ABSTRACT

Certain sewer deterioration modeling approaches, represent the condition of a pipe as the sum of individual defect severities, leading to the loss of spatial information about defects in the pipe. This paper proposes a hybrid framework for incorporating spatial information of defects into the analysis of sewer pipe condition. The first component of the framework is called Defect Cluster Analysis (DCA) and it seeks to identify defect clusters (i.e. areas with multiple defects in proximity) and quantify their severity. The second component of the framework is called Defect Co-Occurrence Mining and it attempts to identify groups of defects, which occur simultaneously in pipes. The framework was evaluated on data from 7193 inspections of sewers in the US. Validation of the results by subject matter experts indicates that the proposed framework enables a fine-grained analysis of pipe condition and could be instrumental in rehabilitation decision-making.

摘要

某些下水道恶化建模方法将管道的状况表示为单个缺陷严重程度的总和，导致有关管道缺陷的空间信息丢失。本文提出了一种混合框架，用于将缺陷的空间信息纳入下水道管道状况分析。该框架的第一个组成部分称为缺陷聚​​类分析 (DCA)，它旨在识别缺陷聚类（即邻近有多个缺陷的区域）并量化其严重性。该框架的第二个组成部分称为缺陷共现挖掘，它试图识别同时发生在管道中的缺陷组。该框架是根据美国 7193 次下水道检查的数据进行评估的。