Some Studies on Measurement of Worn Surface by Digital Image Processing

Abstract

Digital image processing (DIP) becomes a common tool for analyzing engineering problems by fast, frequent and noncontact method of identification and measurement. An attempt has been made in the present investigation to use this method for automatically detecting the worn regions on the material surface and also its measurement. Brass material has been used for experimentation as it is used generally as a bearing material. A pin on disc dry sliding wear testing machine has been used for conducting the experiments by applying loads from 10 N to 50 N and by keeping sliding distance and sliding speed constant. After testing, images are acquired by using 1/2 inch interline transfer CCD image sensor with 795(H)[Formula: see text]896(V) spatial resolution of 8.6[Formula: see text][Formula: see text]m (H)[Formula: see text]8.3[Formula: see text][Formula: see text]m (V) unit cell. Denoising has been done to remove any possible noise followed by contrast stretching to enhance image for wear region extraction. Segmentation tool was used to divide the worn and unworn regions by identifying white regions greater than a threshold value with an objective of quantifying the worn surface for tested specimen. Canny edge detection and granulometry techniques have been used to quantify the wear region. The results revel that the specific wear rate increases with increase in applied load, at constant sliding speed and sliding distance. Similarly, the area of worn region as identified by DIP also increased from 42.7% to 69.97%. This is because of formation of deeper groves in the worn material.