Manufacturing Technology 2023, 23(4):449-460 | DOI: 10.21062/mft.2023.062

Analysis of Cutting Forces with Application of the Discrete Wavelet Transform in Titanium Ti6Al4V Turning

Paweł Karolczak ORCID...
Wrocław University of Science and Technology, Faculty of Mechanical Engineering, wyb. Wyspiańskiego 27, 50-370 Wroclaw, Poland

The paper presents the possibilities of using the wavelet transform to filter the cutting force signal. Tests were carried out by dry turning on the Ti6Al4V alloy with variable cutting parameters. Four blades with different nose geometry and coatings were used. From the recorded waveforms, the mean values of the force component Fc and the load stability coefficient were calculated. The measured force waveforms were filtered with Daubechies 4 (db4) and Daubechies 6 (db6) wavelets. From the ratio of the load stabil-ity after filtration to the load stability before filtration, the noise and disturbance values generated during the turning of the tested alloy and the force measurement were estimated. The conducted research shows how the machining conditions affect the values of force, stability, and thus also the variability of the cutting edge load when turning a titanium alloy. They also show the effectiveness of the Discrete Wave-let Transform (DWT) in separating the noise from the force signal.

Keywords: Titanium alloys, Cutting forces, Wavelet analysis, Load stability, Measurement disturbances

Received: May 31, 2023; Revised: August 1, 2023; Accepted: August 15, 2023; Prepublished online: August 15, 2023; Published: September 5, 2023  Show citation

