KnE Engineering

ISSN: 2518-6841

The latest conference proceedings on all fields of engineering.

A New Approach For Dressing Operation Monitoring Using Voltage Signals Via Impedance-Based Structural Health Monitoring

Published date: Feb 11 2018

Journal Title: KnE Engineering

Issue title: 6th Engineering, Science and Technology Conference - Panama 2017 (ESTEC 2017)

Pages: 942-952

DOI: 10.18502/keg.v3i1.1514

Authors:

Pedro de Oliveira Conceição Juniorpedroliveira@hotmail.comUniversidade Estadual Paulista UNESP, Bauru, São Paulo

Rodrigo de Souza Ruzziroruzzi@hotmail.comUniversidade Federal de Uberlândia UFU, Uberlândia, Minas Gerais

Wenderson Nascimento Lopeswendersonmanin@gmail.comUniversidade Estadual Paulista UNESP, Bauru, São Paulo

Felipe Aparecido Alexandrefelipeapalexandre@hotmail.comUniversidade Estadual Paulista Júlio Mesquita Filho - UNESP, Bauru, São Paulo

Fabricio Guimarães Baptistafabriciogb@feb.unesp.brUniversidade Estadual Paulista UNESP, Bauru, São Paulo

Paulo Roberto de Aguiaraguiarpr@feb.unesp.brUniversidade Estadual Paulista UNESP, Bauru, São Paulo

Eduardo Carlos Bianchibianchi@feb.unesp.brUniversidade Estadual Paulista UNESP, Bauru, São Paulo

Abstract:

Among the methods used in structural health monitoring (SHM), the electromechanical impedance technique (EMI), which uses piezoelectric transducers of lead zirconate titanate (PZT), stands out for its low cost. This paper presents a new approach for monitoring of the dressing operation based on structural health monitoring from the digital processing of voltage signals based on the time-domain response of a PZT transducer by EMI method. Experimental tests of the dressing process were performed by using a single-point dresser equipped with a natural diamond. The voltage signals in the time-domain were collected in different damage levels using a measurements EMI System. By using damage metrics, it was possible to qualify different damage levels that the diamond suffered during the dressing operation, observing variations from the magnitude of the signals. The dressing operation is of utmost importance for the grinding process and the dresser wear negatively affects the result of the process, which owns high added value. In this way, this work contributes with a new monitoring tool which aims ensuring a consistent dressing operation.

Keywords: Manufacturing process, automation, electromechanical impedance, dressing operation.

References:

[1] Aguiar, Paulo R, Andre G.O. Souza, Eduardo C Bianchi, Ricardo R. Leite, and Fabio Romano Lofrano Dotto. 2009. “Monitoring the Dressing Operation in the Grinding Process.” International Journal of Machining and Machinability of Materials 5 (1): 3–22. doi:10.1504/IJMMM.2009.023110.


[2] Baptista, F G, D Budoya, V A D Almeida, and J A C Ulson. 2014. “An Experimental Study on the Effect of Temperature on Piezoelectric Sensors for Impedance-Based Structural Health Monitoring.” Sensors 14 (1208–27).


[3] Baptista, F G, and J Filho Vieira. 2009. “A New Impedance Measurement System for PZT Based Structural Health Monitoring.” IEEE Trans. Instrum. Meas 58 (3602–8).



[4] Bilgen, Onur, Ya Wang, and Daniel J Inman. 2012. “Electromechanical Comparison of Cantilevered Beams with Multifunctional Piezoceramic Devices.” Mechanical Systems and Signal Processing 27. Elsevier: 763–77. doi:10.1016/j.ymssp.2011.09.002.


[5] Junior, Pedro O. C., Rubens V Souza, Cesar H Martins, Paulo R. Aguiar, F. I. Ferreira, and E.C. Bianchi. 2017. “Wear Monitoring of Single-Point Dresser in Dry Dressing Operation Based on Neural Models.” Proceedings of the IASTED International Conference Modelling, Identification and Control (MIC 2017) 36 (Mic): 178–85.
doi:10.2316/P.2017.848-054.


