Advanced signal analysis of acoustic emission data to discrimination of different corrosion forms

Aim of the present work is to give an analytical approach suitable to distinguish three different corrosion forms through the use of acoustic emission technique. Corrosion attacks have been obtained on three different types of martensitic stainless steel in a FeCl3 solution, using conditions set by the ASTM G48 standard. These martensitic stainless steel used were characterised by different mechanical, microstructural and electrochemical properties, which lead to the development of specific corrosion forms, albeit the steels were tested in the same environmental conditions. A multivariate statistical analysis approach, based on principal component analysis (PCA) and self-organising map (SOM), has been adopted to evaluate AE data and to obtain highlight damage-sensitive features. Specific clusters of variables related to specific corrosion phenomena have been identified, promoting this analysis approach as a potential procedure for discriminating onset of a specific corrosion mechanism.