Tool wear resulted in increased cutting tool forces and machined surface temperature.

刀具磨损造成更多的部队和刀具加工表面温度.

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Tool wear modeling method for spiral rod milling is presented.

介绍了一种螺杆铣削过程刀具磨损建模的方法.

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Therefore, the prediction of tool wear and failure is very urgent.

因此, 预测刀具的磨损和破损的产生,显得十分紧迫.

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However, tool wear is high in USM, due to the abrasive cutting action.

但是, 由于USM是磨削加工, 因而刀具损耗大.

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Acoustic Emission ( AE ) is a useful and effective technique in tool wear monitoring.

声发射技术是刀具磨损监测的一种新方法.

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The cutting temperature highcutting process , concerning about the tool wear, workpiece surface integrity and machining precision.

切削温度与刀具磨损 、 工件加工表面完整性及加工精度密切相关.

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The experiment results showed that HOS could be used to distinguish different tool wear styles.

实验结果表明,利用高阶量可以有效区分刀具磨损的不同阶段.

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The effects of vibration parameters on the surface roughness and the tool wear are analyzed.

研究了不同振动参数对工件表面粗糙度和刀具磨损量的影响规律.

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Accompanied with the development of modern machining industry, tool wear monitoring becomes more and more important.

随着现代加工工业的发展, 对刀具磨损的监测在保障生产安全和产品质量中发挥着越来越重要的作用.

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A tool wear monitoring method based on the neuro fuzzy - network using B spline function is presented.

提出一种基于B样条函数模糊神经网络的刀具磨损量监测方法.

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At a low temperature, the mechanical property improving, residual stress, roughness & cutting tool wear decreasing.

低温状态下金属材料表现为机械性能提高, 残余应力下降, 粗糙度降低 、 刀具磨损减小.

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In EDM process, tool wear is one the primary factors affecting geometrical precision of work piece.

电火花成形加工过程中, 工具电极的损耗是影响工件几何形状精度的主要因素之一.

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The experimental results show that the proposed method for tool wear monitoring is reliable and effective.

实验分析表明,该方法实现刀具磨损监测是行之有效的.

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The cutting sound signal in audible range includes a plenty of tool - wear information.

可听阈内的切削声信号包含着丰富的刀具磨损信息.

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