The consistency of visual sewer inspection data

Abstract : In common with most infrastructure systems, sewers are often inspected visually. Currently, the results from these inspections inform decisions for significant investments regarding sewer rehabilitation or replacement. In practice, the quality of the data and its analysis are not questioned although psychological research indicates that, as a consequence of the use of subjective analysis of the collected images, errors are inevitable. This article assesses the quality of the analysis of visual sewer inspection data by analysing data reproducibility; three types of capabilities to subjectively assess data are distinguished: the recognition of defects, the description of defects according to a prescribed coding system and the interpretation of sewer inspection reports. The introduced uncertainty is studied using three types of data: inspector examination results of sewer inspection courses, data gathered in day-to-day practice, and the results of repetitive interpretation of the inspection results. After a thorough analysis of the data it can be concluded that for all cases visual sewer inspection data proved poorly reproducible. For the recognition of defects, it was found that the probability of a false positive is in the order of a few percent, the probability of a false negative is in the order of 25%.
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https://hal.archives-ouvertes.fr/hal-00663958
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Submitted on : Friday, July 27, 2012 - 7:00:02 AM
Last modification on : Thursday, February 7, 2019 - 2:45:00 PM
Long-term archiving on : Sunday, October 28, 2012 - 2:45:23 AM

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J. Dirksen, F.H.L.R. Clemens, H. Korving, Frédéric Cherqui, Pascal Le Gauffre, et al.. The consistency of visual sewer inspection data. Structure and Infrastructure Engineering, Taylor & Francis (Routledge): STM, Behavioural Science and Public Health Titles, 2011, pp.1-15. ⟨10.1080/15732479.2010.541265⟩. ⟨hal-00663958⟩

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