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EFFECTS OF CUTTING PARAMETERS ON ACOUSTIC FREQUENCY CREATED IN MACHINING OF COLD WORK TOOL STEELS

Yıl 2018, Cilt: 5 Sayı: 2, 65 - 78, 29.06.2018

Hüseyin Polat Muammer Nalbant Hasan Basri Ulaş

Öz



The objective of this study is to
investigate the effects of machining parameters on the acoustic frequency
developed during the machining of cold work tool steels. The machining tests
were carried out through a milling method with different machining parameters.
Analogue acoustic signals obtained via the microphone were converted and
digitized. During idle operation and cutting operation, the obtained spindle
sound recordings were subjected to Fast Fourier Transform (FFT) and converted
from the time domain to the frequency domain, and the statistical effects of
cutting parameters were investigated by use of analysis of variance. Cutting
speed was found to be the only influential factor for the acoustic frequency in
idle time. In the starting of machining, the feed rate, cutting speed, and
depth of cut were seen to affect the acoustic frequency, while the cutting
speed, insert material, insert radius, depth of cut, and feed rate were seen to
be effective in the later stages of machining.




Anahtar Kelimeler

Acoustic Frequency Fast Fourier Transform Cold work tool steel

Kaynakça

  • [1] Cook PR., Sound Production and Modeling, IEEE Computer Graphics and Application, 22, 23-27, (2002).
  • [2] Li X., “A brief review: acoustic emission method for tool wears monitoring during turning”, Int. J. of Machine Tools & Manufacture, 42, 157–165, (2002).
  • [3] Dimla E, Snr. Dimla, “Sensor signals for tool-wear monitoring in metal cutting operations—a review of methods”, Int. J. of Machine Tools & Manufacture, 40, 1073–1098, (2000). [4] Liang S. and D. Dornfeld, “Tool wear detection using time series analysis of acoustic emission”, J. of Engineering for Industry Transactions of the ASME Series B, 111, 199–205, (1989). [5] Li X. and Z. Yuan, “Tool wear monitoring with wavelet packet transform-fuzzy clustering method”, Wear , 219, 145–154, (1998).
  • [6] Tekiner Z and S. Yeşilyurt, “Investigation of the cutting parameters depending on process sound during turning of AISI 304 austenitic stainless steel”, Materials & Design, 25, 507–513 (2004).
  • [7] Ravindra, H.V., Srinivasa Y.G., Krishnamurthy R., “Acoustic emission for tool condition monitoring in metal cutting”, Wear, 212, 78-84 (1997).
  • [8] Srinivasa P., Nagabhushana T. N., Rao RBKN., “Tool condition monitoring using acoustic emission, surface roughness and growing cell structures neural network”, Machining Science and Technology, 16, 653–676 (2012).
  • [9] Du R., “Signal understanding and tool condition monitoring”, Engineering Applications of Artificial Intelligence, 12, 585-597 (1999).
  • [10] Mathew MT., Srinivasa P., Rocha LA., “An effective sensor for tool wear monitoring in face milling: Acoustic emission”, Sadhana, 33, 227–233, (2008).
  • [11] Bhuiyann MSH., Choudhury IA., Nukman Y., “An innovative approach to monitor the chip formation effect on tool state using acoustic emission in turning”, Int. J. of Machine Tools and Manufacture, 58, 19–28, (2012). [12] Gokkaya H and Nalbant M., “The effects of cutting tool geometry and processing parameters on the surface roughness of AISI 1030 steel”, Materials & Design; 28, 717-721, (2007).
  • [13] Kaplan Y., “Effects of different parameters on cutting force, torque, vibration, surface roughness, tool wear and exit burrs in drilling”, MSc. Thesis, Gazi University Institute of Science and Technology, Ankara, 24-26, (2010)
  • [14] Kaplan Y., Nalbant M., Gökkaya H., “The experimental investigation of the effect of machining parameters on burr formation in drilling of AISI D2 and AISI D3 cold work steels”, Karaelmas Sci Eng J, 1:37–46, (2011)
  • [15] Kaplan Y., Motorcu AR., Nalbant M., Okay Ş., “The effects of process parameters on acceleration amplitude in the drilling of cold work tool steels”, International Journal of Advanced Manufacturing Technology, 80:1387–1401, (2015). [16] Nalbant, M. and Yildiz Y., “Effect of cryogenic cooling in milling process of AISI 304 stainless steel”, Transactions of Nonferrous Metals Society of China, 21(1), 72-79, (2011).
  • [17] Nalbant M., Altin A., Gokkaya H., “The effect of coating material and geometry of cutting tool and cutting speed on machinability properties of Inconel 718 super alloys”, Materials and Design, 28(5), 1719-1724, (2007).
  • [18] Ciftci I., Turker M., Seker U., “Evaluation of tool wear when machining SiCp-reinforced Al-2014 alloy matrix composites”, Materials & Design, 25, 251-255, (2004).
  • [19] Seker U. and Hasirci H., “Evaluation of machinability of austempered ductile irons in terms of cutting forces and surface quality”, J. of Materials Processing Technology, 173, 260-268, (2006).
  • [20] Choudhury IA., Lee CY., Bhuiyan MSH., Nukman Y., “Tool condition monitoring using AE signal in turning of assab-705 steel”, Conference on Manufacturing Technology and Management World Engineering Congress, Kuching, Sarawak, Malaysia, (2010).

