Abstract
HP austenitic stainless steel undergoes microstructural aging due to prolonged exposure to oxidizing and corrosive atmospheres in steam reforming furnaces. The derived aging states are classified by its service temperature and microstructural markers and monitoring it is important to residual life assessment. In this regard it was used a portable Eddy Current inspection system with the aid of machine learning classification tools, characterizing aging states in HP steel in real-time. The classification profile of a 12-meter tube was acquired, validated through Field Metallurgical Replication. The developed Eddy Current inspection system successfully differentiates three regions, revealing a progression of aging states.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call