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Acoustic Emission Monitoring of Grinding-Polishing of Extra-Low Dispersion Lens

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Abstract

In this study, acoustic emission (AE) was adopted to monitor the grinding–polishing process of extra-low dispersion (ED) lens. S-FPL51, a raw material of ED lens, exhibits extraordinary optical properties such as high Abbe numbers and low dispersion. However, processing S-FPL51 is difficult because of its mechanical properties such as low hardness and high wear abrasion, which make the adjustment of the lens thickness difficult, and the lens are scratched easily. Therefore, an AE sensor was employed to monitor the grinding–polishing process because of its high sensitivity to material removal. Furthermore, several experiments were conducted to establish a relation between grinding–polishing parameters, such as pressure, rotating speed, root mean square (RMS) value of AE signals, and material removal rate (MRR). The results indicated that MRR is strongly correlated to the RMS of AE signals. Subsequently, several MRR models were derived based on the experimental data, and an AE signal term was introduced into the modified Preston equation to estimate MRR. Moreover, the results indicated the AE sensor to be a potential tool for monitoring the grinding–polishing process of optical lens.

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References

  1. Leviton, D. B., Frey, B. J., & Henry, R. M. (2013). Temperature-dependent refractive index measurements of S-FPL51, S-FTM16, and S-TIM28 to cryogenic temperatures. Process SPIE, 8863(886308), 1–14. https://doi.org/10.1117/12.2024821

    Article  Google Scholar 

  2. Pelizzo, M. G., Corso, A. J., Santi, G., & Tessarolo, E. (2019). Characterization techniques and qualification tests of glass and optical coatings for space applications. Process SPIE, 11116(111160N), 1–8. https://doi.org/10.1117/12.2530214

    Article  Google Scholar 

  3. Marks, D. L., Son, H. S., Phillips, Z. F., Feller, S. D., Kim, J., & Brady D. J. (2014). Multiscale Camera Objective with sub 2 Arcsec Resolution, 36 degree Field-of-View. In Computational Optical Sensing and Imaging (pp. CTh1C-3). Optical Society of America. https://doi.org/10.1364/COSI.2014.CTh1C.3

  4. Sakimoto, K., Akitaya, H., Yamashita, T., Kawabata, K. S., Nakaya, H., Miyamoto, H., Harao, T., Itoh, R., Matsui, R., Moritani, Y., Nakashima, A., Ohsugi, T., Sasada, M., Takai, K., Ueno, I., Ui, T., Urano, T., & Yoshida, M. (2012). An optical and near-infrared multipurpose instrument HONIR. Process SPIE, 8446(844673), 1–12. https://doi.org/10.1117/12.926425

    Article  Google Scholar 

  5. Ortiz, R., Carrasco, E., Paez, G., Reyes, J., Hidalgo, A., Dalton, G., Trager, S., Aguerri, J. A. L., Bonifacio, P., Vallenari, A., Abrams, D. C., & Middleton, K. (2018). Antireflective coatings for the red camera of WEAVE spectrograph. Process SPIE, 10706(107065G), 1–12. https://doi.org/10.1117/12.2313955

    Article  Google Scholar 

  6. Corso, A. J., Tessarolo, E., Baccaro, S., Cemmi, A., Sarcina, I. D., Magrin, D., Borsa, F., Ragazzoni, R., Viotto, V., Novi, A., Burresi, M., Pellowski, F., Salatti, M., Pagano, I., & Pelizzo, M. G. (2018). Rad-hard properties of the optical glass adopted for the PLATO space telescope refractive components. Optics Express, 26(26), 33841–33855. https://doi.org/10.1364/OE.26.033841

    Article  Google Scholar 

  7. Sutowski, P., Nadolny, K., & Kaplonek, W. (2012). Monitoring of cylindrical grinding processes by use of a non-contact AE system. International Journal of Precision Engineering and Manufacturing, 13, 1737–1743. https://doi.org/10.1007/s12541-012-0228-7

    Article  Google Scholar 

  8. Nasir, V., Cool, J., & Sassani, F. (2017). Acoustic emission monitoring of sawing process: Artificial intelligence approach for optimal sensory feature selection. The International Journal of Advanced Manufacturing Technology, 102, 4179–4197. https://doi.org/10.1007/s00170-019-03526-3

    Article  Google Scholar 

  9. Jiang, C., Song, Q., Guo, D., & Li, H. (2014). Estimation algorithm of minimum dwell time in precision cylindrical plunge grinding using acoustic emission signal. International Journal of Precision Engineering and Manufacturing, 15, 601–607. https://doi.org/10.1007/s12541-014-0377-y

    Article  Google Scholar 

  10. Zhang, G., Zeng, Y., Zhang, W., Zhou, H., Wen, Z., & Yao, Y. (2016). Monitoring for damage in two-dimensional pre-stress scratching of SiC ceramics. International Journal of Precision Engineering and Manufacturing, 17, 1425–1432.

