Model of grinding-induced line/area roughness and subsurface damage in brittle material based on genetic algorithm and deep neural network

Shenxin Yin; Huapan Xiao

doi:10.1117/12.2617309

15 February 2022 Model of grinding-induced line/area roughness and subsurface damage in brittle material based on genetic algorithm and deep neural network

Shenxin Yin, Huapan Xiao

Author Affiliations +

Proceedings Volume 12166, Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021); 121664D (2022) https://doi.org/10.1117/12.2617309
Event: Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021), 2021, Hong Kong, Hong Kong

Abstract

Post processes are usually needed to improve the quality and performance of ground brittle materials, and their low efficiency and high cost are greatly determined by grinding-induced roughness and subsurface damage (SSD). This raises an urgent demand to accurately predict various roughness and SSD depth. In this paper, grinding experiments are conducted on K9 glass samples with different processing parameters, including abrasive grain diameter, grinding depth, wheel speed, and feed speed. The line roughness Ra, area roughness Sa, and SSD depth are measured. Based on genetic algorithm (GA) and deep neural network, a relationship model among processing parameters, Ra, Sa, and SSD depth, is established. The model is accurate and reliable with a mean absolute percentage error MAPE < 10% and a correlation coefficient R > 0.94. The research is valuable in the evaluation of surface and subsurface integrity for ground brittle materials.

Citation Download Citation

Shenxin Yin and Huapan Xiao "Model of grinding-induced line/area roughness and subsurface damage in brittle material based on genetic algorithm and deep neural network", Proc. SPIE 12166, Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021), 121664D (15 February 2022); https://doi.org/10.1117/12.2617309

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