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Time-Frequency Analysis and Statistical Variation for Feature Extraction in the Dressing of Conventional Grinding Wheels
* 1 , * 2 , * 3 , * 4 , * 4
1  Paraná Federal Institute of Education, Science and Technology
2  Departamento de Engenharia Elétrica, UNESP, Av. Eng. Luiz E. C.Coube, 14-01, CEP: 17033-360, Bauru, SP, Brasil
3  Departamento de Engenharia Elétrica, Centro Universitário de Lins (UNILINS), Lins 16401-371, Brasil
4  Instituto Federal de Educação, Ciência e Tecnologia do Paraná (IFPR), campus Jacarezinho, Avenida Dr. Tito, 801, JardimPanorama, Jacarezinho, PR, CEP: 86400-000, Brazil
Academic Editor: Francisco Falcone

https://doi.org/10.3390/ECSA-12-26602 (registering DOI)
Abstract:

The study proposes a new methodology based on time-frequency analysis for the indirect monitoring of the dressing operation of conventional grinding wheels. Through a low-cost piezoelectric diaphragm (PZT), acoustic signals are captured during the process. The analysis is based on the coefficient of variation of the Short-Time Fourier Transform (STFT). The results indicate that the signal instability is high in the first passes but progressively decreases, reaching stability between passes 10 and 15. This suggests that the surface of the grinding wheel is regularized and ready for grinding. The methodology can serve as an objective indicator to assist the operator in interrupting the dressing process at the optimal moment, thereby optimizing grinding quality and reducing operational costs.

Keywords: Grinding Wheel Dressing; Acoustic Emission (AE); Short-Time Fourier Transform (STFT); Spectral Analysis; Dressing Monitoring
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