PiggyBack AI Pipeline Inspection

Oceanit’s PiggyBack is an intelligent PIG system that enables unprecedented digital analysis of pipelines, using multispectral data capture. 

 

In tandem with RIVEAL, Oceanit’s PiggyBack is revolutionizing pipeline safety and maintenance. For energy sector, pipeline transportation and inspection is critical to ensure safe and efficient transport, predict and prevent accidents, and meet environmental regulatory goals.  “Pigging” is the practice of using PIGs, or Pipeline Inspection Gauges, which run through a pipeline and perform various maintenance, cleaning, and inspection operations.

PIGs earned their name from 1900s pipe operations, where early cleaning “pigs” were made from straw bales wrapped in barbed wire and made a squealing noise when traveling through a pipeline.  In more recent years, PIGs have evolved to capture intelligent data, such as ultrasonic leak detection.

Oceanit’s PiggyBack is an AI-driven, intelligent PIG system that enables unprecedented digital analysis of pipelines using multi-spectral qualitative data capture. PiggyBack takes pipeline inspection and maintenance to the next level, delivering deeper insights, faster and in more detail. 

Features include advanced multi-spectral Imaging, on-board INS for precise geolocation data, and predictive AI for actionable insights. PiggyBack can pinpoint issues such as corrosion or erosion, debris or wax build-up, pipe integrity defects, and more.

PiggyBack data is analyzed with computer vision AI to process hundreds of miles of pipeline data in just minutes. The system helps to identify surface anomalies such as corrosion, flagging trouble areas and allowing operators to quickly determine courses of action. 

PiggyBack can rapidly cover hundreds of miles of pipeline, providing actionable data to reduce maintenance costs, prevent accidents, and ensure ongoing safe and reliable operation.  It also improved the quality of preparation and application of advanced surface treatments, such as Oceanit’s DragX or HydroPel nanocomposites.