Events6th International Electronic Conference on Sensors and Applications
Published
This submission belongs to the session D. Applications of the event 6th International Electronic Conference on Sensors and Applications
Published date
14 Nov, 2019
Citation
Pedro Oliveira Junior, Paulo R Aguiar, Rodrigo S Ruzzi, Salvatore Conte, Martin Aulestia Viera, Felipe Aparecido Alexandre, Fabricio Guimarães Baptista, Cristiano Soares Junior, Tool Condition Monitoring in Grinding Operation using Piezoelectric Impedance and Wavelet Analysis, in Proceedings of 6th International Electronic Conference on Sensors and Applications, 15 November–30 November 2019, MDPI: Basel, Switzerland, doi: 10.3390/ecsa-6-06589
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Tool Condition Monitoring in Grinding Operation using Piezoelectric Impedance and Wavelet Analysis

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Rodrigo S Ruzzi 3
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1. Department of Electrical Engineering, São Paulo State University; Av. Eng. Luiz Edmundo Carrijo Coube, 14-01, Bauru, Brazil, Brazil
2. Department of Electrical Engineering, São Paulo State University; Av. Eng. Luiz Edmundo Carrijo Coube, 14-01, Bauru, Brazil
3. School of Mechanical Engineering, Federal University of Uberlandia, Av. João de Ávila 2121, Uberlandia , Brazil
4. Department of Chemical, Material and Industrial Production Engineering, University of Naples Federico II, Piazzale Tecchio 80, 80125, Naples, Italy
5. São Paulo State University, UNESP, Brazil
Abstract

The purpose of the present study is to monitor tool condition in the grinding operation through the electromechanical impedance (EMI) by using wavelet analysis. To achieve this, a dressing experiment was conducted on an industrial aluminum oxide grinding wheel by fixing a stationary single-point diamond tool. The proposed approach was verified experimentally at various dressing tool conditions. The signals obtained from an EMI data acquisition system, composed of a piezoelectric diaphragm transducer attached to the tool holder, were processed by using the discrete wavelet transform. The approximation and detail coefficients obtained from wavelet decomposition were used to estimate the tool condition by using the correlation coefficient deviation metric (CCDM). The results show good performance in tool condition monitoring by the proposed technique, which effectively contributes to modern machine tool automation

Keywords
Piezoelectric transducers
sensor monitoring
electromechanical impedance
wavelet transform
tool condition monitoring
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