Term 252

⁠An Intelligent Pipeline Integrity System that Predicts Failures and Deploys Inspection Only Where Needed

Project Type: Self-Initiated

Project Description

This project presents a robotic camera-assisted pipeline inspection system for real-time corrosion detection and integrity assessment. A deep learning model based on CNN architecture is used to detect corrosion regions, calculate corrosion percentage, and classify severity. The results are visualized through a dashboard and integrated with PIPESIM analysis to evaluate corrosion rate, wall thickness, and failure risk, providing an effective decision-support solution.