Experimental investigation of correlation between attrition wear and features of acoustic emission signals in single-grit grinding

ORIGINAL ARTICLE
  • 70 Downloads

Abstract

The cutting performance of grit is controlled by its shape and geometric parameters. However, the geometry changes with the progression of attrition wear, thereby increasing grinding temperature, grinding force and decreasing grinding efficiency. It is important to monitor the cutting condition of grit to confirm its state of wear. Acoustic emission (AE) signals have been widely used in monitoring cutting tool conditions and have been proven effective in detecting tool wear and failure. To identify the correlation between attrition wear and AE features, comparison tests were carried out with a pair of sharp and blunt grits scratching on hardened AISI4340 workpiece and the AE signals during the scratching process were obtained. The signals were analyzed in the time, frequency, and time-frequency domain The numbers of AE counts in the time domain differed for the sharp and blunt grits. It is also found that the proportions of AE energy in the frequency band of 0–90 kHz and 90–250 kHz differed was attributed to differences in strength of the various AE sources. The AE energy was further analyzed in time-frequency domain using discredit wavelet transform (DWT). The AE energy at certain decomposition level was extracted. A validation test was carried out with a worn grit. It was suggested that features associated with AE energy are appropriate for detecting attrition wear of grit, but the number of AE counts fluctuated owing to the complex friction behavior of the worn surfaces. The results of AE energy distribution in the time-frequency domain reveal that the amplitude of the AE energy deteriorates more rapidly when the grit is worn.

Keywords

Single grit grinding Attrition wear AE energy Frequency band 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgements

The authors would like to thank the National Nature and Science foundation of China (Grant Nos. 51675481) and Shanghai sailing program (17YF1407600).

