1.2.0 Selection of Processing Parameters.

1.2.1 FFT Length

The 'FFT Length' parameter determines the length of each segment used to obtain all the time-dependent quantities. Longer FFT length will generate spectra extending towards lower frequencies, but the time resolution of the processed data will be reduced because more points are used to generate a single result. Ideally, to generate reliable values of charge and frequency of corrosion events, the 'FFT length' should be sufficiently long that a plateau is visible in the low-frequency end of current and potential power spectral densities spectra.

Fig 13.0 The selection of FFT length can be made in the preference menu.The default length is 1024

1.2.2 FFT Window

FFT is usually calculated for a fixed length of time record. When the signal is discontinues, the abrupt ending on both ends of the signal causes a phenomenon called 'spectral leakage '. When a signal is terminated abruptly and analysed using FFT the spectrum spreads into all the the FFT bins rather than confining into a particular FFT bin. The spectral leakage can be reduced considerably if the signal amplitude can be gradually reduced to 0 at both the ends rather than abruptly cutting the signal. This type of technique is called 'windowing'. There are different types of windowing function are generally used, the most common one is 'hanning' window.

Fig 14.0 The software supports different windowing functions for FFT . The most popular windowing function is 'hanning'.

1.2.3 Sampling Interval

The sampling interval must be set equal to the actual sampling interval used during the acquisition of noise potential and noise current. The software ignores the time column and assume that the points are equally spaced of the sampling interval selected by the user.

Fig 15.0 The user need to to enter the sampling interval manually. This should be actual value used while acquiring the noise data from a potentiostat

1.2.4 Spectra Average

The spectra average parameter determines how many impedance spectra are used to calculate the averaged impedance spectrum. A high number of spectra will generally produce a less-noisy averaged impedance spectrum and a less noisy low frequency impedance vs. time plot, but it will decrease the time resolution.

Fig 16.0 Spectra average parameter determines how many spectra are averaged.

1.2.5 Points Average for Low Frequency Limit

This parameters determines how many low-frequency points are averaged to obtain the low-frequency values of impedance, potential power spectral density and current power spectral density. If a plateau is evident in the low-frequency end of the spectra, the parameter should be set to include roughly all the points that belongs to the low-frequency plateau.

Fig 17.0 This parameter determines how many low frequency points are averaged for estimating the low-frequency impedance.

1.2.6 Stern-Geary Coefficient

It is the Stern-Geary coefficient for the material under investigation, and it is required to estimate charge and frequency of corrosion events. It must be obtained experimentally or from the literature. The value of the Stern-Geary coefficient does not affect the calculation of impedance and resistance.

Fig 18.0 The stearn-Geary coefficient of the material under investigation can be entered here

1.2.7 Skip Iterations between saved spectra

The software provides an option for the user to save the spectra periodically, which is calculated by the FFT function. The option is provided to the user at the beginning of the processing. The software will ask the user whenever the software starts a new electro chemical noise analysis. It is not always required to save the complete spectra, doing so can result in very large files. The parameter 'skip iterations between saved spectra' determines how often the complete spectra will be saved to the disk.

Fig 19.0 Before processing a file the user is asked if complete spectra are to be saved.

Fig 20.0 Saving the complete spectrum is not required always and can result in large data file.

Table below shows how a typical spectra file is organized

Nth Record |
X axis ( in log) |
potential PSD |
Current PSD |
Impedance PSD |

1126 |
-3.01029996 |
0.52261167 |
0.00000002 |
4172.30476987 |

1126 |
-2.70926996 |
0.29134762 |
0.00000001 |
4156.83706831 |

1126 |
-2.53317870 |
0.06467640 |
0.00000000 |
6102.40065220 |

1126 |
-2.40823997 |
0.03039187 |
0.00000000 |
6702.12785726 |

- |
- |
- |
- |
- |

1126 |
-0.30103000 |
0.00000009 |
0.00000000 |
8180.12650179 |

1177 |
-3.01029996 |
0.61943963 |
0.00000001 |
4172.30476987 |

1177 |
-2.70926996 |
0.30128671 |
0.00000001 |
4156.83706831 |

1177 |
-2.53317870 |
0.05226266 |
0.00000000 |
6102.40065220 |

**Note : ( Total number of values depends on FFT Length, for Ex. if FFT length is 1024 there will 1024 values for 1126th record)

1.2.8 Segment Overlap Percentage

This parameter determines the overlap between a segment extracted from the complete dataset and the following segment. High values of overlap, combined with high values of spectra average generally provide less noisy output data, but this considerably increases the computation time.

Fig 21.0 A high percentage of FFT overlap ensures less noisy output data but increases computational time.

1.2.9 Processing Speed

This parameters determines how fast the processing progress. It is useful to set the processing speed to a low value in order to follow step-by step the calculations and identify the best set of process parameters. Once the best process parameters are identified, the processing speed can be increased to maximum value to reduce computation time. The processing speed parameter does not affect the values of the results.

Fig 22.0 User can change the processing speed. The value of processing speed does not affect the results.