Synergistic methods for pipeline inspection

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The safe and economical transport of oil and natural gas is an important part of Canada's infrastructure. With aging pipelines, the need for constant maintenance and repair is important not only to ensure economic stability but also to prevent catastrophic environmental damage resulting from pipeline rupture.  Thus, pipelines must be regularly inspected for potentially hazardous defects.  The preferred method of inspection is magnetic flux leakage (MFL) imaging. This is normally accomplished using an inspection device referred to as a "pig", which is inserted into the pipe. These devices collect a magnetic "image" of the pipe, that helps the inspectors identify potentially hazardous defects in the pipeline wall.The goal of this project is to develop a reliable automated framework of algorithms that can be used for pipeline defect detection and evaluation. The emphasis is on the precise characterization and evaluation of defects such as surface breaking cracks and corrosion so that repair and replacement can be duly prioritized. This will be accomplished by a synergistic combination of signal processing and physics-based model-aided approaches to a magnetic inverse problem. Sophisticated optimization methodologies such as space mapping will be used to accelerate the solution process.This proposal is in co-operation with Intratech Inline Inspection Services Ltd. (Intratech), a firm which provides MFL imaging inspection services to pipeline operators throughout the world. The methodologies developed in the course of this project will benefit our industrial partner, the Canadian pipeline industry, and the environment, as they all  have a stake in improved pipeline inspection procedures.