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A new digital measurement method for accurate curve grinding process

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Abstract

In this paper, an online measurement and error compensation system for curve grinding based on pattern recognition was presented and verified by experiments. The measurement system organization and its principle of operation were introduced in detail. The work piece and grinding wheel image were sampled at certain positions to avoid spark influence. In order to increase system resolution, images were sampled only at local areas of the work piece and grinding wheel. A discrimination technology based on a circular tolerance zone was proposed which can solve the problem of local image edge comparison. For image de-noising, a local threshold algorithm was applied to determine new wavelet coefficients. Furthermore, a two-step edge detection method was used to realize sub-pixel precision. Finally, a series of experiments were carried out to examine the detection precision of the image measurement system and its influencing factors. From experiments, it can be said that the proposed method in this paper is effective, and its detection precision is much better than traditional methods.

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References

  1. 1.

    Fan KC, Lee MZ, Mou JI (2002) On-line non-contact system for grinding wheel wear measurement. Int J Adv Manuf Technol 19:14–22

  2. 2.

    Tonshoff HK, Friemuth T, Becker JC (2002) Process monitoring in grinding. Ann CIRP 51(2):551–571

  3. 3.

    Kim H, Kim SR, Ahn JH (2001) Process monitoring of center less grinding using acoustic emission. J Mater Process Technol 111:(1–3)273–278

  4. 4.

    Wang Z, Willett P, Deaguiar PR (2001) Neural network detection of grinding burn from acoustic emission. J Mach Tools Manuf 41(2):283–309

  5. 5.

    Pawel K (2001) An intelligent system for grinding wheel condition monitoring. J Mater Process Technol 109(3):258–263

  6. 6.

    Furutani K, Hieu NT, Ohguro N, Nakamura T (2003) Automatic compensation for grinding wheel wear by pressure based in-process measurement in wet grinding. Precis Eng 27:9–13

  7. 7.

    Chang M, Liu KH (1999) Non-contact scanning measurement utilizing a space mapping method. Opt Lasers Eng 30:503–512

  8. 8.

    Mallat S, Zhong S (1992) Characterization of signals from multi-scale edges. IEEE T Pattern Anal 14(7):710–732

  9. 9.

    Donoho DL (1995) De-noising by soft-threshold. IEEE T Inform Theory 41(3)613–627

  10. 10.

    Chang SG, Yu B, Vetterli M (2000) Adaptive wavelet thresholding for image de-noising and compression. IEEE T Image Process 9(9):1532–1546

  11. 11.

    Lyvers EP, Mitchell OR (1989) Sub-pixel measurements using a moment based edge operator. IEEE T Pattern Anal 11(12):1293–1309

  12. 12.

    Zhang Y, Hu D, Xu J (2004) Subpixel edge location of machine parts based on the vision images. Chi Hsieh Kung Ch’eng Hsueh Pao 40(6):179–182 (in Chinese)

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Author information

Correspondence to Yong-hong Zhang.

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Zhang, Y., Wang, L., Ma, C. et al. A new digital measurement method for accurate curve grinding process. Int J Adv Manuf Technol 36, 305–314 (2008). https://doi.org/10.1007/s00170-006-0844-4

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Keywords

  • Curve grinding
  • Pattern recognition
  • Circular tolerance zone
  • Error compensation