Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on artificial intelligenc e is the subject of a new report. According to news reporting out of Virginia Po lytechnic Institute and State University by NewsRx editors, research stated, “Th is research proposes a framework for categorizing the radial tire mode shapes us ing machine learning (ML) based classification and feature recognition algorithm s, advancing the development of a digital twin for tire performance analysis.” Financial supporters for this research include Centire, Which Operates Under Nsf . Our news journalists obtained a quote from the research from Virginia Polytechni c Institute and State University: “Tire mode shape categorization is required to identify modal features in a specific frequency range to maximize driving perfo rmance and secure safety. However, the mode categorization work requires a lot o f manual effort to interpret modes. Therefore, this study suggests an ML-based c lassification tool to replace the conventional categorization process with two p rimary objectives: (1) create a database by categorizing the tire mode shapes ba sed on the identified features and (2) develop an ML-based surrogate model to cl assify the tire mode shapes without manual effort. The feature map of the tire m ode shape is built with the Zernike annular moment descriptor (ZAMD). The mode s hapes are categorized using the correlation value derived by the modal assurance criteria (MAC) with all ZAMD values for each tire mode shape and subsequently c reating the appropriate labels. The decision tree, random forests, and XGBoost, the representative supervised-learning algorithms for classification, are implem ented for surrogate model development.”
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