ACS AIP APA ASA Harvard Chicago IEEE ISO690 MLA NLM Turabian Vancouver
Karolczak P. Analysis of Cutting Forces with Application of the Discrete Wavelet Transform in Titanium Ti6Al4V Turning. Manufacturing Technology. 2023;23(4):449-460. doi: 10.21062/mft.2023.062.
Share...
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. ABBAS AT, SHARMA N, ANWAR S, LUQMAN M, TOMAZ I, HEGAB H. Multi-response optimization in high-speed machining of Ti-6Al-4V using TOPSIS-fuzzy integrated approach. Materials. 2020;13(5): 1104. https://doi.org/10.3390/ma13051104 Go to original source...
    2. MIERZEJEWSKA Ż, KUPTEL P, SIDUN J. Analysis of the surface condition of removed bone implants. Eksploatacja i Niezawodnosc - Maintenance and Reliability. 2016;18(1): 65-72. http://dx.doi.org/10.17531/ein.2016.1.9 Go to original source...
    3. HREN I, KUŚMIERCZAK S, HORKÝ R, MACH J. Analysis of the Effect of Heat Treatment and Corrosion Load on the Microstructure and Microhardness of the Ti6Al4V Alloy. Manufacturing Technology. 2022;22(4):414-422. doi: 10.21062/mft.2022.058. Go to original source...
    4. ROUDNICKA M, BAYER F, MICHALCOVA A, KUBASEK J, GHASSAN E, ALZUBI H, VOJTECH D. Biomedical titanium alloy prepared by additive manufacturing: Effect of processing on tribology. Manufacturing Technology 2020, 20(6):809-816 | DOI: 10.21062/mft.2020.112 Go to original source...
    5. VONAVKOVA I, VOJTECH D, PALOUSEK D. Characterization of β-Ti alloy prepared by SLM method. Manufacturing Technology. 2020;20(5):690-696. doi: 10.21062/mft.2020.091 Go to original source...
    6. PIMENOV DP, MIA M, GUPTA MK, MACHADO AR, TOMAZ IV, SARIKAYA M, WOJCIECHOWSKI S, MIKOŁAJCZYK T, KAPŁONEK W. Improvement of machinability of Ti and its alloys using cooling lubrication techniques: a review and future prospect. Journal of Materials Research and Technology. 2021:11: 719-753 https://doi.org/10.1016/j.jmrt.2021.01.031 . Go to original source...
    7. GRZESIK W, NIESŁONY P, HABRAT W. Investigation of the tribological performance of AlTiN coated cutting tools in the machining of Ti6Al4V titanium alloy in terms of demanded tool life. Eksploatacja i Niezawodnosc - Maintenance and Reliability. 2019:21(1): 153-158. http://dx.doi.org/10.17531/ein.2019.1.17 Go to original source...
    8. EZUGWU E, BONNEY J, YAMANE Y. An overview of the machinability of aeroengine alloys. Journal of Materials Processing Technology. 2003:134(2): 233-53. https://doi.org/10.1016/S0924-0136(02)01042-7. Go to original source...
    9. HABRAT W. Analiza i modelowanie toczenia wykończeniowego tytanu i jego stopów. Oficyna Wydawnicza Politechniki Rzeszowskiej. 2019. Rzeszów
    10. BHUI AS, SINGH G, SIDHU SS, BAINS PS. Experimental investigation of optimal ED machining parameters for Ti-6Al-4V biomaterial. Facta Universitatis Series: Mechanical Engineering. 2018:16(3): 337-345. https://doi.org/10.22190/FUME180824033B Go to original source...
    11. SINGH A, GHADAI RK, KALITA K, CHATTERJEE P, PAMUČAR D. EDM process parameter optimization for efficient machining of Inconel - 718. Facta Universitatis Series: Mechanical Engineering. 2020:18(3): 473-490 https://doi.org/10.22190/FUME200406035S Go to original source...
    12. MUTHUKRISHNAN N, DAVIM PJ. Influence of coolant in machinability of titanium alloy (Ti-6Al-4V). Journal of Surface Engineered Materials and Advanced Technology. 2011;1(1): 9-14. https://doi.org10.4236/jsemat.2011.11002. Go to original source...
    13. DEIAB I, RAZA SW, PERVAIZ S. Analysis of lubrication strategies for sustainable machining during turning of titanium Ti-6Al-4V alloy. Procedia CIRP. 2014;17: 766-771. Go to original source...
    14. GRGURAS D, STERLE L, PUSAVEC F. Cutting forces and chip morphology in LCO2 + MQL assisted robotic drilling of Ti6Al4V. Procedia CIRP. 2021;102: 299-302 Go to original source...
    15. GAURAV G, SHARMA A, DANGAYACH GS, MEENA ML. Assessment of jojoba as a pure and nano-fluid base oil in minimum quantity lubrication (MQL) hard-turning of Ti6Al4V: A step towards sustainable machining. Journal of Cleaner Production. 2020;272; 122553 https://doi.org/10.1016/j.jclepro.2020.122553 Go to original source...
    16. NI C, WANG X, ZHU L, LIU D, WANG Y, ZHENG Z, ZHANG P. Machining performance and wear mechanism of PVD TiAlN/AlCrN coated carbide tool in precision machining of selective laser melted Ti6Al4V alloys under dry and MQL conditions. Journal of Manufacturing Processes. 2022;79: 975-989 Go to original source...
    17. LIU H, AYED Y, BIREMBAUX H, ROSSI F, POULACHON G. Impacts of flank wear and cooling strategies on evolutions of built-up edges, diffusion wear and cutting forces in Ti6Al4V machining. Tribology International. 2022;171: 107537 Go to original source...
    18. GUO S, ZHENG H, LIU X, GU L. Comparison on Milling Force Model Prediction of New Cold Saw Blade Milling Cutter Based on Deep Neural Network and Regression Analysis. Manufacturing Technology. 2021;21(4):456-463. doi: 10.21062/mft.2021.053 Go to original source...
    19. TSAI MY, CHANG SY, HUNG JP, WANG CC. Investigation of milling cutting forces and cutting coefficient for aluminum 6060-T6. Computers and Electrical Engineering. 2016;51: 320-330. Go to original source...
    20. ZHAO Z, TO S, ZHU Z, YIN T. A theoretical and experimental investigation of cutting forces and spring back behaviour of Ti6Al4V alloy in ultraprecision machining of microgrooves. International Journal of Mechanical Sciences. 2020;169: 105315 Go to original source...
