Tool wear monitoring for the titanium alloy milling process based on power spectrum energy of spindle vibration
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摘要: 针对复杂切削工况下钛合金结构件加工过程中刀具磨损监测的难题，提出基于主轴振动信号功率谱能量的刀具磨损监测方法。首先，在剔除振动信号原始数据异常点的基础上，通过功率谱分布提取反映刀具磨损退化过程的0～7f0频带能量指标、过齿频率基频f0和倍频3f0幅值等3个指标作为监测刀具退化过程的敏感指标。其次，提出基于结构件加工质量约束的刀具磨损失效阈值确定方法。最后，在钛合金槽腔结构件上验证了本方法的可行性。结果表明：相比于基于FFT谱、时域统计指标与小波包频带能量的刀具磨损监测方法，文章提出的复杂切削工况下的刀具磨损监测方法效果更加显著，可准确识别刀具的早期磨损。Abstract: To solve the problem of tool wear monitoring in the machining process of titanium alloy structural parts under complex operational conditions, a novel tool wear monitoring method based on the power spectrum energy of spindle vibration was proposed. Firstly, the energy indicators of the 0~7f0 frequency band reflecting the tool wear degradation process, as well as the tooth passing frequency f0 and the frequency multiplier 3f0 amplitude indicators are extracted through power spectrum analysis as sensitive information for monitoring the tool degradation process. Secondly, a method is proposed to determine the tool wear fault threshold based on the machining quality constraints of structural parts. Finally, the feasibility of this method is verified on the cavity structure. The results show that compared with the tool wear monitoring methods based on FFT spectrum, time-domain statistical, and wavelet packet frequency band energy, the proposed tool wear monitoring method is more effective and can accurately identify the early tool wear.
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Key words:
- tool wear monitoring /
- spectrum energy /
- fault threshold /
- power spectrum
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图 2 槽腔结构件在恒定切削参数下加工时的主轴振动信号（刀具直径16 mm，钛合金材料；切削参数：转速600 r/min，进给速度96 mm/min，切宽2 mm，切深2 mm）
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