• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2018, Vol. 54 ›› Issue (17): 85-93.doi: 10.3901/JME.2018.17.085

• 特邀专栏:智能制造装备 • 上一篇    下一篇

智能车床的颤振实时辨识与在线抑制系统研究

熊振华, 孙宇昕, 丁龙杨   

  1. 上海交通大学机械系统与振动国家重点实验室 上海 200240
  • 收稿日期:2017-09-11 修回日期:2017-12-09 出版日期:2018-09-05 发布日期:2018-09-05
  • 作者简介:熊振华,男,1974年出生,博士,研究员,博士研究生导师。主要研究方向为智能制造、运动控制与先进电子制造。E-mail:mexiong@sjtu.edu.cn;孙宇昕,男,1991年出生,博士研究生。主要研究方向为信号处理,故障诊断,振动抑制。E-mail:sunyuxinhe@sjtu.edu.cn;丁龙杨,男,1992年出生,博士研究生。主要研究方向为智能制造,振动抑制。E-mail:medinglongyang@sjtu.edu.cn
  • 基金资助:
    国家重点基础研究发展计划(973计划,2013CB035804)资助项目。

Online Chatter Detection and Suppression System for Intelligent Machine Tool

XIONG Zhenhua, SUN Yuxin, DING Longyang   

  1. State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240
  • Received:2017-09-11 Revised:2017-12-09 Online:2018-09-05 Published:2018-09-05

摘要: 颤振是切削加工中的一种不稳定现象,它会对生产效率、加工表面和机床零部件造成恶劣的影响。因此,在加工过程中避免颤振的发生具有非常重要的意义。提出一种颤振的实时辨识与在线抑制系统,在不额外加装驱动部件的情况下,实现数控机床上加工颤振的智能抑制。该加工颤振智能抑振系统包括三部分:第一,以加权小波包熵作为特征实时地监测车削加工过程,并在颤振开始孕育时就将其辨识出来;第二,一旦检测到颤振,采用基于尺度因子的插值傅里叶算法,将颤振频率实时估计出来;第三,根据颤振频率,计算出主轴转速扰动的幅值和频率,使主轴转速按照指定的幅值和频率周期性变化,及时地将颤振抑制在其孕育阶段。通过薄壁圆盘端面车削试验对该系统进行验证,结果表明,所提颤振实时辨识与在线抑制系统能在颤振的孕育阶段,成功地将颤振检测出来,并及时进行抑制,实现了智能化的颤振抑制。

关键词: 颤振检测, 颤振抑制, 车削, 智能制造

Abstract: In machining processes, chatter, as an unstable phenomenon, has been a major problem due to its adverse effects on productivity, surface finish and machine tool components. It is of great importance to avoid chatter and ensure the stable turning process. A real-time chatter detection and suppression system (CDSS) to avoid chatter in turning processes is presented. The weighted wavelet packet entropy is employed to monitor the turning process and it detects chatter in the premature stage. Once chatter is identified, the dominant chatter frequency is immediately estimated by the scale factor-based interpolated DFT. The spindle speed variation, which periodically modulates the spindle speed around a nominal value, is instantly activated to suppress chatter. The variation parameters, i.e. amplitude and frequency, are computed based on dominant chatter frequency. In this way, chatter can be automatically identified and suppressed in an online fashion before it has fully developed. To experimentally verify the proposed method, the end-face turning of a flexible disc is carried out on a numerical control lathe with Siemens 840D. Two turning experiments with and without the CDSS are conducted using the same cutting parameters, cutting tool and workpiece. Experimental results demonstrate that chatter can be automatically detected and suppressed by the CDSS before chatter arrives at fully developed stage.

Key words: chatter detection, chatter suppression, intelligent manufacturing, turning

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