超声振动辅助磨削牙科氧化锆陶瓷切削力预测模型研究

肖行志,郑侃,廖文和

振动与冲击 ›› 2015, Vol. 34 ›› Issue (12) : 140-145.

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PDF(1322 KB)
振动与冲击 ›› 2015, Vol. 34 ›› Issue (12) : 140-145.
论文

超声振动辅助磨削牙科氧化锆陶瓷切削力预测模型研究

  • 肖行志,郑侃,廖文和
作者信息 +

Research on prediction model of cutting force in ultrasonic vibration assisted grinding of zirconia ceramics

  • XIAO Xing-zhi, ZHENG Kan, LIAO Wen-he
Author information +
文章历史 +

摘要

通过单因素实验设计,开展了牙科氧化锆陶瓷的超声振动辅助磨削实验,分别建立了超声振动辅助磨削加工切削力指数预测模型、BP神经网络预测模型以及理论预测模型。通过验证实验对比分析了三种模型的预测精度,并阐明了误差产生的原因。结果表明,基于BP神经网络的切削力预测模型相对于指数和理论模型具有较高的预测精度,其平均相对误差仅为9.60%,理论模型因未能考虑材料的塑性流动去除,导致预测精度较低。

Abstract

Ultrasonic vibration assisted grinding (UVAG) experiments of dental zirconia ceramics have been conducted through single-factor method, the index prediction model and BP neural networks prediction model of cutting force in UVAG have been proposed, as well as the theoretical cutting force prediction model. The verification experiment has been conducted to study the prediction accuracy of these three models, and the causes of errors have been revealed. The result indicates that the BP neural networks prediction model has higher precision compared with two others, and the relative error is only 9.60%, the prediction accuracy of theoretical model is poor due to the neglect of plastic flow removal during UVAG.

关键词

超声振动辅助磨削 / 牙科氧化锆陶瓷 / 切削力预测 / 指数模型 / BP神经网络 / 理论模型

Key words

ultrasonic vibration assisted grinding / dental zirconia ceramics / cutting force prediction / index model / BP neural networks / theoretical model

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导出引用
肖行志,郑侃,廖文和. 超声振动辅助磨削牙科氧化锆陶瓷切削力预测模型研究[J]. 振动与冲击, 2015, 34(12): 140-145
XIAO Xing-zhi, ZHENG Kan, LIAO Wen-he. Research on prediction model of cutting force in ultrasonic vibration assisted grinding of zirconia ceramics[J]. Journal of Vibration and Shock, 2015, 34(12): 140-145

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