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

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°.