Development and Implementation of an Internet of Things-Based Acoustic Emission Sensor for Industrial Process Monitoring

• Grant number: 24/01374-6
• Support Opportunities: Regular Research Grants
• Start date: July 01, 2024
• End date: June 30, 2026
• Field of knowledge: Engineering - Electrical Engineering
• Principal Investigator: Fábio Romano Lofrano Dotto
• Grantee: Fábio Romano Lofrano Dotto
• Host Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Associated researchers: Alessandro Roger Rodrigues ; Dennis Brandão ; Paulo Roberto de Aguiar
• Associated scholarship(s): 25/02367-6 - Hybrid System Architecture for Cloud-Enabled Manufacturing Monitoring Using IoT Acoustic Emission Sensors, BP.IC; 24/13409-9 - Characterization of Low-Cost Piezoelectric Ceramics for IoT Acoustic Emission Sensors in Industry 4.0, BP.IC

Abstract

The project aims a wireless acoustic emission sensor development based on the Internet of Things (IoT), designed to be compact and reconfigurable for monitoring processes within the framework of Industry 4.0. The primary innovation lies in establishing an IoT ecosystem through the embedded software in the sensor, facilitating the implementation of diagnostic models, feature extraction, pattern classification, and integration with cloud storage systems (cloud manufacturing). The technological challenge begins with the electronic and mechanical design and development of the sensor, coupled with the evaluation of commercial piezoelectric ceramics for capturing acoustic emission signals. Sensor characterization will encompass comprehensive analyses in both the time and frequency domains, considering the sensor's response in challenging factory floor environments. Emphasis will be on identifying a wireless communication solution enabling high-speed data transfer while efficiently managing battery consumption. Ultimately, the sensor's validation will be conducted through software developed in Matlab, connected to the sensor via a remote server employing the MQTT (Message Queuing Telemetry Transport) protocol. This validation process will involve tests within a CNC drilling process, ultimately leading to the classification of the thickness of metal sheets. The project involves undergraduate and master's students, collaboration with external research laboratories, publication in selective editorial policy journals, and potentially culminate in patent applications for the innovative techniques and products developed through the project with Instituto Nacional da Propriedade Industrial - INPI. (AU)