An Approach to Pipe Image Interpretation Based Condition Assessment for Automatic Pipe Inspection

Abstract

Condition assessment forms an important part of the asset management of buried pipelines. This is carried out through the use of inspection systems which usually consist of an image acquisition device attached to a mobile robotic platform. Complete or partial automation of image interpretation could increase the efficiency and objectivity of pipe inspection. A key component of an automatic pipe inspection system is the segmentation module. This paper describes an approach to automatic pipe inspection using pixel-based segmentation of colour images by support vector machine (SVM) coupled with morphological analysis of the principal component of the segmented image. The morphological analysis allows the principal component of the segmented image to be decomposed into the pipe flow lines region, the pipe joints, and adjoining defects. A simple approach to detecting pipe connections using fuzzy membership functions relating to defect size and location is also described.

A Qualitative Approach to Determine the Areas of Highest Inflow and Infiltration in Underground Infrastructure for Urban Area

“…ere are two types of approaches to assess possible location of I&I: (i) quantitative and (ii) qualitative. Quantitative method such as flow rate measurement, stable isotope method, and pollutant time-series method is used to assess the amount of the I&I in pipe network, while smoke testing, dye testing, distributed temperature sensing (DTS) method, and closed circuit television (CCTV) method are listed as the qualitative method and are used to locate/detect the I&I problems in the underground pipe network [11][12][13].…”