Detection of cracking in mild steel fatigue specimens using acoustic emission and digital image correlation

The aim of this investigation was to identify sources of AE in mild steel fatigue specimens and rel1ate them to damage mechanisms. Digital Image Correlation (DIC), a full-field strain measurement technique, was used to validate the findings. This paper describes in detail the results of a ‘dog bone’ style specimen undergoing uni-axial fatigue loading. This test forms part of a much larger programme designed to develop an AE monitoring system to identify damage initiation and growth from background noise in fatigue testing of automotive steels subjected to corrosion. Crack growth was monitored in the test using two AE sensors and, to allow a comparison with the detected and located signals, DIC images were captured periodically at peak loads. As part of the initial analysis located signals were compared with areas of high deformation and crack growth as identified by the DIC system. Results demonstrated that it is possible to distinguish the different AE signals originating from various possible failure mechanisms such as Plastic deformation, delamination of DIC paint and crack initiation and propagation. This might be utilized for an effective and powerful approach to monitor multiple failure mechanisms; this has significant applications in automotive chassis testing