Understanding Magnetic Flux Leakage Signals From Dents

The Magnetic Flux Leakage (MFL) technique is sensitive both to pipe wall geometry and pipe wall stresses, therefore MFL inspection tools have the potential to locate and characterize mechanical damage in pipelines. However, the combined influence of stress and geometry make MFL signal interpretation difficult for a number of reasons: 1) the MFL signal from mechanical damage is a superposition of geometrical and stress effects, 2) the stress distribution around a mechanically damaged region is very complex, consisting of plastic deformation and residual (elastic) stresses, 3) the effect of stress on magnetic behaviour is not well understood. Accurate magnetic models that can incorporate both stress and geometry effects are essential in order to understand MFL signals from dents. This paper reports on work where FEA magnetic modeling is combined with experimental studies to better understand dents from MFL signals. In experimental studies, mechanical damage was simulated using a tool and die press to produce dents of varying aspect ratios (1:1, 2:1, 4:1), orientations (axial, circumferential) and depths (3–8 mm) in plate samples. MFL measurements were made before and after selective stress-relieving heat treatments. These annealing treatments enabled the stress and geometry components of the MFL signal to be separated. Geometry and stress ‘peaks’ tend in most cases to overlap — however stress features are most prominent in the dent rim region and geometry peaks over central region. In general the geometry signal scales directly with depth. The stress scales less significantly with depth. As a result deep dents will display a ‘geometry’ signature while in shallow dents the stress signature will dominate. In the finite element analysis work, stress was incorporated by modifying the magnetic permeability in the residual stress regions of the modeled dent. Both stress and geometry contributions to the MFL signal were examined separately. Despite using a number of simplifying assumptions, the modeled results matched the experimental results very closely, and were used to aid in interpretation of the MFL signals.