MUTUAL CHANGE OF ACOUSTIC EMISSION STATISTICAL ENERGY PARAMETERS AT TREATING TOOL WEAR

S. F. Filonenko, A. P. Stakhova

Abstract


The results of experimental studies of acoustic radiation energy during processing tool wear are considered. The regularities of acoustic emission signal statistical energy parameters changes at normal and catastrophic processing tool wear are determined. It is revealed that the regularities of change in the statistical energetic parameters of acoustic emission signals do not observe a characteristic features of the change which are associated with the appearance of a certain type of tool wear. The regularities of experimental acoustic emission signal statistical energy parameters mutual change during normal and catastrophic processing tool wear are determined. It is shown that the ratio of the acoustic emission signal average energy level to the average energy level standard deviation at a given analysis interval is a sensing parameters to the mechanisms and stages of cutting tool wear during materials machining.


Keywords


Аcoustic emission; acoustic radiation energy; machining; statistical energy parameters; tool wear

References


P. Kovač, I. Mankova, M. Gostimirović, M. Sekulić, and B. Savković, “A review of machining monitoring systems,” Journal of production engineering, vol. 14, no. 1, pp. 1–6, 2011.

P. Stavropoulosa, D. Chantzisa, C. Doukasa, A. Papacharalampopoulosa, and G. Chryssolouris, “Monitoring and control of manufacturing processes: A review,” Procedia CIRP, vol. 8, pp. 421–425, 2013. https://doi.org/10.1016/j.procir.2013.06.127.

A. Rai, and S. K. Ganguly, “Monitoring and Control of Machining Process: A Review,” Research Journal of Engineering, vol. 5(5), pp. 31–36.

T. Wijaya, W. Caesarendra, T. Tjahjowidodo, B. K. Pappachan, A. Wee, and M. I Roslan, “A Review on Sensors for Real-time Monitoring and Control Systems on Machining and Surface Finishing Processes,” MATEC Web of Conferences, vol. 159, no. 02034, 2018, 6 p. https://doi.org/10.1051/matecconf/201815902011

M. Hassan, A. Sadek, M. H. Attia, and V. Thomson, “Intelligent machining: real-time tool condition monitoring and intelligent adaptive control systems,” Journal of Machine Engineering, vol. 18, no. 1, pp. 5–17, 2018. https://doi.org/10.5604/01.3001.0010.8811

C. K. Mukhopadhyay, T. Jayakumar, B. Raj, and S. Venugopal, “Statistical Analysis of Acoustic Emission Signals Generated During Turning of a Metal Matrix Composite,” J. of the Braz. Soc. of Mech. Sci. and Eng., vol. 34, no. 2, pp. 145–154, 2012. https://doi.org/10.1590/S1678-58782012000200006

D. A. Fadare, W. F. Sales, J. Bonney, and E. O. Ezugwu, “Influence of cutting parameters and tool wear on acoustic emission signal in high-speed turning of Ti-6Al-4V alloy”, Journal of Emerging Trends in Engineering and Applied Sciences, vol. 3, no. 3, pp. 547–555, 2012.

O. A. Olufayo and K. Abou-El-Hossein, “Acoustic Emission Monitoring in Ultra-High Precision Machining of Rapidly Solidified Aluminium,” Proceedings International Conference on Competitive Manufacturing (Coma ’13, 30 January–1 February 2013, Stellenbosch, South Africa), 2013, pp. 307–312.

Y. Wei, Q. An, X. Cai, M. Chen, and W. Ming, “Influence of Fiber Orientation on Single-Point Cutting Fracture Behavior of Carbon-Fiber/Epoxy Prepreg Sheets,” Materials, no. 8, 2015, pp. 6738–6751. https://doi.org/10.3390/ma8105336

N. Mokhtar, I. Y. Ismail, M. Asmelash, H. Zohari, and A. Azhari, “Analysis of acoustic emission on surface roughness during end milling,” ARPN Journal of Engineering and Applied Sciences, vol. 12, no. 4, pp. 1324–1328, 2017.

S. J. Ha, B. C. Shin, M. W. Cho, K. J. Lee, and W. S. Cho, “High speed end-milling characteristics of pre-sintered Al2O3/Y-TZP ceramic composites for dental applications,” Journal of the Ceramic Society of Japan, vol. 118, no. 11, pp. 1053–1056, 2010. https://doi.org/10.2109/jcersj2.118.1053

P. Kulandaivelu, P. S. Kumar, and S. Sundaram, “Wear monitoring of single point cutting tool using acoustic emission techniques,” Sādhanā, vol. 38, Part 2, pp. 211–234, 2013. https://doi.org/10.1007/s12046-013-0130-8

G. Vetrichelvan, S. Sundaram, S. S. Kumaran, P. Velmurugan, “An investigation of tool wear using acoustic emission and genetic algorithm,” Journal of Vibration and Control, vol. 21, no. 15, pp. 3061–3066, 2015. https://doi.org/10.1177/1077546314520835

X. Rimpault, J. F. Chatelain, J. E. Klemberg-Sapieha, M. Balazinski, “Fractal analysis of cutting force and acoustic emission signals during CFRP machining,” Procedia CIRP, vol. 46, pp. 143–146, 2016. https://doi.org/10.1016/j.procir.2016.03.171

D. Kong, Y. Chen, N. Li, and S. Tan, “Tool wear monitoring based on kernel principal component analysis and v-support vector regression, The International Journal of Advanced Manufacturing Technology, vol. 89, no. 1–4, pp. 175–190, 2017. https://doi.org/10.1007/s00170-016-9070-x

A. Caggiano, “Tool Wear Prediction in Ti-6Al-4V Machining through Multiple Sensor Monitoring and PCA Features Pattern Recognition,” Sensors, vol. 18, no. 823, 14 p. https://doi.org/10.3390/s18030823

S. F. Filonenko, “The effect of wear of a cutting tool with a controlled depth of cut on the acoustic emission,” Eastern European Journal of Enterprise Technologies, vol. 6, no. 9, pp. 47–50, 2015. https://doi.org/10.15587/1729-4061.2015.56871

S. F. Filonenko, “Acoustic energy at controlled cutting depth of composite material,” Electronics and Control Systems, no. 3(49), pp. 93–99, 2016. https://doi.org/10.18372/1990-5548.49.11244

S. Filonenko, “Acoustic emission at treating tool wear with a not controlled cutting depth,” Proceedings of the National Aviation University, no. 1(70), 2017, pp. 90–97. https://doi.org/10.18372/2306-1472.70.11426

S. Filonenko, “Acoustic emission energy parameters at composite tool wear with a not controlled cutting depth,” Technical science and technologies, no. 1(7), pp. 24–32, 2017. https://doi.org/10.25140/2411-5363-2017-1(7)-24-32


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