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Study of Cutting Parameter Effect on Spindle Vibration for Tool Breakage Monitoring in Drilling

机译:钻削刀具监控中切削参数对主轴振动的影响研究

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The cutting parameter effect including tool diameter and feed rate on the spindle vibration signal for tool breakage monitoring was studied. The vibration signal obtained from the accelerometer installed on a fixture connected to the spindle housing was considered as the input signal for the monitoring system. The monitoring system was integrated by a signal transformation module, feature selection module for creating the features related to the breakage event, and a classifier module for classifying the tool breakage event based on the selected features. The linear discriminate function was adopted as the classifier in this chapter. To collect the vibration signals for analyzing the signals and system performance affected by cutting parameter, an experiment was implemented on a tapping machine along with 2 mm/3 mm diameter drill and aluminum alloy workpiece. In feature analysis, various wavelet coefficients for the collected signals were analyzed for system performance with various tool diameters and feed rates. The results show that the system developed by combined signals obtained from various cutting parameters is not reliable to detect tool breakage when implementing with any cutting parameters included in the model development. However, 100 % classification rate can be obtained for all case based on the model developed by type 3 signals and with properly choosing wavelet coefficient as features.
机译:研究了包括刀具直径和进给率在内的切削参数对主轴振动信号的监控,以监测刀具的破损情况。从安装在与主轴箱相连的夹具上的加速度计获得的振动信号被视为监控系统的输入信号。该监视系统由信号转换模块,用于创建与破损事件相关的特征的特征选择模块以及用于基于所选特征对工具破损事件进行分类的分类器模块集成在一起。本章采用线性判别函数作为分类器。为了收集振动信号以分析受切削参数影响的信号和系统性能,在攻丝机上与直径为2 mm / 3 mm的钻头和铝合金工件一起进行了实验。在特征分析中,针对各种信号直径和进给速度,分析了收集信号的各种小波系数的系统性能。结果表明,当使用模型开发中包含的任何切削参数实施时,由从各种切削参数获得的组合信号开发的系统对于检测刀具破损是不可靠的。然而,可以对所有情况下基于由3型信号,并且与适当选择的小波系数作为特征建立的模型来获得100%的分类率。

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