TY - JOUR
T1 - Decoupling the influence of wall thinning and cladding thickness variation pulsed eddy current using principal component analysis
AU - Izzuddin, Faris
AU - Osman, Mohammad
AU - Shirkoohi, Maziar
AU - Duan, Fang
AU - Zhao, Zhanfang
PY - 2021/7/27
Y1 - 2021/7/27
N2 - Corrosion may develop and grow on steel pipes under layers of insulation and cladding. Inspection of the pipes through these protective layers is of paramount importance. Pulsed eddy current (PEC) is a primary non-destructive testing (NDT) technique candidate for this type of inspection as it requires no contact with the inspection material. To overcome the variability in PEC signals due to variations in the cladding thickness, a
large measurement set is analysed in this paper using principal component analysis (PCA). The PCA approach decomposes the signal set into a number of uncorrelated variables that explain the maximum amount of the variance in the data set, in which, in this respect, efficiently separate the influences contributed by the difference in the material properties of cladding and pipe wall. The feasibility of using PCA to quantify simulated steel pipe wall independent of confounding cladding thickness variations is investigated. It is found that, with sufficient amount of data, the approach can effectively separate the influences contributed by the wall thickness variations from the cladding thickness variations.
AB - Corrosion may develop and grow on steel pipes under layers of insulation and cladding. Inspection of the pipes through these protective layers is of paramount importance. Pulsed eddy current (PEC) is a primary non-destructive testing (NDT) technique candidate for this type of inspection as it requires no contact with the inspection material. To overcome the variability in PEC signals due to variations in the cladding thickness, a
large measurement set is analysed in this paper using principal component analysis (PCA). The PCA approach decomposes the signal set into a number of uncorrelated variables that explain the maximum amount of the variance in the data set, in which, in this respect, efficiently separate the influences contributed by the difference in the material properties of cladding and pipe wall. The feasibility of using PCA to quantify simulated steel pipe wall independent of confounding cladding thickness variations is investigated. It is found that, with sufficient amount of data, the approach can effectively separate the influences contributed by the wall thickness variations from the cladding thickness variations.
KW - Pipe inspection
KW - Non-destructive testing
KW - Pulsed eddy current
KW - Principal component analysis
U2 - 10.1109/JSEN.2021.3100648
DO - 10.1109/JSEN.2021.3100648
M3 - Article
SN - 1530-437X
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
ER -