Quantitative Gun Barrel Diagnostics with Remote Field Eddy Currents and Artificial Intelligence

ABSTRACT: Gun barrels have a variety of failure modes that must be monitored over the life of a barrel. Fatigue cracking is one of the most critical failure modes and can result in catastrophic barrel rupture if not detected and addressed. Currently, there is no existing NDI method or equipment to assess fatigue cracking within the barrel wall. Luna"s proposed technique has the advantage of automated inspection using compact and portable hardware that can deployed on a flight line without need to remove barrels from the aircraft. Present eddy current inspection techniques rely on highly trained personnel to visually inspect and interpret test data, with human error serving as the primary drawback in using eddy currents to inspect the health of tubes. The automation of eddy current analysis and flaw sizing is very important in this research effort. Luna"s proposed technique makes use of artificial intelligence to classify the eddy current signals and to recognize disruptive variables such as variation in microstructure (magnetic permeability, electrical conductivity), lift-off and edge effects, as well as the rifling signature itself. The system will be designed to account for these variables and differentiate fatigue crack characteristics (fault length and depth) from false readings. BENEFIT: Luna"s goal for this project is to develop a portable inspection device that is suitable to inspect gun barrels on a flight line without need to remove them from the aircraft. The proposed work plan is focused on detecting cracks that grow radially outward into the barrel wall, providing an assessment of fault location, length, and depth. This technique is important to the military community, but is applicable to many other industries as well. For example, pipelines, pressure vessels, and steam generator tubes for power plants all contain critical modes of cracking such as fatigue cracking, fretting corrosion, stress corrosion cracking, or intergranular attacking on the outer surfaces of tubes. As design and analysis techniques evolve to incorporate fatigue crack detection, it is important to have measurement techniques capable of providing supporting data. The proposed technology expands the assessment of fatigue cracking capability to support these important challenges.