By Topic

A Comparison of Analysis Methods of Pipe Failure Characteristics Based on Maintenance Records of Water Distribution System

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Wang Yi ; Sch. of Environ. Sci. & Technol., Tianjin Univ., Tianjin, China ; Tian Yimei

The characteristic data applied for establishing predicting models of pipe failure in water distribution system (WDS) should be examined and screened in the first place. The effects of different way of data processing based on a series on maintenance records are compared, which includes a classification method by Bayesian theorem, a hypothesis testing by analysis of variance and an association rule of data mining. The result shows the Bayesian theorem is applicable for nonparametric analysis, and can give classification limits intuitively. But this method may neglect the relations between different variates and effects. It's proper to adopt this method when there are few pipe characteristics available. The analysis of variance (ANOVA) is able to point out the interaction of variates and deal with both parametric and nonparametric tests. The association rule can provide correlations between different attributes, but may also bring excessive and nonsense results and it appears that more detailed records are required to make use of this method. It is suggested that the data should be carefully examined in appropriate method before applied to a model.

Published in:

Management and Service Science (MASS), 2010 International Conference on

Date of Conference:

24-26 Aug. 2010