Grain edge detection of diamond grinding wheel

Lijun Zhou; Changcai Cui; Chunqi Huang; Hui Huang; Ruifang Ye

doi:10.1117/12.2014856

31 January 2013 Grain edge detection of diamond grinding wheel

Lijun Zhou, Changcai Cui, Chunqi Huang, Hui Huang, Ruifang Ye

Proceedings Volume 8759, Eighth International Symposium on Precision Engineering Measurement and Instrumentation; 87591J (2013) https://doi.org/10.1117/12.2014856
Event: International Symposium on Precision Engineering Measurement and Instrumentation 2012, 2012, Chengdu, China

Abstract

The topograpgy characterization of grinding wheel grain is indispensable for precision grinding, it depends on accurate edge detecting and recognition of abrasive grains from wheel bond to a large extent. Due to different reflective characteristics arising among different materials, difference between maximum and minimum intensity (Δ ) of diamond is larger than that of bond. This paper uses a new method for grain edge detection of resin-bonded diamond grinding wheel that combines the improved Canny operator in Method of Maximum Classes Square Error (called as OTSU) with ΔI obtained by the white light interferometry (WLI). The experimental results show that the method based on improved Canny operator can effectively detect the edge of diamond grain.

Citation Download Citation

Lijun Zhou, Changcai Cui, Chunqi Huang, Hui Huang, and Ruifang Ye "Grain edge detection of diamond grinding wheel", Proc. SPIE 8759, Eighth International Symposium on Precision Engineering Measurement and Instrumentation, 87591J (31 January 2013); https://doi.org/10.1117/12.2014856

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available