Identification of dynamic instabilities in machining process using the approximate entropy method
Identification of dynamic instabilities in machining process using the approximate entropy method
复制标题
DOI：
10.1016/j.ijmachtools.2011.02.004
复制
发表时间：
2011-06-01
影响因子：
14
通讯作者：
Herrera-Ruiz, Gilberto
中科院分区：
文献类型：
--
作者：
Perez-Canales, Daniel;Alvarez-Ramirez, Jose;Herrera-Ruiz, Gilberto
颤振不稳定性是机械加工过程中一个长期存在的问题，它产生的振动具有非线性和非平稳的动力学特征。虽然传统的快速傅立叶变换方法通常用于工业中的抖振监测，但该方法仅适用于线性和平稳信号。提出了基于近似熵（ApEn）的铣削颤振不稳定性辨识方法。熵是数据序列中与随机性相关的不规则性和复杂性的指标。ApEn方法的吸引力在于它可以处理非线性和非平稳数据，需要相对较少的观测量，并且可以用于噪声信号。在实验室铣削实验中，采用时频监测方法实现了ApEn，结果表明，在一定频率范围内，不稳定抖振与熵增量有关。相比之下，稳定铣削会导致熵模式，其中高熵值集中在高频处，这与刀具的自然动力学有关。(C) 2011 Elsevier Ltd.版权所有。
Chatter instability is a persistent problem in machining process that produces vibrations characterized by nonlinear and nonstationary dynamics. Although traditional fast Fourier transform approaches are typically used for the monitoring of chattering in industry, the method is suitable only for linear and stationary signals. In this paper, methods based on approximate entropy (ApEn) are proposed to identify chatter instabilities in milling process. as entropy is an index of the irregularity and complexity related to randomness from data series. The attractiveness of the ApEn approach is that it can deal with nonlinear and nonstationary data, requires a relatively small number of observations and can be used for noisy signals. For a lab-scale milling experimental setup, the ApEn was implemented under a time-frequency monitoring method, showing that instable chattering is associated with entropy increment for a frequency range. In contrast, stable milling led to an entropy pattern where high-entropy values are concentrated at high frequencies, which are related to the natural dynamics of the cutting tool. (C) 2011 Elsevier Ltd. All rights reserved.