Smart systems for fault diagnosis and monitoring of industrial assets based on the industry 4.0 concept

• Grant number: 23/02413-2
• Support Opportunities: Regular Research Grants
• Start date: November 01, 2023
• End date: October 31, 2025
• Field of knowledge: Engineering - Electrical Engineering
• Principal Investigator: Pedro de Oliveira Conceição Junior
• Grantee: Pedro de Oliveira Conceição Junior
• Host Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Associated researchers: Alessandro Roger Rodrigues ; Marco Henrique Terra ; Paulo Roberto de Aguiar

Abstract

This research project aims to develop advanced methodologies for diagnosing and classifyingfailures in aerospace composite structures, aligning with the current trend in the industry and the concept of "Industry 4.0." The proposed approach will utilize data obtained from acoustic emission sensors, advanced feature extraction techniques, and pattern recognition methods to validate the methodologies. The validation will be performed by examining delamination and microcrack phenomena in carbon fiber-reinforced polymer (CFRP) structures and designing condition-based indicators through state-of-the-art deep learning algorithms and convolutional neural networks (CNNs). The research activities will concentrate on industrial automation to optimize and reduce manufacturing costs through the early identification of various types ofdamage and the prediction of the remaining useful life (RUL) of aerospace composite structures. This project will also guide scientific initiation, master's, and/or doctoral research work under the supervision of the principal investigator. The expected outcomes will contribute to the hostinstitution by generating new knowledge and disseminating it through publications in reputable journals. Additionally, it may lead to the formation of potential collaborations between academia and industry and the possibility of new research projects. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

MONSON, PAULO MONTEIRO DE CARVALHO; CONCEICAO JUNIOR, PEDRO DE OLIVEIRA; DOTTO, FABIO ROMANO LOFRANO; DE AGUIAR, PAULO ROBERTO; RODRIGUES, ALESSANDRO ROGER; DAVID, GABRIEL AUGUSTO. Structural damage classification in composite materials using the Wigner-Ville distribution and convolutional neural networks. Materials Letters, v. 369, p. 4-pg., 2024-05-31. (23/02413-2)