## 4 Experimental Results
### MSSA Results  
The signal from the Hall sensors is a multivariate input (i.e., 15 inputs) of the MSSA filter. The sensor probes scanned over 350 mm length of the MSR finned tube with a distance resolution of 1.0 mm. The input signal of the MSSA filter has a size of \(P\times L=15\times 351\). The stacking length \(M\) is chosen lower than half of the \(L\); for example, \(M=50\) was used in this study. Figure 6 shows an example of the distribution of the eigenvalues according to the sorting order. The eigenvalue was normalized to the sum to show the variance retained of the scanned magnetic signals in each eigenvalue. It shows three first eigenvalues having high values, which are corresponding to the trend signal. The middle eigenvalues are corresponding to the corrosion signal. In addition. the remained small eigenvalues are corresponding to the noise signal. The eigenvalues for the trend signal could be easily distinguished because of their high values; however, it is difficult to separate the eigenvalues of the corrosion and noise signals. Therefore, w-correlation was additionally used to separate the corrosion and noise signals. Figure 7 shows an example of the w-correlation matrix. The low w-correlation values area among the eigenvalues corresponds to the corrosion signal because the noise signal is random, thus has a low correlation with the corrosion signal. Figure 5: Differential magnetic scanned signal of the MFLT, ECT and PSECT methods on the MSR finned tube and the section view at the holes of 2.5 mm diameter (sensor #5). Figure 8 shows the decomposition of the magnetic scanned signal into the trend, noise and corrosion signals. The experiment was done with a 200-mA and 2000-Hz supplied current to the bobbin coil. The results show that the trend signal, which is the superposition of the magnetic field from the magnet (\(B_{M}\)), probe variation (\(B_{V}\)), material degradation (\(B_{D}\)) and exciting bobbin coil (\(B_{B}\)) could be extracted with the three first eigenvalues. The noise signal associated with the fins effect was also extracted even though a slight corrosion signal is still mixed. Finally, the corrosion signal could be successfully extracted with the eigenvalues from 4 th to 18 th. Figure 6: Eigenvalues distribution. Figure 7: W–correlation that could separate noise signal and corrosion signal. Figures 9-11 show the comparison results of the proposed MSSA filter with the Gabor and WT filters in the magnetic scanned signal of the MFLT and ECT methods, respectively. The MFLT signal was get much influenced by the noises from the fins effect, lift-off variation, and material degradation effect that the small corrosions were difficult to be detected; for instance, corrosion with a diameter of 1.3 mm and depth lower than 60% of the wall thickness. The strong variation of the background signal is mainly due to the variation of the lift-off and material degradation. Because the MSR tube has a high permeability, it will interact with the magnet during the scan that made the variation of the sensor lift-off. The material degradation, such as non-uniform changes of the magnetic permeability due to the stress concentration, has made a significant change in the MFLT signal intensity. However, the MSSA filter provides a good result with a clear indication of the corrosion signals than the wavelet and Gabor filters. The strong variation of the background signal was efficiently removed, but difficult in the wavelet and Gabor filters. The fins effect was smaller in the ECT method because of the skin effect, but the variation of the background signal was still clearly observed, as shown in Figure 10. The small corrosion with a diameter of 1.3 mm and depth lower than 80% of the wall thickness were not observed by the wavelet filter. In the Gabor filter result, the 60% depth corrosion could be observed, but appearing edges effect in the first and last part of the scanned signal. However, the MSSA filter is still working well and provides a clear signal of the corrosion.