采用小波包能量熵的铣削振动状态分析方法研究

doi:10.3901/JME.2018.21.057

机械工程学报 ›› 2018, Vol. 54 ›› Issue (21): 57-62.doi: 10.3901/JME.2018.21.057

采用小波包能量熵的铣削振动状态分析方法研究

张智^1,2, 刘成颖^1,3, 刘辛军^1,3, 张洁^1,3

1. 清华大学机械工程系北京 100084;
2. 海军航空工程学院飞行器工程系烟台 264001;
3. 清华大学精密超精密制造装备及控制北京市重点实验室北京 100084

收稿日期:2017-11-06 修回日期:2018-04-19 出版日期:2018-11-05 发布日期:2018-11-05
通讯作者: 刘成颖(通信作者),女,1960年出生,硕士,副教授,硕士研究生导师。主要研究方向为超精密加工工艺与装备、精密驱动与控制。E-mail:liucy@tsinghua.edu.cn
作者简介:张智,男,1990年出生。主要研究方向为机床振动的识别与在线监测。E-mail:z-zha14@mails.tsinghua.edu.cn
基金资助:
国家04科技重大专项资助项目（2013ZX04001021）。

Analysis of Milling Vibration State Based on the Energy Entropy of WPD

ZHANG Zhi^1,2, LIU Chengying^1,3, LIU Xinjun^1,3, ZHANG Jie^1,3

1. Department of Mechanical Engineering, Tsinghua University, Beijing 100084;
2. Department of Aircraft Engineering, Navy Aeronautical Engineering Academy, Yantai 264001;
2. Beijing Key Laboratory of Precision/Ultra-precision Manufacturing Equipment and Control, Tsinghua University, Beijing 100084

Received:2017-11-06 Revised:2018-04-19 Online:2018-11-05 Published:2018-11-05

摘要/Abstract

摘要： 颤振是影响机床加工质量的重要原因之一。为实现切削颤振的实时在线识别与评价，采用加速度传感器，获取主轴振动信号，以小波包能量熵值为指标，对铣削加工的稳定状态及振动形式进行识别。通过多传感器对加工过程进行监测，确定加工的稳定性；对主轴振动信号进行频谱分析，了解不同加工状态下的信号频谱特点，分析其振动形式。对信号进行小波包分解，发现在不同的振动状态下，信号的能量分布有显著规律。试验表明，切削从稳定状态到不稳定状态，本质上是强迫振动和颤振的能量强度和分布发生了变化。能量熵描述能量分布的变化，是识别切削状态和振动状态变化的有效方法。

关键词: 颤振, 能量熵, 强迫振动, 切削稳定性, 小波包分解

Abstract: Chatter is one of the critical factors that hinder machining quality in machining processes. To identify and evaluate chatter online, the acceleration is used to obtain the vibration signal of spindle. And by using the energy entropy of wavelet packet decomposition, the vibration signal is decomposed to judge the stability of milling and distinguish the vibration states. The stability of milling can be determined by the multi-sensor. Understanding the difference of signal in different conditions and analyzing the vibration forms the spectrum analysis is the second step. Then decomposition of the vibration signal with wavelet packet presents a significant law in the energy distribution of signal in different vibration forms. Several milling tests are conducted and shows that the milling state changing from stability to instability is same to the changing energy intensity between forced vibration and chatter. The energy entropy can describe the different distribution of energy well, which is a good way to identify the milling state and the vibration states.

Key words: chatter, energy entropy, forced vibration, stability of cutting, wavelet packet decomposition

中图分类号:

TH113

张智, 刘成颖, 刘辛军, 张洁. 采用小波包能量熵的铣削振动状态分析方法研究[J]. 机械工程学报, 2018, 54(21): 57-62.

ZHANG Zhi, LIU Chengying, LIU Xinjun, ZHANG Jie. Analysis of Milling Vibration State Based on the Energy Entropy of WPD[J]. Journal of Mechanical Engineering, 2018, 54(21): 57-62.

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采用小波包能量熵的铣削振动状态分析方法研究

Analysis of Milling Vibration State Based on the Energy Entropy of WPD

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