    Article  Google Scholar 

  11. Law, L., Kim, J., & Lee, S. (2013). An approach to monitoring the thermomechanical behavior of a spindle bearing system using acoustic emission (AE) energy. International Journal of Precision Engineering and Manufacturing, 14, 1169–1175.

    Article  Google Scholar 

  12. Sutowaski, P., & Swiecik, R. (2017). The estimation of machining results and efficiency of the abrasive electro-discharge grinding process of Ti6Al4V titanium alloy using the high-frequency acoustic emission and force signals. The International Journal of Advanced Manufacturing Technology, 94, 1263–1282.

    Article  Google Scholar 

  13. Liu, C. S., & Qu, Y. J. (2020). Grinding wheel loading evaluation by using acoustic emission signals and digital image processing. Sensor, 20(15), 4092–4104.

    Article  Google Scholar 

  14. Torres, F., & Griffin, J. (2015). Control with micro precision in abrasive machining through the use of acoustic emission signals. International Journal of Precision Engineering and Manufacturing, 16, 441–449.

    Article  Google Scholar 

  15. Pilny, L., Bissacco, G., De Cguffrem, L., & Ramsing, J. (2016). Acoustic emission-based in-process monitoring of surface generation in robot-assisted polishing. International Journal of Computer Integrated Manufacturing, 29(11), 1218–1226.

    Article  Google Scholar 

  16. Geng, Z., Puhan, D., & Reddyhoff, T. (2019). Using acoustic emission to characterize friction and wear in dry sliding steel contacts. Tribology International, 134, 394–407.

    Article  Google Scholar 

  17. Hase, A., Mishina, H., & Wada, M. (2012). Correlation between features of acoustic emission signals and mechanical wear mechanisms. Wear, 292–293(15), 144–150.

    Article  Google Scholar 

  18. Bhuiyan, M. S. H., Choudhury, I. A., Mahari, M., Nukman, Y., & Dawal, S. Z. (2016). Application of acoustic emission sensor to investigate the frequency of tool wear and plastic deformation in tool condition monitoring. Meausrement, 92, 208–217.

    Google Scholar 

  19. Zhu, W. L., & Beaucamp, A. (2020). Compliant grinding and polishing: A review. International Journal of Machine Tools and Manufacture, 158, 103634.

    Article  Google Scholar 

  20. Seshan, K. (Ed.). (2012). Handbook of thin film deposition. William Andrew.

  21. Guiot, A., Pattofatto, S., & Tournier, C. (2011). Modeling of a polishing tool to simulate material removal. Advanced Materials Research, 223, 754–763.

    Article  Google Scholar 

  22. Liu, C. W., Chen, H. C., & Lin, S. C. (2019). Acoustic emission monitoring system for hard polishing of sapphire wafer. Sensors and Materials, 31(9), 2681–2689.

    Article  Google Scholar 

  23. Goossens, F., Cherif, M., & Cahuc, O. (2015). Modelling of the polishing process of AISI 316L with structured abrasive belts. International Journal of Machining and Machinability of Materials, 17(5), 434–453.

    Article  Google Scholar 

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Acknowledgements

The authors are grateful for the support of the Research Project of the Ministry of Science and Technology, Taiwan (MOST108-2218-E-007-059-MY2).

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  1. Department of Power Mechanical Engineering, National Tsing Hua University, Xinzhu, 30013, Taiwan

    Chun-Wei Liu, Hong-Chang Chen & Shih-Chieh Lin

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  1. Chun-Wei Liu
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  2. Hong-Chang Chen
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Correspondence to Chun-Wei Liu.

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Liu, CW., Chen, HC. & Lin, SC. Acoustic Emission Monitoring of Grinding-Polishing of Extra-Low Dispersion Lens. Int. J. Precis. Eng. Manuf. 24, 53–60 (2023). https://doi.org/10.1007/s12541-022-00733-z

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