Prediction Of The Economic Residual Life Of Water Pipes

Since rehabilitation and replacement of water pipes usually require immense budget and time, efficient program or methodology, such as evaluating the economic residual life of pipes, is expected to extremely useful in the maintenance of water distribution system.This paper introduced many statistical models of pipe failure prediction and the EPR (Evolutionary Polynomial Regression) model was developed based on the basic information of water pipes and historic records of pipe breaks in the study area. The EPR model reported here was aggregated, so it cannot be used directly for assessing burst rate at the individual pipe level. But EPR model contained the aggregated variable (pipe length) and the time factor (pipe age), the burst rate forecasting equation of individual pipe was established. The optimal replacement time of a pipe was obtained using the equivalence relationship between burst rate and threshold break rate. The survival analysis based on Cox regression (the proportional hazards model) for pipes were made, which the survival times were defined as the economic optimal replacement times of pipes. Then the survival function was obtained, and the distribution of the survival times of the pipes was considered to have a Weibull distribution. The survival function was proved to obeyed the proportional hazards assumption by analyzing the standardized score residuals. The model for predicting economic residual life of water pipes was constructed based on the definition of economic residual life which calculated as the remaining time until a pipe reached the median survival time from the current time of the analysis. Then the model was test by the deviance residuals. Finally, the main factors affecting the economic life of water pipes were analyzed, the conclusion was that pipe diameter and pipe material were protective factors, pipe length was risk factor in this paper.It showed that the methodology developed in this paper may help utilities identify important factors related to the economic life, and obtain the model for predicting economic residual life of water pipes which was verified to be of better fitting accuracy.