[6] Marchi, Marcelo, Fabricio Guimarães Baptista, Paulo Roberto de Aguiar, and Eduardo Carlos Bianchi. 2015. “Grinding Process Monitoring Based on Electromechanical Impedance Measurements.” Measurement Science and Technology 26 (4). IOP Publishing: 45601. doi:10.1088/0957-0233/26/4/045601.


[7] Martins, Cesar H. R., Paulo R. Aguiar, Arminio Frech, and Eduardo Carlos Bianchi. 2014. “Tool Condition Monitoring of Single-Point Dresser Using Acoustic Emission and Neural Networks Models.” IEEE Transactions on Instrumentation and Measurement 63 (3): 667–79. doi:10.1109/TIM.2013.2281576.


[8] Ni, Y.Q., X.G. Hua, K.Q. Fan, and J.M. Ko. 2005. “Correlating Modal Properties with Temperature Using Long-Term Monitoring Data and Support Vector Machine Technique.” Eng. Struct. 27: 1762–1773.


[9] Nilsson, J.W., and S.A. Riedel. 2003. Circuitos Elétricos.


[10] Oliveira, M. Anderson De, J. V. Filho, V. L. Junior, and D. J. Inman. 2013. “A Novel TimeDomain Technique for Damage Detection Applied to SHM Using Savitzky-Golay Filter.” Aerospace Engineering: A Roadmap to Intelligent Structures - Proceedings of the 9th International Workshop on Structural Health Monitoring, IWSHM 1: 996–
1003.


[11] Silveira, Ricardo Zanni, Leandro Melo Campeiro, and Fabricio G Baptista. 2017. “Performance of Three Transducer Mounting Methods in Impedance-Based Structural Health Monitoring Applications.” Journal of Intelligent Material Systems and Structures 1 (14). doi:10.1177/1045389X17689942.


[12] Tandon, N, and A Choudhury. 2000. “A Review of Vibration and Acoustic Measurement Methods for the Detection of Defects in Rolling Element Bearings” 32 (1999): 469–80.

XML
Download
HTML
Cite
Share
Crossref Cited-by logo

6

Pedro Oliveira C. Junior, Salvatore Conte, Doriana M. D’Addona, Paulo R. Aguiar, Fabricio G. Baptista, Eduardo C. Bianchi, Roberto Teti (2019)

Damage patterns recognition in dressing tools using PZT-based SHM and MLP networks, Procedia CIRP

Volume: 79, First Page: 303

10.1016/j.procir.2019.02.071

Pedro O. Junior, Doriana M. D’Addona, Felipe A. Alexandre, Rodrigo Ruzzi, Paulo R. Aguiar, Fabricio G. Baptista, Eduardo C. Bianchi (2019)

Impedance-Based PZT Transducer and Fuzzy Logic to Detect Damage in Multi-point Dressers,

First Page: 213

10.1007/978-3-030-16943-5_19

Pedro Junior, Doriana M. D’Addona, Paulo Aguiar, Roberto Teti (2018)

Dressing Tool Condition Monitoring through Impedance-Based Sensors: Part 2—Neural Networks and K-Nearest Neighbor Classifier Approach, Sensors

Volume: 18, Issue: 12, First Page: 4453

10.3390/s18124453

Wenderson N. Lopes, Pedro O. C. Junior, Paulo R. Aguiar, Felipe A. Alexandre, Fábio R. L. Dotto, Paulo Sérgio da Silva, Eduardo C. Bianchi (2021)

An efficient short-time Fourier transform algorithm for grinding wheel condition monitoring through acoustic emission, The International Journal of Advanced Manufacturing Technology

Volume: 113, Issue: 1-2, First Page: 585

10.1007/s00170-020-06476-3

Felipe Aparecido Alexandre, José Claudio Lopes, Lucas de Martini Fernandes, Fernando Sabino Fonteque Ribeiro, Breno Ortega Fernandez, Luiz Eduardo de Angelo Sanchez, Rodolfo Fischer Moreira de Oliveira, Hamilton José de Mello, Paulo Roberto Aguiar, Eduardo Carlos Bianchi (2020)

Depth of dressing optimization in CBN wheels of different friabilities using acoustic emission (AE) technique, The International Journal of Advanced Manufacturing Technology

Volume: 106, Issue: 11-12, First Page: 5225

10.1007/s00170-020-04994-8