Pipeline defects and oil leakages pose an enormous challenge especially in the oil and gas industries, hence, the need for an effective and economical pipeline inspection system. This work focused on the development of a cost effective In-Line-Inspection tool called a smart pipe inspection gauge (PIG). A Test bed was designed and developed to simulate the impulses experienced by the PIG as it moved along the pipeline. The electronics and sensors embedded in the smart PIG were designed to detect vibrations as it moved along the pipe wall and allowed for the wireless transmission of data collected by the PIG system. The results obtained from the laboratory tests revealed dramatic changes in the vibrational intensity experienced by the smart PIG at various intervals. This validates the use of off-the-shelf sensing equipment with a low cost assembly to detect defects in pipelines.
<p>Robotic units used in pipe inspection are expensive to purchase and repair. Many companies do not offer long term support for the repair and maintenance of their robotic units. Consequently Associated Environmental Services Limited (AES), a Wellington based pipe inspection company approached Victoria University to facilitate the repair of a non-functional system. As a result this Masters project aims to design and implement a reliable pipe inspection system for use by AES. This thesis outlines and discusses the circuit boards and software designed for such a robotic unit. A reliable graphical user interface and internal circuitry for the robot was designed and is also presented.</p>
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.
<p>Robotic units used in pipe inspection are expensive to purchase and repair. Many companies do not offer long term support for the repair and maintenance of their robotic units. Consequently Associated Environmental Services Limited (AES), a Wellington based pipe inspection company approached Victoria University to facilitate the repair of a non-functional system. As a result this Masters project aims to design and implement a reliable pipe inspection system for use by AES. This thesis outlines and discusses the circuit boards and software designed for such a robotic unit. A reliable graphical user interface and internal circuitry for the robot was designed and is also presented.</p>
Pipe inspection system by guide wave using a long distance waveguide