the feature and the mechanism of tool wear for turning powder superalloy with cubic boron nitride ( cbn) bite are researched in this paper.

1、

the influence of cutting parameters was considered when the features sensitive to tool flank wear are extracted from the time series ar model. the principle of feature extraction was proposed.

在提取作为刀具磨损特征量的AR模型参数时，考虑了切削用量对模型参数的影响，提出了特征量选取的准则，使所提取的特征量更加实用化。

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2、

with the development of fms, cims and other automation techniques, the new tool wears monitoring system which is more practical and reliable in critical demand.

随着FMS、CIMS等自动化技术的发展，迫切需要新型、实用、可靠的刀具磨损监控系统。

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3、

two intelligent models with different mathematical characteristics ( anns and svm) are applied separately to recognize tool wear states and the results are fused to make the final decision.

以两种具有不同数学特性的智能识别模型ANN和SVM，分别对刀具磨损状态进行识别，并将识别结果进行融合得出最终决策。

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4、

last, eds analysis of surface composition of cutters and cuttings was done. the wear patterns of cutters were also observed.

最后用EDS分析了刀具磨损表面及切屑的成份，并观察了刀具的磨损形貌。

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5、

finally, according to the feature extraction, we build tool condition monitoring system based on rbf neural network to identify the tool wear state.

最后根据提取的特征参数，建立基于人工神经网络的RBF神经网络系统来对刀具磨损状态进行识别。

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6、

the influences of quantity used in cutting and orientation of fiber on drilling force, tool wear and drilling precision were investigated, and the mechanism was analyzed.

考察了Al2O3短纤维和C短纤维含量、纤维位向、钻削速度及进给量对钻削力、刀具磨损和钻削精度的影响，并进行了分析。

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7、

auto-monitoring of the tool wear and analysis on the wearing status have become the exigent problems in fms and cims.

自动监测刀具磨损、分析刀具磨损状况是FMS和CIMS中迫切需要解决的问题。

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8、

surface plastic deformation always occurs during the whole tool wear process. the drastic wear of the flank surface on cutting tool produces white layer in workpiece surface.

工件表面的塑性变形在刀具磨损整个过程中都会发生，加工表面白层在刀具后刀面磨损剧烈时产生，但X射线分析没有发现相变。

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9、

analysis of wearing form of pcd tool

PCD刀具磨损形式分析

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10、

the on-line monitoring of tool wear and breakage is one of the basic functions of fms.

刀具磨损、破损的在线监控是FMS的基本功能之一。

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11、

feature extraction of machined surface texture for tool wear monitoring based on hough transform

基于Hough变换的刀具磨损监测加工表面纹理特征提取

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12、

the selected features are then considered as inputs to bp neural network to complete recognition of the status of the cutting tool.

利用小波包分解技术对信号进行分析，得到有效的特征量作为BP神经网络的输入样本，并对网络进行学习训练，完成对刀具磨损状态的有效识别。

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13、

a study of the methods of controlling tool wear life prediction in fms

FMS环境下刀具磨损寿命预测研究

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14、

experimental study on the cutting force and wear of lathe tool for sic p/ 2024 al composite

SiC P/2024复合材料切削力与刀具磨损的试验研究

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15、

study of tool wear on-line monitoring in cnc turning

CNC车削中刀具磨损实时监控的试验研究

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16、

analysis of tool wear condition based on matlab

基于MATLAB的刀具磨损状态分析

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17、

tool wear monitoring based on b-spline fuzzy neural networks

基于B样条模糊神经网络的刀具磨损监测

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18、

partial least squares regressive analysis and modeling for tool wear

刀具磨损的偏最小二乘回归分析与建模

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19、

study on prediction of the state of tool wear based on rbf network

基于RBF网络的刀具磨损状态预测技术研究

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20、

it relies on a series of cameras and ultra-sound radar sensors that ensure the car stays in lane and is a safe distance from other cars.

依靠一系列的摄像机和超声雷达感应器，汽车能够确保在车道内行驶，并与其他车辆保持安全距离。

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