Combined Use of Modal Analysis and Machine Learning for Materials Classification - Abdelkader, Mohamed; Noman, Muhammad Tayyab; Amor, Nesrine; Petru, Michal; Mahmood, Aamir (Materials (Basel, Switzerland), 2021)
The present study deals with modal work that is a type of framework for structural dynamic testing of linear structures. Modal analysis is a powerful tool that works on the modal parameters to ensure the safety of materials and eliminate the failure possibilities. The concept of classification through this study is validated for isotropic and orthotropic materials, reaching up to a 100% accuracy when deploying the machine learning approach between the mode number and the associated frequency of the interrelated variables that were extracted from modal analysis performed by ANSYS. This study shows a new classification method dependent only on the knowledge of resonance frequency of a specific material and opens new directions for future developments to create a single device that can identify and classify different engineering materials.
Keywords: anisotropic; resonance frequency; isotropic; orthotropic; modal analysis; mode shapes