Name
Abstract | ||
|---|---|---|
In this paper, we present a fast method for classification of defects detected by eddy current testing (ECT). This is done by using defects derived by lab experiments. For any defect, the ECT magnetic field response for different EC-probe's paths is represented on a complex plane to obtain Lissajous' figures. Their shapes are described through the use of few geometrical parameters forming a featur... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TIM.2018.2792848 | IEEE Transactions on Instrumentation and Measurement |
Keywords | Field | DocType |
Magnetic resonance imaging,Feature extraction,Probes,Trajectory,Atmospheric measurements,Particle measurements,Shape | Eddy-current testing,Decision tree,Feature vector,Matthews correlation coefficient,Pattern recognition,Naive Bayes classifier,Feature extraction,Electronic engineering,C4.5 algorithm,Artificial intelligence,Lissajous curve,Mathematics | Journal |
Volume | Issue | ISSN |
67 | 4 | 0018-9456 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gianni D'Angelo | 1 | 61 | 7.32 |
| Marco Laracca | 2 | 77 | 14.34 |
| Salvatore Rampone | 3 | 54 | 6.45 |
| Giovanni Betta | 4 | 30 | 7.15 |