DocumentCode :
3575646
Title :
Fast predicting statistical subsurface damage parameters of the K9 sample
Author :
Hairong Wang ; Hongfeng Chen ; Lihui Xiao ; Bike Zhang ; Zhuangde Jiang
Author_Institution :
State Key Lab. for Manuf. Syst. Eng., Xi´an Jiaotong Univ., Xi´an, China
fYear :
2014
Firstpage :
197
Lastpage :
201
Abstract :
Based on the subsurface damage model and the material removal rate of K9 glass in HF acid solution, a fast method was proposed to calculate a set of parameters to characterize the subsurface damage of a polished sample. When micro cracks of the etched sample´s subsurface can be clearly observed, by using image processing, lengths, widths, angles, densities of the micro cracks can be calculated and depths of the micro cracks may be predicted by the load-crack model. The set of the parameters, including length, depth, angle, density, and other parameters, can be considered as a complete description about subsurface damage of the sample.
Keywords :
grinding; image processing; microcracks; optical glass; polishing; production engineering computing; HF acid solution; K9 glass; SSD; grinding process; image processing; material removal rate; sample polishing; subsurface damage parameter; subsurface microcrack; Etching; Glass; Image processing; Optical imaging; Surface cracks; fast calculation; high-precision components; image processing; subsurface damage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO), 2014 International Conference on
Type :
conf
DOI :
10.1109/3M-NANO.2014.7057330
Filename :
7057330
Link To Document :
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