References

  1. 1.
    Aurich JC, Herzenstiel P, Sudermann H (2008) High-performance dry grinding using a grinding wheel with a defined grain pattern. Ann CIRP 57(2):666–696Google Scholar
  2. 2.
    Butler-Smith PW, Axinte DA, Daine M (2009) Preferentially oriented diamond micro-arrays: a laser patterning technique and preliminary evaluation of their cutting forces and wear characteristics. Int J Mach Tools Manuf 49:1175–1184CrossRefGoogle Scholar
  3. 3.
    Axinte DA, Butler-Smith PW, Akgun C, Kolluru K (2013) On the influence of single grit micro-geometry on grinding behavior of ductile and brittle materials. Int J Mach Tools Manuf 74:12–18CrossRefGoogle Scholar
  4. 4.
    Butler-Smith PW, Axinte DA, Daine M (2011) Ordered diamond micro-arrays for ultra-precision grinding—an evaluation in Ti–6AL–4V. Int J Mach Tools Manuf 51(1):54–66CrossRefGoogle Scholar
  5. 5.
    Pacella M, Axinte DA, Butler-Smith PW, Shipway P, Daine M, Wort C (2015) An assessment of the wear characteristics of micro-cutting arrays produced from polycrystalline diamond and cubic boron nitride composites. J Manuf Sci Eng 138(2):021001–1– 021001-16CrossRefGoogle Scholar
  6. 6.
    Anderson D, Warkentin A, Bauer R (2011) Experimental and numerical investigations of single abrasive-grain cutting. Int J Mach Tools Manuf 51:898–910CrossRefGoogle Scholar
  7. 7.
    Mei Y M, Yu ZH, Yang ZS (2017) Numerical investigation of the evolution of grit fracture and its impact on cutting performance in single grit grinding. Int J Adv Manuf Technol 89(9–12):3271–3284Google Scholar
  8. 8.
    Anderson D, Warkentin A, Bauer R (2012) Comparison of spherical and truncated cone geometries for single abarasive-grain cutting. J Mater Process Technol 212:1946–1953CrossRefGoogle Scholar
  9. 9.
    Wu HY, Huang H, Jiang F, Xu XP (2016) Mechanical wear of different crystallographic orientations for single abrasive diamond scratching on Ta12W. Int J Refract Met Hard Mater 54:260–269CrossRefGoogle Scholar
  10. 10.
    Fujimoto M, Ichida Y (2008) Micro fracture behavior of cutting edges in grinding using single crystal cBN grains. Diam Relat Mater 17:1759–1763CrossRefGoogle Scholar
  11. 11.
    Ding WF, Xu JH, Chen ZZ, Su HH, Fu YC (2010) Grain wear of brazed polycrystalline CBN abrasive tools during constant-force grinding Ti-6Al-4V alloy. Int J Adv Manuf Technol 52:9–12Google Scholar
  12. 12.
    Ding WF, Xu JH, Chen ZZ, Su HH, Fu YC (2010) Wear behavior and mechanism of single-layer brazed CBN abrasive wheels during creep-feed grinding cast nickel-based superalloy. Int J Adv Manuf Technol 51:541–550CrossRefGoogle Scholar
  13. 13.
    Dai CW, Ding WF, Xu JH, Fu YC, Yu TY (2017) Influence of grain wear on material removal behavior during grinding nickel-based superalloy with a single diamond grain. Int J Mach Tools Manuf 113:49–58CrossRefGoogle Scholar
  14. 14.
    Shi Z, Malkin S (2006) Wear of electroplated CBN grinding wheels. J Manuf Sci Eng 128:110–118CrossRefGoogle Scholar
  15. 15.
    Malkin S, Cook NH (1971) The wear of grinding wheels: Part 1–attritios wear. J Eng Ind 93:1120–1128CrossRefGoogle Scholar
  16. 16.
    Luis HA, Alexandre MA, Wander LV, Wisley FS, Alisson RM (2015) A new approach for detection of wear mechanisms and determination of tool life in turning using acoustic emission. Tribol Int 92:519–532CrossRefGoogle Scholar
  17. 17.
    Nešlusan M, Mičieta B, Mičietova A, Čillikova M, Mrkvica I (2015) Detection of tool breakage during hard turning through acoustic emission at low removal rates. Measurement 70:1–13CrossRefGoogle Scholar
  18. 18.
    Moia DFG, Thomazella IH, Aguiar PR, Bianchi EC, Martins CHR, Marchi M (2014) Tool condition monitoring of aluminum oxide grinding wheel in dressing operation using acoustic emission and neural networks. J Braz Soc Mech Sci Eng 37:627–640CrossRefGoogle Scholar
  19. 19.
    Alan H, Hiroshi M, Masaki W (2012) Correlation between features of acoustic emission signals and mechanical wear mechanisms. Wear 292–293:144–150Google Scholar
  20. 20.
    Alan H, Masaki W, Hiroshi M (2008) The relationship between acoustic emissions and wear particles for repeated dry rubbing. Wear 265:831–839CrossRefGoogle Scholar
  21. 21.
    Rubtsov VE, Kolubaev EA, Kolubaev AV, Popov VL (2013) Using acoustic emission for the analysis of wear processes during sliding friction. Tech Phys Lett 39:223–225CrossRefGoogle Scholar
  22. 22.
    Griffin JM, Torres F (2015) Dynamic precision control in single-grit scratch tests using acoustic emission signals. Int J Adv Manuf Technol 81:935–953CrossRefGoogle Scholar
  23. 23.
    James G, Chen X (2014) Real-time fuzzy-clustering and CART rules classification of the characteristics of emitted acoustic emission during horizontal single-grit scratch tests. Int J Adv Manuf Technol 74:481–502CrossRefGoogle Scholar
  24. 24.
    Griffin J, Chen X (2009) Characteristics of the acoustic emission during horizontal single grit scratch tests: Part 1 characteristics and identification. Int J Abras Technol 2(1):25–42CrossRefGoogle Scholar
  25. 25.
    Torres F, Griffin J (2015) Control with micro precision in abrasive machining through the use of acoustic emission signals. Int J Precis Eng Manuf 16:441–449CrossRefGoogle Scholar
  26. 26.
    Yang ZS, Yu ZH (2011) Grinding wheel wear monitoring based on wavelet analysis and support vector machine. Int J Adv Manuf Technol 62:107–121CrossRefGoogle Scholar
  27. 27.
    Tahsin TÖ, Xun C (2011) Process monitoring and metrology for single grit grinding test performance. In: Proceedings of the 17th international conference on automation and computing. University of Huddersfield, Huddersfield, UK p 143–148Google Scholar
  28. 28.
    Baccar D, Söffker D (2015) Wear detection by means of wavelet-based acoustic emission analysis. Mech Syst Signal Process 60-61:198–207CrossRefGoogle Scholar
  29. 29.
    Pawade RS, Joshi SS (2011) Analysis of acoustic emission signals and surface integrity in the high-speed turning of Inconel 718. Proc Inst Mech Eng B J Eng Manuf 226:3–27CrossRefGoogle Scholar
  30. 30.
    Ahn BW, Lee SH (2009) Characterization and acoustic emission monitoring of AFM nanomachining. J Micromech Microeng 19(4):045028Google Scholar
  31. 31.
    Teti R, Dorndeld D (1989) Modeling and experimental analysis of acoutic emission from metal cutting. J Eng Ind 111(3):229– 237CrossRefGoogle Scholar
  32. 32.
    Devi LN, Rychev SV (2016) An experimental study of the influence of tool material and fine turning conditions on the level of acoustic emission signals. J Superhard Mater 38:51–57CrossRefGoogle Scholar
  33. 33.
    Ferrer C, Salas F, Pascual M, Orozco J (2010) Discrete acoustic emission waves during stick-slip friction between steel samples. Tribol Int 43:1–6CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Ltd. 2017

Authors and Affiliations

  1. 1.The State Key Laboratory of Fluid Power Transmission and Control, College of Mechanical EngineeringZhejiang UniversityHangzhouPeople’s Republic of China
  2. 2.Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, College of Mechanical EngineeringZhejiang UniversityHangzhouPeople’s Republic of China
  3. 3.School of Logistics EngineeringShanghai Maritime UniversityShanghaiPeople’s Republic of China

Personalised recommendations