PREDICTION OF S-WAVE ARRIVAL POINT ON RECEIVED SIGNAL OF BENDER ELEMENT TEST USING MACHINE LEARNING

Abstract

Generalization performance of a support vector regression model for the bender element test of which the S-wave arrival point is often difficult to determine on the received signal has been examined for the purpose of assisting experimenters' determination. Based on linear theory, 8960 received signals were numerically generated using realistic parameters. Then the model was trained with predictors of 11 dimensions which were extracted from the signal shape and the test condition as well as the true arrival point of the S-wave. The model has been validated by comparing the predicted values with the true arrival points using the synthetic signals. The prediction has also been made for a series of received signals in actual bender element tests which were conducted in Toyoura sand, a legorith simulant, and a peat and compared with arrival points which were determined by an expert. The prediction has substantially agreed with the expert's determination.