Abstract
Aiming at the problems of complex sensor layout, low detection accuracy when using guided wave to detect the elbow’s erosion degree, this research presents a new approach based on asymmetric guided wave and Genetic Algorithm-Least Support Vector Machine (GA-LSSVM). The program for calculating elbow’s dispersion curve was compiled using the semi-analytical finite element (SAFE) method. Through numerical simulation, it is found that the bending mode in the guided wave signal at the outer arch back position of the receiving end decreases with the increase of the erosion degree, which leads to the decrease of the signal’s time domain energy. Finally, The GA-LSSVM model were used to predict various elbow specimens’ residual wall thickness, and the results shows the high prediction accuracy. The average accuracy of predicting the new elbows is 87.63%. This research provides a feasible scheme for detecting elbow’s erosion degrees in engineering.
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