Time–frequency methods for trend removal in electrochemical noise data

2012 ◽  
Vol 70 ◽  
pp. 199-209 ◽  
Author(s):  
A.M. Homborg ◽  
T. Tinga ◽  
X. Zhang ◽  
E.P.M. van Westing ◽  
P.J. Oonincx ◽  
...  
Keyword(s):  
Electrochemical Noise ◽  
Time Frequency ◽  
Noise Data ◽  
Trend Removal

Novel time–frequency characterization of electrochemical noise data in corrosion studies using Hilbert spectra

2013 ◽  
Vol 66 ◽  
pp. 97-110 ◽  
Author(s):  
A.M. Homborg ◽  
E.P.M. van Westing ◽  
T. Tinga ◽  
X. Zhang ◽  
P.J. Oonincx ◽  
...  
Keyword(s):  
Electrochemical Noise ◽  
Time Frequency ◽  
Corrosion Studies ◽  
Noise Data

scholarly journals The reassigned pseudo Wigner–Ville transform in electrochemical noise analysis

2019 ◽  
Vol 21 (44) ◽  
pp. 24361-24372 ◽  
Author(s):  
Ivana Jevremovic ◽  
Andreas Erbe
Keyword(s):  
Signal Processing ◽  
Time Evolution ◽  
Electrochemical Noise ◽  
Noise Analysis ◽  
Time Frequency ◽  
Noise Data ◽  
Frequency Components

Several different time–frequency transforms from signal processing were used to analyze electrochemical noise data to determine frequency components contained within the noise record and their time evolution.

Development of Time-Frequency Analysis in Electrochemical Noise for Detection of Pitting Corrosion

CORROSION ◽  
10.5006/2900 ◽  
2018 ◽  
Vol 75 (2) ◽  
pp. 183-191 ◽  
Author(s):  
Mohammad Nazarnezhad Bajestani ◽  
Jaber Neshati ◽  
Mohammad Hossein Siadati
Keyword(s):  
Frequency Analysis ◽  
Pitting Corrosion ◽  
Electrochemical Noise ◽  
Time Frequency Analysis ◽  
Time Frequency

Transient Analysis and Simulation of Pitting Corrosion for the Estimation of Noise Resistance

CORROSION ◽  
2000 ◽  
Vol 56 (9) ◽  
pp. 928-934
Author(s):  
G. Miramontes de León ◽  
D. C. Farden ◽  
D. E. Tallman
Keyword(s):  
Computer Simulation ◽  
Pitting Corrosion ◽  
Transient Analysis ◽  
Electrochemical Noise ◽  
Electrochemical Impedance ◽  
Transient Behavior ◽  
Noise Resistance ◽  
New Approach ◽  
Noise Data ◽  
Current Transients

Abstract A new approach for the measurement of noise resistance based on the transient behavior of pitting corrosion is presented. Potential noise and current transients have been recognized as a characteristic behavior of pitting corrosion. This new approach uses the transient information present during corrosion as a way to estimate the noise resistance of coated metals directly. Computer simulation and analytical results are presented, indicating that the new technique can be applied to the problem of noise resistance estimation. This new approach was applied to experimental electrochemical noise data obtained with commercial electrochemical impedance spectroscopy (EIS)/electrochemcial noise measurement (ENM) equipment.

THE USE OF ELECTROCHEMICAL NOISE ANALYSIS ON CORRODING SYSTEMS

2004 ◽  
Vol 04 (03) ◽  
pp. R39-R55 ◽  
Author(s):  
G. MONTESPERELLI ◽  
G. GUSMANO
Keyword(s):  
Electrochemical Noise ◽  
Quantitative Estimation ◽  
Noise Analysis ◽  
Electrochemical Techniques ◽  
Sampling Interval ◽  
Entropy Method ◽  
Corrosion Mechanism ◽  
Statistical Parameters ◽  
Noise Data ◽  
Sampling Duration

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.

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