Skip to main content
SpringerLink
Log in

Vibration analysis in milling titanium alloy based on signal processing of cutting force

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

In metal cutting processes, the chatter may cause fast wear of tools and poor surface quality of the processed parts; it can happen on different cutting parameters, but how do we identify the chatter and how do we select suitable cutting parameters to avoid chatter at high material removal rate (MRR). In this paper, the signal processing methods such as time domain, frequency domain, and time–frequency domain analysis are introduced. The signals of cutting force that were collected in milling titanium alloy Ti–6Al–4V at variable cutting speeds varied from 80 to 360 m/min; signal analysis methods such as time domain, frequency domain, and time–frequency domain were put forward. Further analysis results reveal that the chatter occur when cutting speeds are 240 and 360 m/min, when the maximum value of cutting forces increase by 61.9–66.8%, the standard deviation increase by 84.1–86.1%, and the surface roughness increase by 34.2–40.5% compared with that of at 80 m/min. Detail signal d2 is employed to monitor cutting stability state from the result of wavelet analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Duncan GS, Tummond MF, Schmitz TL (2005) An investigation of the dynamic absorber effect in high-speed machining. Int J Mach Tool Manuf 45:497–507

    Article  Google Scholar 

  2. López de Lacalle LN, Pérez-Bilbatua J, Sánchez JA, Llorente JI, Gutiérrez A, Albóniga J (2000) Using high pressure coolant in the drilling and turning of low machinability alloys. Int J Adv Manuf Technol 16:85–91

    Article  Google Scholar 

  3. Lopez de Lacalle LN, Perez J, Llorente JI, Sanchez JA (2000) Advanced cutting conditions for the milling of aeronautical alloys. J Mater Process Technol 100:1–11

    Article  Google Scholar 

  4. Ezugwu EO, Wang ZM (1997) Titanium alloys and their machinability—a review. J Mater Process Technol 68:262–274

    Article  Google Scholar 

  5. Sun S, Brandt M, Dargusch MS (2009) Characteristics of cutting forces and chip formation in machining of titanium alloys. Int J Mach Tool Manuf 49:561–568

    Article  Google Scholar 

  6. Basturk S, Senbabaoglu F (2010) Titanium machining with new plasma boronized cutting tools. CIRP Ann Manuf Technol 59:101–104

    Article  Google Scholar 

  7. Sun J, Guo YB (2009) Material flow stress and failure in multiscale machining titanium alloy Ti–6Al–4V. Int J Adv Manuf Technol 41:651–659

    Article  Google Scholar 

  8. Chen G, Ren CZ, Yang XY, Jin XM, Guo T (2011) Finite element simulation of high-speed machining of titanium alloy (Ti–6Al–4V) based on ductile failure model. Int J Adv Manuf Technol 56:1027–1038

    Article  Google Scholar 

  9. Rahman M, Wang ZG, Wong YS (2006) A review on high-speed machining of titanium alloys. Jpn Soc Mech Eng Intern J 49(1):11–20

    Google Scholar 

  10. Al-Zaharnah IT (2006) Suppressing vibrations of machining processes in both feed and radial directions using an optimal control strategy: the case of interrupted cutting. J Mater Process Technol 172:305–310

    Article  Google Scholar 

  11. Armando ISA, Anselmo ED, Robson P (2010) Vibration analysis of cutting force in titanium alloy milling. Int J Mach Tool Manuf 50:65–74

    Article  Google Scholar 

  12. Liao YS, Young YC (1996) A new on-line spindle speed regulation strategy for chatter control. Int J Mach Tool Manuf 36(5):651–660

    Article  Google Scholar 

  13. Lee BY, Tarng YS (1999) Milling cutter breakage detection by the discrete wavelet transform. Mechatronics 9:225–234

    Article  Google Scholar 

  14. Li XL, Guan XP (2004) Time-frequency-analysis-based minor cutting edge fracture detection during end milling. Mech Syst Signal Process 18:1485–1496

    Article  Google Scholar 

  15. Cao HR, Chen XF, Zi YY, Ding F, CheHX TJY, He ZJ (2008) End milling tool breakage detection using lifting scheme and Mahalanobis distance. Int J Mach Tool Manuf 48:141–151

    Article  Google Scholar 

  16. Kim JS, Kang MC, Ryu BJ, Ji YK (1999) Development of an on-line tool-life monitoring system using acoustic emission signals in gear shaping. Int J Mach Tool Manuf 39:1761–1777

    Article  Google Scholar 

  17. Huang PL, Li JF, Sun J, Song LY (2010) Vibration analysis in high speed machining titanium alloy with solid cemented carbide end mill. Mater Sci Eng Powder Metall 15:574–579

    Google Scholar 

  18. Huang PL, Li JF, Sun J, Ge MJ (2012) Milling force vibration analysis in high-speed-milling titanium alloy using variable pitch angle mill. Int J Adv Manuf Technol 58(1):153–160

    Article  Google Scholar 

  19. Yao ZH, Mei DQ, Chen ZC (2010) On-line chatter detection and identification based on wavelet and support vector machine. J Mater Process Technol 210:713–719

    Article  Google Scholar 

  20. Schmitz T, Medicus K, Dutterer B (2002) Exploring once-per-revolution audio signal variance as a chatter indicator. Mach Sci Technol 6:207–225

    Article  Google Scholar 

  21. Cao HR, Chen XF, Zi YY, Ding F (2008) End milling tool breakage detection using lifting scheme and Mahalanobis distance. Int J Mach Tool Manuf 48:141–151

    Article  Google Scholar 

  22. Li XL (2001) Detection of tool flute breakage in end milling using feed-motor current signatures. ASME Trans Mechatron 6:491–498

    Article  Google Scholar 

  23. Li WH, Gong WG (2005) A method of recognizing tool-wear states based on a fast algorithm of wavelet transform. J Mater Process Technol 170:374–380

    Article  Google Scholar 

  24. Zhu KP, Wong YS, Hong GS (2009) Wavelet analysis of sensor signals for tool condition monitoring: a review and some new results. Int J Mach Tool Manuf 49:537–553

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Mechanical Engineering, Shandong University, Jinan, 250061, China

    Panling Huang, Jianfeng Li, Jie Sun & Jun Zhou

  2. Key Laboratory of High Efficiency and Clean Mechanical Manufacture, Shandong University, Ministry of Education, Jinan, 250061, China

    Panling Huang, Jianfeng Li, Jie Sun & Jun Zhou

Authors
  1. Panling Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jianfeng Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jie Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jun Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jianfeng Li.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Huang, P., Li, J., Sun, J. et al. Vibration analysis in milling titanium alloy based on signal processing of cutting force. Int J Adv Manuf Technol 64, 613–621 (2013). https://doi.org/10.1007/s00170-012-4039-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-012-4039-x

Keywords

Search

Navigation