TY - JOUR
T1 - Determining feature extraction parameters for pulsed eddy current sensor
T2 - a minimisation problem approach
AU - Nafiah, Faris
AU - Tokhi, Mohammad O
AU - Shirkoohi, Gholamhossein
AU - Duan, Fang
AU - Zhao, Zhanfang
AU - Rees-Lloyd, Owen
PY - 2021/11/15
Y1 - 2021/11/15
N2 - Pulsed eddy current (PEC) is an electromagnetic non-destructive testing (NDT) technique mainly used to inspect corrosion in pipelines. Like many other NDT techniques, to quantify pipe wall thickness, a signal feature has to be extracted from the PEC response. The authors’ previous work has exploited the linear relationship of the time-derivative feature to propose an in-situ calibration routine. However, to extract the time-derivative feature, two configuration parameters need to be determined prior to feature extraction. To the authors’ knowledge, none of the previous works explores the determining factors of this configuration parameters, where the current technique is still limited to using brute force method or trial-and-error. This paper brings novelty by formulating the aforementioned problem as a minimisation problem, and solving it using a particle swarm optimisation (PSO) algorithm. The obtained results, compared against brute force method, demonstrate the feasibility and performance improvement of using PSO in determining the configuration parameters. The approach thus presented is validated and the results obtained are justified by analysing the underlying physical system theory.
AB - Pulsed eddy current (PEC) is an electromagnetic non-destructive testing (NDT) technique mainly used to inspect corrosion in pipelines. Like many other NDT techniques, to quantify pipe wall thickness, a signal feature has to be extracted from the PEC response. The authors’ previous work has exploited the linear relationship of the time-derivative feature to propose an in-situ calibration routine. However, to extract the time-derivative feature, two configuration parameters need to be determined prior to feature extraction. To the authors’ knowledge, none of the previous works explores the determining factors of this configuration parameters, where the current technique is still limited to using brute force method or trial-and-error. This paper brings novelty by formulating the aforementioned problem as a minimisation problem, and solving it using a particle swarm optimisation (PSO) algorithm. The obtained results, compared against brute force method, demonstrate the feasibility and performance improvement of using PSO in determining the configuration parameters. The approach thus presented is validated and the results obtained are justified by analysing the underlying physical system theory.
U2 - 10.1109/JSEN.2021.3119466
DO - 10.1109/JSEN.2021.3119466
M3 - Article
SN - 1530-437X
VL - 21
SP - 26124
EP - 26131
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
IS - 22
ER -