    21. YAMEOGO D, HADDAG B, MAKICH H, NOUARI M. Prediction of the cutting forces and chip morphology when machining the Ti6Al4V alloy using a microstructural coupled model. Procedia CIRP. 2017;58: 335 - 340. Go to original source...
    22. ZHU KP, WONG YS, HONG GS. Wavelet analysis of sensor signals for tool condition monitoring: a review and some new results. International Journal of Machine Tools and Manufacture. 2009;49(7-8): 537-553. Go to original source...
    23. FENG Z, LIANG M, CHU F. Recent advances in time-frequency analysis methods for machinery fault diagnosis: A review with application examples. Mechanical Systems and Signal Processing. 2013;38(1): 165-205. Go to original source...
    24. KRUEGER E, SCHEEREN EM, PACHECO RINALDIN CD, LAZZARETTI AE, NEVES EB, NOGUEIRA-NETO GN, NOHAMA P. Impact of skinfold thickness on wavelet-based mechanomyographic signal. Facta Universitatis Series: Mechanical Engineering. 2018;16(3): 359-368 https://doi.org/10.22190/FUME170602001K Go to original source...
    25. SHANBHAG VV, ROLFE BF, ARUNACHALAM N, PEREIRA MP. Investigating galling wear behaviour in sheet metal stamping using acoustic emissions. Wear. 2018;414-415: 31-42, https://doi.org/10.1016/j.wear.2018.07.003. Go to original source...
    26. GARCÍA PLAZA E, NÚÑEZ LÓPEZ PJ. Analysis of cutting force signals by wavelet packet transform for surface roughness monitoring in CNC turning. Mechanical Systems and Signal Processing. 2018;98: 634-651, https://doi.org/10.1016/j.ymssp.2017.05.006. Go to original source...
    27. LEE WK, RATNAM MM, AHMAD ZA. Detection of chipping in ceramic cutting inserts from workpiece profile during turning using fast Fourier transform (FFT) and continuous wavelet transform (CWT). Precision Engineering. 2017;47: 406-423 Go to original source...
    28. DUTTA S, PAL SK, SEN R. Progressive tool flank wear monitoring by applying discrete wavelet transform on turned surface images. Measurement. 2016;77: 388-401, https://doi.org/10.1016/j.measurement.2015.09.028. Go to original source...
    29. AHMED YS, ARIF AFM, VELDHUIS SC. Application of the wavelet transform to acoustic emission signals for built-up edge monitoring in stainless steel machining. Measurement. 2020;154: 1074-1078 https://doi.org/10.1016/j.measurement.2020.107478 Go to original source...
    30. TANGJITSITCHAROEN S, LOHASIRIWAT H. Intelligent monitoring and prediction of tool wear in CNC turning by utilizing wavelet transform. International Journal of Advanced Manufacturing Technologies. 2018;99(9): 2219-2230, https://doi.org/10.1007/s00170-017-1424-5. Go to original source...
    31. POUR M. Determining surface roughness of machining process types using a hybrid algorithm based on time series analysis and wavelet transform. International Journal of Advanced Manufacturing Technologies. 2018;97(9): 2603-2619, https://doi.org/10.1007/s00170-18-2070-2. Go to original source...
    32. ZAJAC J, MAKIEŁA W, STĘPIEŃ K, GOGOLEWSKI D. An Evaluation of Changeability of Parameters Describing Abbot Curve during a Wavelet Decomposition Process. Manufacturing Technology. 2014;14(4):665-671. doi: 10.21062/ujep/x.2014/a/1213-2489/MT/14/4/665. Go to original source...
    33. LI H, QIN X, HUANG T, LIU X, SUN D, JIN Y. Machining quality and cutting force signal analysis in UD-CFRP milling under different fiber orientation. International Journal of Advanced Manufacturing Technologies. 2018;98(9): 2377-2387. doi:10.1007/s00170-018-2312-3. Go to original source...
    34. GARCÍA PLAZA E, NÚŃEZ LÓPEZ PJ. Analysis of cutting force signals by wavelet packet transform for surface roughness monitoring in CNC turning. Mechanical Systems and Signal Processing. 2018;98: 634-651 doi:10.1016/j.ymssp.2017.05.006. Go to original source...
    35. PAHUJA R, MAMIDALA R. Quality monitoring in milling of unidirectional CFRP through wavelet packet transform of force signal. Procedia Manufacturing. 2020;48: 388-399 Go to original source...
    36. PAHUJA R, MAMIDALA R. Process monitoring in milling unidirectional composite laminates through wavelet analysis of force signals. Procedia Manufacturing. 2018;26: 645-655 doi:10.1016/j.promfg.2018.07.075. Go to original source...
    37. PAHUJA R, MAMIDALA R. Surface quality monitoring in abrasive water jet machining of Ti6Al4V-CFRP stacks through wavelet packet analysis of acoustic emission signals. International Journal of Advanced Manufacturing Technologies. 2019;104: 4091-4104. doi:10.1007/s00170-019-04177-0. Go to original source...
    38. CABRERA CG, ARAUJO AC, CASTELLO DA. On the wavelet analysis of cutting forces for chatter identification in milling. Advances in Manufacturing. 2017;5(2): 130-142. DOI 10.1007/s40436-017-0179-4 Go to original source...
    39. TANGJITSITCHAROEN S, LOHASIRIWAT H. Hybrid monitoring of chip formation and straightness in CNC turning by utilizing daubechies wavelet transform. Procedia Manufacturing. 2018;25: 279-286 Go to original source...
    40. KAROLCZAK P. Application of Discrete Wavelet Transform to analysis of cutting forces in turning of Composites based on aluminium alloys reinforced with Al2O3 fibres. FME Transactions. 2021;49: 563-574. https://doi.org/10.5937/fme2103563K Go to original source...
    41. CICHOSZ P. Narzędzia skrawające. 2006: WNT Warszawa

    This is an open access article distributed under the terms of the Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0), which permits non-comercial use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.


    Return to the content