1) drill wear
钻头磨损
1.
In the drilling process, the power spectrum of a drilling force is closely related to the drill wear.
在钻削过程中,钻削力功率谱与钻头磨损之间具有较强的相关性,被广泛用于钻头磨损监测,但是关于功率谱特征的提取和识别一直没有很好解决。
2.
In this paper,the cutting force signals in different drill wear conditions are decomposed and reconstructed using wavelet transform; and the changing characteristics of cutting force signals of time domains in different frequency bands are obtained.
采用小波分析对钻头不同磨损状态的切削力信号进行分解与重构处理 ,获得了切削力信号在不同频段的时域变化特征 ,并分析了各个频段重构信号的方差随钻头磨损的变化规律。
4) drill wear monitoring
钻头磨损监测
1.
Meanwhile,with an aim at the strong randomization and uncertainty characteristics between the feature vectors and drill wears in drilling process,a kind of drill wear monitoring method based on Hidden Markov Model(HMM) was presented.
从工程应用的角度论述了小波包分解原理及其能量谱监测理论,并将该理论应用于钻削力信号特征提取中,针对钻削过程特征矢量与钻头磨损之间具有较强的随机性和不确定性的特点,提出一种基于隐马尔可夫模型(HMM)的钻头磨损监测方法。
2.
With the drilling process as the research objective, the drill wear monitoring experimental system with the drilling force as the monitoring signal is e.
论文以钻削过程为研究对象，建立了以钻削力作为监测信号的钻头磨损监测实验系统，对钻削力信号的特征提取以及基于HMM的多特征融合钻头磨损监测技术进行了系统的理论与实验研究。
3.
With the drilling process as the research objective, the feature extraction of drilling force and noise signals during the drill wear monitoring as well as the drill wear condition recognition was studied theoretically in this artic.
论文以钻削过程为研究对象，对钻头磨损状态监测中钻削力和噪声信号的特征提取和刀具状态识别等进行了系统的理论分析与实验研究，建立了以钻削力和加工噪声作为监测信号的HMM钻头磨损监测实验系统。
5) throwaway bit
磨损报废的钻头
6) gauge wear
钻头径向磨损
补充资料：大直径牙轮钻头
大直径牙轮钻头
大““钻头篡
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条