Optimal Ultrasonic Pulse Repetition Rate for Damage Detection in Plates Using Neural Networks

An experimental study for the determination of the optimal pulse repetition rate frequency (PRF) for damage detection in aluminum and composites is presented in this paper. a method for predicting the damage size and depth from C-Scan results using neural networks is also presented. Two graphite fiber IM7/F5250-4 (Bismaleimid) composite plates and four aluminum plates were used for the study. Damage was fabricated by drilling holes of varying depth and diameter on the test specimens. Ultrasonic transmission tests were carried out on a DIGITALWAVE immersion type C-Scan system. PRF values from 100 to 5000 Hz were investigated for the scan. the defect locations were clearly observed as peaks in the C-Scan mesh. the equivalent hole diameter, depth and the location of the holes with respect to a predetermined edge were calculated from the C-Scan plots and correlated with the actual values to determine the optimal PRF values. a close correlation was found between the calculated diameter obtained from the C-Scan results and the actual hole diameter. Low PRF values (100 Hz) were found best for scanning of aluminum and intermediate values (500 Hz) were best for scanning of composites. Prediction of the actual damage size from the C-Scan calculated damage size was successfully accomplished with radial basis function neural network