Oil Pipeline Defect Detection

Oil pipeline defect detection aims to improve pipeline safety and efficiency by automating the identification of flaws like leaks and corrosion. Current research emphasizes the use of autonomous vehicles (drones, underwater robots, and amphibious systems) equipped with various sensors (acoustic, optical, magnetic flux leakage) to collect data, coupled with advanced image processing and machine learning algorithms, including convolutional neural networks (CNNs), for automated defect identification. This work is crucial for minimizing costly downtime, preventing environmental disasters, and enhancing the overall reliability of pipeline infrastructure.