Research on optical surface quality online monitoring based on support vector machine

Guo Bi; Zhiji Sun; Dongxu Zhang

doi:10.1117/12.2069661

6 August 2014 Research on optical surface quality online monitoring based on support vector machine

Guo Bi, Zhiji Sun, Dongxu Zhang

Proceedings Volume 9281, 7th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies; 928118 (2014) https://doi.org/10.1117/12.2069661
Event: 7th International Symposium on Advanced Optical Manufacturing and Testing Technologies (AOMATT 2014), 2014, Harbin, China

Abstract

The interference of grinding wheel and optic surface during grinding process causes numerous acoustic emission (AE) phenomena. AE signals are competent for monitoring the quality of the ground surface. A quality prediction model of grinding optics is established based on support vector machine (SVM). Some time domain characteristics of AE signals are chosen as the input vectors. And surface roughness (Ra) and surface shape accuracy (P-V) are the output vectors, respectively. The experiment results show that the model can accurately predict the surface quality of the optics during grinding.

Citation Download Citation

Guo Bi, Zhiji Sun, and Dongxu Zhang "Research on optical surface quality online monitoring based on support vector machine", Proc. SPIE 9281, 7th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies, 928118 (6 August 2014); https://doi.org/10.1117/12.2069661

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