Southern Methodist University

Sensr Monitoring Technologies LLC

Jase D Sitton

Brett Story

Walter F Bleser, Ii

John P Orsak

Adam De Jong

Provided herein is a method for determining a soil classification comprising: obtaining a soil sample; conducting two or more field tests on the soil sample to obtain raw data for each field test; and calculating the soil classification from the raw data by applying a previously obtained validation dataset obtained from a training and validation soil classification calculation using samples of known soil classification, wherein the validation dataset is obtained using a feed-forward backpropagation neural network.

Data fusion technique for predicting soil classification

A method for classifying a response signal of acceleration data of a structure includes obtaining at least one signal feature of a response signal, inputting the at least one signal feature into an artificial neural network, and classifying, using the artificial neural network, the response signal as an impact event or a non-impact event. One or more signal features may be used, including a response length feature, a number of peaks feature, a spectral energy feature, a dominant frequency feature, a maximum response feature, a center of mass feature, a slope feature, an average peak power feature, a response symmetry feature, or combinations thereof. One or more artificial neural networks may be used. The artificial neural networks may be trained using different combinations of signal features.

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Dallas, TX, United States of America

Jase D Sitton