This rapid communication addresses early detection of fatigue damage evolution in polycrystalline alloys, based on the observation of surface deformation (e.g. roughness, linings and incisions). This method is well suited for calibration of other model-based and experimental tools for damage analysis and prediction in the fatigue crack initiation phase. To this end, the existing theory of symbolic dynamics-based feature extraction from time-series data is extended to the analysis of two-dimensional surface images. The resulting algorithms are experimentally validated on a fatigue-testing machine and a surface interferometer in the laboratory environment. The experiments have been conducted for analysis of statistical changes in the surface profiles due to gradual evolution of deformation in specimens, made of the 2024-T6 aluminum alloy.
All Science Journal Classification (ASJC) codes
- Engineering (miscellaneous)
- Applied Mathematics