Skip to main content
SpringerLink
Log in

An accurate and robust method for the honing angle evaluation of cylinder liner surface using machine vision

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

Abstract

This paper presents a machine vision-based method for evaluating honing angle of cylinder liners by exploring the frequency domain characteristics of cylinder liner images. An image-processing algorithm based on Fourier transform and Hough transform is developed and applied on images containing the honing texture patterns captured from 14 cylinder liners manufactured with varying honing angles. The images are captured from cylinder liner surfaces by destructive and non-destructive manner using a charge-coupled device camera attached with magnifying lenses and a miniature microscopic probe respectively.A graphical user interface-based program and protractor-based manual method are used for verifying the accuracy and consistency of the developed image-processing algorithm for automatically evaluating the honing angle from the captured images of cylinder liner surfaces. The results clearly demonstrate the efficacy of the proposed method for robustly evaluating the honing angle and it can be used by the cylinder liner manufactures for fast and accurate measurement of honing angle with a resolution of 1°.

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

Access this article

Log in via an institution

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. Lee J, Malkin S (1993) Experimental investigation of the bore honing process. Trans ASME J Eng Ind 115(4):406–414. doi:10.1115/1.2901783

    Article  Google Scholar 

  2. Bolander NW, Sadeghi F (2007) Deterministic modeling of honed cylinder liner friction. Tribol T 50(2):248–256. doi:10.1080/10402000701309471

    Article  Google Scholar 

  3. Caciu C, Decencière E, Jeulin D (2008) Parametric optimization of periodic textured surfaces for friction reduction in combustion engines. Tribol T 51(4):533–541. doi:10.1080/10402000802065337

    Article  Google Scholar 

  4. Jocsak J, Le Y, Tian T, Wong VW (2006) Modeling and optimizing honing texture for reduced friction in internal combustion engine. SAE J Automot Eng. doi:10.4271/2006-01-0647, Paper No: 2006-01-0647

    Google Scholar 

  5. Geus D, Stibler M (2008) Industrial application of advanced measuring and evaluation methods for cylinder liners of engine blocks. Meas Sci Technol 19(6):064004. doi:10.1088/0957-0233/19/6/064004

    Article  Google Scholar 

  6. Mark CM (2000) The value of a measurement is in the application of its result. http://www.digitalmetrology.com/Papers/SME2000Abstract.PDF.Accessed 30 June 2010

  7. Leon FP (2002) Evaluation of honed cylinder bores. CIRP Annals Manuf Techn 51(1):503–506. doi:10.1016/S0007-8506(07)61571-6

    Article  Google Scholar 

  8. Weidner A, Seewig J, Reithmeier E (2006) 3D roughness evaluation of cylinder liner surfaces based on structure-oriented parameters. Meas Sci Technol 17(3):477–482. doi:10.1088/0957-0233/17/3/S03

    Article  Google Scholar 

  9. Dimkovski Z, Anderberg C, Ohlsson R, Rosén BG (2010) Characterization of worn cylinder liner surfaces by segmentation of honing and wear scratches. Wear. doi:10.1016/j.wear.2010.04.024

    Google Scholar 

  10. Beyerer J (1995) Model-based analysis of groove textures with applications to automated inspection of machined surfaces. Measurement 15(3):189–199. doi:10.1016/02632241(95)00003-4

    Article  Google Scholar 

  11. Thomas TR, Rosén BG, Zahouani H, Blunt L, Mansori ME (2010) Traceology, quantifying finishing machining and function: a tool and wear mark characterization study. Wear. doi:10.1016/j.wear.2010.04.025

    Google Scholar 

  12. Sotoudeh N, Greatrix GR, Pasad R, Goldspink GF (1992) Fourier domain compression techniques in resolving spatial characteristics of surface. International Conference on Image Processing and its Application, Maastricht, 7–9 Apr 1992. IEEE Conference Publication, pp 172–175

  13. Tsai DM, Huang TY (2003) Automated surface inspection for statistical textures. Image Vis Comput 21(4):307–323. doi:10.1016/S0262-8856(03)00007-6

    Article  Google Scholar 

  14. Beyerer J, Leon FP (1998) Adaptive separation of random lines and background. Opt Eng 37(10):2733–2741. doi:10.1117/1.601811

    Article  Google Scholar 

  15. Tsai DM, Hsieh CY (1999) Automated surface inspection for directional textures. Image Vis Comput 18(1):49–62. doi:10.1016/S0262-8856(99)00009-8

    Article  Google Scholar 

  16. Duda RO, Hart PE (1972) Use of the Hough transformation to detect lines and curves in pictures. Commun ACM 15(1):11–15

    Article  Google Scholar 

  17. Gonzalez RC, Woods RE, Eddins LS (2004) Digital image processing using MATLAB. Pearson Education, New Delhi

    Google Scholar 

  18. MATLAB (2009) Image processing Toolbox 6-User’s Guide http://www.mathworks.com/access/helpdesk/help/pdf_doc/images/images_tb.pdf .Accessed 30 June 2010

Download references

Author information

Authors and Affiliations

  1. Manufacturing Engineering Section, Department of Mechanical Engineering, Indian Institute of Technology, Madras, Chennai, India

    Deepak Lawrence.K & Balakrishnan Ramamoorthy

Authors
  1. Deepak Lawrence.K
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Balakrishnan Ramamoorthy
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Balakrishnan Ramamoorthy.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lawrence.K, D., Ramamoorthy, B. An accurate and robust method for the honing angle evaluation of cylinder liner surface using machine vision. Int J Adv Manuf Technol 55, 611–621 (2011). https://doi.org/10.1007/s00170-010-3061-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-010-3061-0

Keywords

Search

Navigation