Structural health monitoring of a rotating system using machine learning

• Grant number: 25/15120-9
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: February 01, 2026
• End date: January 31, 2027
• Field of knowledge: Engineering - Mechanical Engineering - Mechanics of Solids
• Principal Investigator: Fábio Roberto Chavarette
• Grantee: Heitor Primiano Gomes
• Host Institution: Instituto de Química (IQ). Universidade Estadual Paulista (UNESP). Campus de Araraquara. Araraquara , SP, Brazil

Abstract

This undergraduate research project proposes a methodology for developing SHMs for mechanical structures based on intelligent computing (IC) techniques, using random forests to analyze and monitor the structural integrity of a rotating system. Based on the acquisition and processing of signals obtained through the experimental bench, the random forest algorithm will be applied to the decision-making process to identify and characterize structural failures. The choice to use this intelligent system, i.e., the random forest, is justified by its learning and pattern recognition characteristics, as well as its good performance in other types of pattern recognition and diagnostic problems. (AU)