Author: Salihu, Comfort
Title: CCTV-based deterioration patterns of sewer pipelines
Advisors: Zayed, Tarek (BRE)
Degree: M.Sc.
Year: 2021
Subject: Sewerage -- Maintenance and repair
Sewerage -- Inspection
Hong Kong Polytechnic University -- Dissertations
Department: Department of Building and Real Estate
Pages: x, 87 pages : color illustrations
Language: English
Abstract: The average age of sewers in the Tsim Sha ui area of Hong Kong is 45years. This indicates that the pipes are already approaching their useful service life. If keen attention is not given to the sewers it could lead to sewer failure. A smart and sustainable drainage system is strongly dependent on the status quo of sewer pipelines existing within the infrastructure of cities' networks. Sewer deterioration is still a challenge in many cities and Hong Kong is not left out. Many factors are responsible for the deterioration of sewers. Although these factors are well known, the level of impact each of them has on the deterioration process has not been clearly defined. Over time, sewer deterioration models have been developed in different cities of the world to help predict sewer conditions. But the drainage service department in Hong Kong do not have a predictive deterioration model that helps in predicting the time a pipe might likely fail given certain conditions. Therefore, the objective of this research is to do an extensive review of current deterioration models, to identify and study the critical factors and defects that affect sewer pipeline deterioration and impact on Hong Kong environment and to develop a CCTV based deterioration model for the pipes. In achieving these objectives, a scientometric and systematic literature review was done to give an in-depth view of existing works. Furthermore, meta-analysis was performed in other to ascertain the level of impact each of these factors have on the deterioration process. Also, based on the CCTV inspection data collected from DSD, a Weibull deterioration model for vitrified clay pipes and concrete pipes and multilinear regression model were developed. Data for the scientometric review, systematic review and meta-analysis were sourced from literatures. In developing the multilinear regression deterioration models, CCTV inspection data was collected from the Drainage service department. The factors considered in the model were age, length, diameter and ICG. Also, the deterioration curve developed using Weibull analysis was based on the pipe age and structural grading ICG. Unsupervised learning of the data was conducted using K-means clustering, the result of the clustering was then compared with the actual data which gave an average similarity percentage of 89%. The result of the unsupervised learning was further used to carry out a multilinear regression analysis. The results of meta-analysis indicate that the most significant factors impacting sewer pipeline deterioration include operational defect, pipe shape, pipe material, waste type, structural defect, and hydraulic conditions. The result of the Weibull deterioration curve indicates that the useful service life for concrete and vitrified clay pipes are 79years and 48years respectively. The regression models developed shows that the R2 value for vitrified clay sewer pipes, concrete sewer pipes, and ductile iron sewer pipes were 71.18%, 71.47% and 81.51 percent respectively while that of concrete storm water pipes is 73.69%. Regression equation was developed for the different pipe types and materials. The model validation shows a standard deviation and mean of the actual ICG and the Predicted ICG of the various pipe materials to be closely linked. The sensitivity analysis result for the model indicates that pipe diameter has a significant influence on sewer pipe deterioration but have little impacts on stormwater pipes. The findings obtained from this research will lead to the adoption of intelligent policies by the concerned decision-makers, and also help the drainage service department in Hong Kong identify critical pipes and take necessary precautionary measures.
Rights: All rights reserved
Access: restricted access

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