金属切削过程刀具磨损信号的混沌特征

发布时间：2018-04-20 23:34

本文选题：刀具状态监测 + 相空间重构　；参考：《振动与冲击》2015年10期

【摘要】：针对刀具磨损过程中声发射信号非线性特征,提出基于混沌理论的信号分析及特征提取方法。采用延迟时间法对去噪后的时间序列进行相空间重构,分析延迟时间及嵌入维数随刀具磨损的变化规律;用关联维数、最大Lyapunov指数及Kolmogorov熵三种混沌特征参数定量分析刀具在不同切削条件下随磨损量增大所呈现的变化规律。研究结果表明,刀具磨损声发射信号具有明显的混沌特征,三种混沌特征参数、延迟时间及嵌入维数与刀具磨损状态具有明显的对应关系,可用作刀具磨损状态监测、磨损量预测的特征参数。
[Abstract]:In view of the nonlinear characteristics of acoustic emission signals in tool wear, a method of signal analysis and feature extraction based on chaos theory is proposed. The delay time method is used to reconstruct the phase space of the time series after de-noising, and the change rules of the delay time and the embedding dimension with the tool wear are analyzed, and the correlation dimension, the maximum Lyapunov index and the Kolmogo are used. The three chaotic characteristic parameters of ROV entropy are used to quantitatively analyze the changing law of the cutting tool with the increase of wear and tear in different cutting conditions. The results show that the acoustic emission signals of tool wear have obvious chaotic characteristics, and three chaotic characteristic parameters, the delay time and the embedding dimension have obvious corresponding relationship with the wear state of the tool tool, which can be used as the tool wear. Tool wear condition monitoring and wear parameters prediction.

【作者单位】：东北电力大学机械工程学院;
【基金】：吉林省科技厅科技公关计划(20140204004SF)
【分类号】：TG506;TG71

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