Sewer asset management tool: dealing with experts’ opinions

نویسندگان

  • C. Werey
  • F. Cherqui
  • M. Ibrahim
  • P. Le Gauffre
چکیده

Asset management requires the development of performance indicators (PIs) and decision procedures. Within the French RERAU methodology each rehabilitation criterion is assigned a grade out of four possible ones. This grade results from an aggregation of complementary PIs that use information derived from various sources: visual inspection, O&M data, network monitoring, etc. This paper focuses on the development of dysfunction indicators derived from visual inspection results (WP1 of the French INDIGAU program). Inspection reports provide sequences of observation (defect) codes. On this basis, three complementary procedures are proposed so as to assign a condition grade to the sewer segment: (a) expert rules identifying major defects (b) calculation of a single score and comparison to three thresholds and (c) rules based on the analysis of scores distribution along the segment. Calibrating procedure b) means defining parameters used in the calculation of a single score and defining three (crisp or fuzzy) thresholds. The calibration also requires experts’ judgments that will be used as references. A sample of 45 links has been studied by 8 experts, regarding 10 indicators. The results display a lot of conflicts between experts’ opinions. Three types of situation are defined: 1) no conflict, a consensus can be identified; 2) one expert disagrees with a majority, a consensus may be defined; 3) major conflicts between answers.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

CCTV inspection of sewer segments: calibration of performance indicators based on experts’ opinions

Asset management is an increasing concern for wastewater utilities and companies. Indicators are developed for supporting the definition of investigation and rehabilitation programs. These indicators are mostly based on visual inspections, which provide major information. However, difficulty remains in the translation of a visual inspection survey into dysfunction indicators. Condition grade of...

متن کامل

Sewer asset management: from visual inspection survey to dysfunction indicators

Asset management is an increasing concern for wastewater utilities and companies. Criteria are developed for supporting the definition of investigation and rehabilitation programs. Dysfunction indicators contribute to the calculation of criteria, using expert rules. These indicators are mostly based on visual inspections, which provide major information. However, difficulties remain in the tran...

متن کامل

Bayesian updating of a prediction model for sewer degradation

Sewer degradation is mainly a stochastic process. The future condition of sewers can be predicted with models based on condition states. In The Netherlands, the ‘SPIRIT’ model is being developed which combines expert opinion and visual inspections to predict sewer degradation. The statistical method implemented in this model is based on Bayesian statistics. The likelihood function of condition ...

متن کامل

Sewer rehabilitation criteria evaluated by fusion of fuzzy indicators

This paper deals with definition and assessment of decision criteria for sewer asset management. The work was prepared within a doctoral thesis (Ibrahim, 2008) and is part of a research program (INDIGAU, 2007-2010, www.indigau.fr) supported by the French National Research Agency (ANR). Three main ideas are exposed and illustrated in this paper. 1) Each rehabilitation criterion may be seen as th...

متن کامل

Evaluation of artificial intelligence tool performance and uncertainty for predicting sewer structural condition

a r t i c l e i n f o The implementation of a risk-informed asset management system by a wastewater infrastructure utility requires information regarding the probability and the consequences of component failures. This paper focuses on the former, evaluating the performance of artificial intelligence tools, namely artificial neural networks (ANNs) and support vector machines (SVMs), in predicti...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009