the Co- UDlabs project, which is funded under the European Union’s Horizon 2020 research and innovation programme via Grant Agreement No 101008626. The Deliverable is an output from Work Package 7, “Asset Deterioration”. The University of Sheffield (UFSD). UFSD is the author of this deliverable.

The report describes current defect inspection and classification methodologies and provides a review of their effectiveness. The report argues that historically there has been a strong linkage between the development of international and national defect classification systems and sewer inspection approaches. A state-of-the-art review of commonly used inspection technologies is provided. The potential for newer emerging inspection technologies is also described and discussed. These new approaches are being developed to (i) reduce cost so as to allow the wider use of sewer inspection and (ii) gather more physically relevant information about in-sewer defects so that more physically based pipe deterioration models can be developed, and (iii) to provide inspection data with less uncertainty. If improvements in inspection approaches could be achieved it would allow water utilities to better focus investment for sewer rehabilitation and renewal and also more rapidly identify operational issues that cause system failures such as flooding and the release of untreated wastewater via sewer overflows.

Different sources of information were considered: (i) a search of academic and governmental agency sources – peer reviewed outputs; (ii) search of documentation from other sources that had not been reviewed; and (iii) information from commercial sources, mainly companies providing in-pipe inspection services.

This review has shown that CCTV based inspection currently still dominates sewer inspection, despite the recognition that there is significant uncertainty and cost associated with human based analysis of CCTV images. Different technologies have been developed and deployed to identify defects that are difficult to identify using visual means and that also allow for larger proportions of sewer networks to be inspected. The review has also shown the benefits of multi-sensor approaches when identifying and characterising sewer pipe defects.

Emerging inspection technologies can be organised into 3 groups: new sensing technologies, autonomous, multi-sensor inspection platform and adaptation of AI based approaches to better identify and characterise in-pipe defects from CCTV images. It is also clear that new inspection techniques are being developed so that more physically relevant inspection data can be collected to inform the development and use of more physically based pipe/asset structural deterioration models.



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Co-UDlabs – Building Collaborative Urban Drainage research labs communities 101008626
European Commission