Abstract
This project aims to develop and evaluate machine learning methods for compensating the effects of temperature on signals obtained through the Electromechanical Impedance (EMI) method, as well as for detecting and classifying structural damage. Temperature variation is known to affect EMI signals due to the sensitivity of commonly used sensors and actuators, which can compromise the accur…