Structural health monitoring system of dressers based on electromechanical impedance measurements

• Grant number: 16/02831-5
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: August 01, 2016
• End date: February 29, 2020
• Field of knowledge: Engineering - Electrical Engineering
• Principal Investigator: Paulo Roberto de Aguiar
• Grantee: Pedro de Oliveira Conceição Junior
• Host Institution: Faculdade de Engenharia (FE). Universidade Estadual Paulista (UNESP). Campus de Bauru. Bauru , SP, Brazil
• Associated scholarship(s): 17/16921-9 - A new approach for dressing operation monitoring based on electromechanical impedance using computational intelligence, BE.EP.DR

Abstract

Due of the need of reliable methods to indicate a proper dressing, and the need to prevent the consequences of excessive wear in dressers, this research aims at assessing the changes in the structural health of the single point dresser and multipoint dresser caused by the wear, during its lifetime or damage and failure caused by other factors, such as temperature or shocks. The approach is to employ the fundamentals of damage detection based on the electromechanical impedance (EMI) commonly used in structural health monitoring for monitoring the dressing operation. The impedance method is characterized by its flexibility of using low-cost piezoelectric transducers, such as ceramics of Lead Zirconate Titanate (PZT), in structural damage detection. In this sense, research has been conducted in the Transducers and Data Acquisition Laboratory, coordinated by Professor Fabricio Guimarães Baptista, related to the project funded by the Sao Paulo State Foundation (FAPESP) (2015 / 02500-6) entitled "Monitoring Systems Based on Electromechanical Impedance Technical: New Trends and Challenges ". In addition, results of recent research in the Grinding Process Laboratory, coordinated by Professor Paulo Roberto de Aguiar, shows that the low-cost PZT transducer has great potential in monitoring the grinding process. Hence, this research aims to approach theoretically a new way of monitoring the dressing operation with specific regard to the wear of single-point dressers and fault detection and multipoint dressers by using impedance correlations measured through the EMI method. Consequently, this work will contribute to a new technology for monitoring the dressing operation and optimizing the grinding process.

Scientific publications

(6)

(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)

LOPES, WENDERSON NASCIMENTO; FERREIRA, FABIO ISAAC; ALEXANDRE, FELIPE APARECIDO; SANTOS RIBEIRO, DANILO MARCUS; CONCEICAO JUNIOR, PEDRO DE OLIVEIRA; DE AGUIAR, PAULO ROBERTO; BIANCHI, EDUARDO CARLOS. Digital signal processing of acoustic emission signals using power spectral density and counts statistic applied to single-point dressing operation. IET Science Measurement & Technology, v. 11, n. 5, p. 631-636, AUG 2017. (16/02831-5)

DA CONCEICAO JUNIOR, PEDRO OLIVEIRA; FERREIRA, FABIO ISAAC; DE AGUIAR, PAULO ROBERTO; BATISTA, FABRICIO GUIMARAES; BIANCHI, EDUARDO CARLOS; D'ADDONA, DORIANA MARILENA; TETI, R; DADDONA, DM. Time-domain analysis based on the electromechanical impedance method for monitoring of the dressing operation. 11TH CIRP CONFERENCE ON INTELLIGENT COMPUTATION IN MANUFACTURING ENGINEERING, v. 67, p. 6-pg., 2018-01-01. (16/02831-5)

JUNIOR, PEDRO; D'ADDONA, DORIANA M.; AGUIAR, PAULO R.; TETI, ROBERTO. Dressing Tool Condition Monitoring through Impedance-Based Sensors: Part 1-PZT Diaphragm Transducer Response and EMI Sensing Technique. SENSORS, v. 18, n. 12, DEC 2018. (17/16921-9, 16/02831-5)

JUNIOR, PEDRO; D'ADDONA, DORIANA M.; AGUIAR, PAULO; TETI, ROBERTO. Dressing Tool Condition Monitoring through Impedance-Based Sensors: Part 2-Neural Networks and K-Nearest Neighbor Classifier Approach. SENSORS, v. 18, n. 12, DEC 2018. (17/16921-9, 16/02831-5)

JUNIOR, PEDRO OLIVEIRA C.; CONTE, SALVATORE; D'ADDONA, DORIANA M.; AGUIAR, PAULO R.; BAPTISTA, FABRICIO G.; BIANCHI, EDUARDO C.; TETI, ROBERTO; TETI, R; DADDONA, DM. Damage patterns recognition in dressing tools using PZT-based SHM and MLP networks. 11TH CIRP CONFERENCE ON INTELLIGENT COMPUTATION IN MANUFACTURING ENGINEERING, v. 79, p. 5-pg., 2019-01-01. (17/16921-9, 16/02831-5)

JUNIOR, PEDRO O.; D'ADDONA, DORIANA M.; ALEXANDRE, FELIPE A.; RUZZI, RODRIGO; AGUIAR, PAULO R.; BAPTISTA, FABRICIO G.; BIANCHI, EDUARDO C.; GAPINSKI, B; SZOSTAK, M; IVANOV, V. Impedance-Based PZT Transducer and Fuzzy Logic to Detect Damage in Multi-point Dressers. ADVANCES IN MANUFACTURING II, VOL 4 - MECHANICAL ENGINEERING, v. N/A, p. 10-pg., 2019-01-01. (17/16921-9, 16/02831-5)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

CONCEIÇÃO JUNIOR, Pedro de Oliveira. Tool condition monitoring in the dressing process through electromechanical impedance and machine learning. 2020. Doctoral Thesis - Universidade Estadual Paulista (Unesp). Faculdade de Engenharia. Bauru Bauru.