Yıl 2018, Cilt: 5 Sayı: 2, 65 - 78, 29.06.2018

Hüseyin Polat Muammer Nalbant Hasan Basri Ulaş

Öz

Kaynakça

  • [1] Cook PR., Sound Production and Modeling, IEEE Computer Graphics and Application, 22, 23-27, (2002).
  • [2] Li X., “A brief review: acoustic emission method for tool wears monitoring during turning”, Int. J. of Machine Tools & Manufacture, 42, 157–165, (2002).
  • [3] Dimla E, Snr. Dimla, “Sensor signals for tool-wear monitoring in metal cutting operations—a review of methods”, Int. J. of Machine Tools & Manufacture, 40, 1073–1098, (2000). [4] Liang S. and D. Dornfeld, “Tool wear detection using time series analysis of acoustic emission”, J. of Engineering for Industry Transactions of the ASME Series B, 111, 199–205, (1989). [5] Li X. and Z. Yuan, “Tool wear monitoring with wavelet packet transform-fuzzy clustering method”, Wear , 219, 145–154, (1998).
  • [6] Tekiner Z and S. Yeşilyurt, “Investigation of the cutting parameters depending on process sound during turning of AISI 304 austenitic stainless steel”, Materials & Design, 25, 507–513 (2004).
  • [7] Ravindra, H.V., Srinivasa Y.G., Krishnamurthy R., “Acoustic emission for tool condition monitoring in metal cutting”, Wear, 212, 78-84 (1997).
  • [8] Srinivasa P., Nagabhushana T. N., Rao RBKN., “Tool condition monitoring using acoustic emission, surface roughness and growing cell structures neural network”, Machining Science and Technology, 16, 653–676 (2012).
  • [9] Du R., “Signal understanding and tool condition monitoring”, Engineering Applications of Artificial Intelligence, 12, 585-597 (1999).
  • [10] Mathew MT., Srinivasa P., Rocha LA., “An effective sensor for tool wear monitoring in face milling: Acoustic emission”, Sadhana, 33, 227–233, (2008).
  • [11] Bhuiyann MSH., Choudhury IA., Nukman Y., “An innovative approach to monitor the chip formation effect on tool state using acoustic emission in turning”, Int. J. of Machine Tools and Manufacture, 58, 19–28, (2012). [12] Gokkaya H and Nalbant M., “The effects of cutting tool geometry and processing parameters on the surface roughness of AISI 1030 steel”, Materials & Design; 28, 717-721, (2007).
  • [13] Kaplan Y., “Effects of different parameters on cutting force, torque, vibration, surface roughness, tool wear and exit burrs in drilling”, MSc. Thesis, Gazi University Institute of Science and Technology, Ankara, 24-26, (2010)
  • [14] Kaplan Y., Nalbant M., Gökkaya H., “The experimental investigation of the effect of machining parameters on burr formation in drilling of AISI D2 and AISI D3 cold work steels”, Karaelmas Sci Eng J, 1:37–46, (2011)
  • [15] Kaplan Y., Motorcu AR., Nalbant M., Okay Ş., “The effects of process parameters on acceleration amplitude in the drilling of cold work tool steels”, International Journal of Advanced Manufacturing Technology, 80:1387–1401, (2015). [16] Nalbant, M. and Yildiz Y., “Effect of cryogenic cooling in milling process of AISI 304 stainless steel”, Transactions of Nonferrous Metals Society of China, 21(1), 72-79, (2011).
  • [17] Nalbant M., Altin A., Gokkaya H., “The effect of coating material and geometry of cutting tool and cutting speed on machinability properties of Inconel 718 super alloys”, Materials and Design, 28(5), 1719-1724, (2007).
  • [18] Ciftci I., Turker M., Seker U., “Evaluation of tool wear when machining SiCp-reinforced Al-2014 alloy matrix composites”, Materials & Design, 25, 251-255, (2004).
  • [19] Seker U. and Hasirci H., “Evaluation of machinability of austempered ductile irons in terms of cutting forces and surface quality”, J. of Materials Processing Technology, 173, 260-268, (2006).
  • [20] Choudhury IA., Lee CY., Bhuiyan MSH., Nukman Y., “Tool condition monitoring using AE signal in turning of assab-705 steel”, Conference on Manufacturing Technology and Management World Engineering Congress, Kuching, Sarawak, Malaysia, (2010).
Toplam 16 adet kaynakça vardır.

Ayrıntılar

Bölüm Bilgisayar Mühendisliği
Yazarlar

Hüseyin Polat 0000-0003-4128-2625

Muammer Nalbant

Hasan Basri Ulaş

Yayımlanma Tarihi 29 Haziran 2018
Gönderilme Tarihi 4 Ekim 2017
Yayımlandığı Sayı Yıl 2018 Cilt: 5 Sayı: 2

Kaynak Göster

APA Polat, H., Nalbant, M., & Ulaş, H. B. (2018). EFFECTS OF CUTTING PARAMETERS ON ACOUSTIC FREQUENCY CREATED IN MACHINING OF COLD WORK TOOL STEELS. Gazi University Journal of Science Part A: Engineering and Innovation, 5(2), 65-78.