ADVANCED SIGNAL ANALYSIS APPLIED TO DISCRIMINATE DIFFERENT CORROSION FORMS BY ACOUSTIC EMISSION DATA

The analysis of three corrosion phenomena (uniform corrosion, pitting corrosion and stress corrosion cracking) has been carried out through the use of acoustic emission technique. Corrosion attacks have been obtained on three different types of martensitic stainless steel (X12Cr13, X4CrNiMo16-5-1, 17-4 PH) in a FeCl 3 solution, using conditions set by the ASTM G48 standard. These alloys are characterized by different mechanical, microstructural and electrochemical properties, for each which lead to develop specific corrosion forms, albeit subject to the same environmental conditions. A multivariate statistical analysis approach, based on PCA (Principal Component Analysis), has been adopted to evaluate AE data and to have highlight damage-sensitive features. Specific clusters of variables related to specific corrosion phenomena have been identified, promoting this approach as a procedure for discriminating onset of specific corrosion mechanism.