Dealing with uncertainty in sewer condition assessment: Impact on inspection programs

被引:13
|
作者
Roghani, Bardia [1 ]
Cherqui, Frederic [2 ]
Ahmadi, Mehdi [3 ]
Le Gauffre, Pascal [2 ]
Tabesh, Massoud [4 ]
机构
[1] Univ Tehran, Coll Engn, Sch Civil Engn, Tehran, Iran
[2] INSA Lyon, DEEP, F-69621 Villeurbanne, France
[3] SINTEF, Oslo, Norway
[4] Univ Tehran, Coll Engn, Sch Civil Engn, Ctr Excellence Engn & Management Civil Infrastruc, Tehran, Iran
关键词
Asset management; Uncertainty; Sewer inspection program; Deterioration model; Condition assessment; VISUAL INSPECTION; DECISION-SUPPORT; DETERIORATION; PERFORMANCE;
D O I
10.1016/j.autcon.2019.03.012
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Sewer condition prediction is a fundamental element of proactive maintenance programs. The prediction relies mostly on the assessed condition of inspected segments, generally based on CCTV reports. However, several sources of uncertainty affect the condition assessment and may lead to inefficient maintenance. The present article focuses on three main questions. 1. What is the impact of uncertainty in assessed condition on the prediction model? 2. Considering uncertainties in the assessed condition, is it necessary to collect data on the characteristics of many segments, or are a small number of influential variables enough to build the condition prediction model? 3. Is it better to overestimate (false positive) or underestimate (false negative) the deterioration of a segment? These questions were evaluated on a semi-virtual asset stock and the results confirm that uncertainties affect the inspection efficiency negatively. Results also show that errors leading to the overestimation of the deterioration have less negative impact. The study suggests that data from a small number of influential segments is adequate to inform the prediction model.
引用
下载
收藏
页码:117 / 126
页数:10
相关论文
共 50 条
  • [1] Automated defect detection for sewer pipeline inspection and condition assessment
    Guo, W.
    Soibelman, L.
    Garrett, J. H., Jr.
    AUTOMATION IN CONSTRUCTION, 2009, 18 (05) : 587 - 596
  • [2] Quantitative Impact Assessment of Sewer Condition on Health Risk
    van Bijnen, Marco
    Korving, Hans
    Langeveld, Jeroen
    Clemens, Francois
    WATER, 2018, 10 (03)
  • [3] Comparison of core sampling and visual inspection for assessment of concrete sewer pipe condition
    Stanic, N.
    de Haan, C.
    Tirion, M.
    Langeveld, J. G.
    Clemens, F. H. L. R.
    WATER SCIENCE AND TECHNOLOGY, 2013, 67 (11) : 2458 - 2466
  • [4] Impact of dimension uncertainty and model calibration on sewer system assessment
    Korving, H
    Clemens, F
    WATER SCIENCE AND TECHNOLOGY, 2005, 52 (05) : 35 - 42
  • [5] Vision-Based Defect Inspection and Condition Assessment for Sewer Pipes: A Comprehensive Survey
    Li, Yanfen
    Wang, Hanxiang
    Dang, L. Minh
    Song, Hyoung-Kyu
    Moon, Hyeonjoon
    SENSORS, 2022, 22 (07)
  • [6] Condition assessment of sewer systems
    Iseley, T
    Abraham, DM
    Gokhale, S
    TRENCHLESS PIPELINE PROJECTS: PRACTICAL APPLICATIONS, 1997, : 43 - 51
  • [7] Probabilistic condition assessment of reinforced concrete sanitary sewer pipelines using LiDAR inspection data
    Ebrahimi, Moein
    Jalali, Himan Hojat
    Sabatino, Samantha
    AUTOMATION IN CONSTRUCTION, 2023, 150
  • [8] Dealing with uncertainty in risk assessment
    Murphy, BL
    HUMAN AND ECOLOGICAL RISK ASSESSMENT, 1998, 4 (03): : 685 - 699
  • [9] Risk assessment: Dealing with uncertainty
    Purchase, IFH
    TOXICOLOGY, 2004, 202 (1-2) : 47 - 48
  • [10] Risk assessment: dealing with uncertainty
    Davies, Gordon R. W.
    PSYCHIATRIC BULLETIN, 2012, 36 (02): : 78 - 79