This paper gives an overview of the use of Electrochemical Noise (EN) for corrosion studying and monitoring. Since the quality and reliability of noise data are affected by a number of acquisition parameters, such as sampling interval, sampling duration, D.C. trend and instrumental noise, some experimental and practical aspects were discussed. The use of statistical parameters such as standard deviation, Pit Index and/or Localization Index and Noise Resistance to analyze noise data of corroding systems were examined. Many experimental applications of Electrochemical Noise Measurements on different metals and alloys were given. EN data have been compared with traditional electrochemical techniques. EN allowed to characterize the corrosion behavior of samples giving in some cases good quantitative estimation. The transposition of current and potential noise acquisition in the frequency domain (by Fast Fourier Transform and/or Maximum Entropy Method), gave further information on corrosion mechanism and in particular permitted to identify the type of corrosion. Finally the use of Discriminant Analysis permitted to deduce the best sampling frequency and sampling duration for EN acquisition, able to discriminate between two different situations.
Montesperelli, G., & Gusmano, G. (2004). The use of electrochemical noise analysis on corroding systems. FLUCTUATION AND NOISE LETTERS, 4(3).
|Tipologia:||Articolo su rivista|
|Citazione:||Montesperelli, G., & Gusmano, G. (2004). The use of electrochemical noise analysis on corroding systems. FLUCTUATION AND NOISE LETTERS, 4(3).|
|Settore Scientifico Disciplinare:||Settore ING-IND/22 - Scienza e Tecnologia dei Materiali|
|Revisione (peer review):||Sì, ma tipo non specificato|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1142/S0219477504002129|
|Stato di pubblicazione:||Pubblicato|
|Data di pubblicazione:||2004|
|Titolo:||The use of electrochemical noise analysis on corroding systems|
|Autori:||Montesperelli, G; Gusmano, G|
|Appare nelle tipologie:||01 - Articolo su rivista|