Anglysis of model-assisted probability of detection for eddy current nondestructive testing based on efficient polynomial chaos expansion metamodel
Probability of detection(PoD)is very important to quantify the detection ability of eddy current nondestructive testing(NDT)system.In the study of Model Assisted PoD(MAPoD),large amounts of data are needed to accurately determine the model parameters which is time consuming and hard to achieve experimentally or by simulation.To overcome this issue,in this paper,the ordinary least square based polynomial chaos expansion(OLS PCE)metamodel was proposed,to improve the efficiency of the MAPoD study for 3D eddy current NDT problem with the application of kernel degeneration(KD).The case of placing a coil with a finite cross section above the thick plate with a surface slot with selecting the coil position and liftoff as the uncertainty propagation parameters were tested.The results showed that the differences of PoD parameters between the ones predicted by the OLS PCE metamodel and calculated by the KD-BEM based physical model were smaller than 1％with less time required.
boundary element methodmetamodelpolynomial chaos expansioneddy current nondestructive testingmodel assisted probability of detection
万方数据
维普
