航空学报 > 2023, Vol. 44 Issue (11): 27562-027562   doi: 10.7527/S1000-6893.2022.27562

切削加工过程中颤振在线监测研究综述

李益文1,3, 邓朝晖2,3(), 刘涛1,3, 卓荣锦1,3, 李重阳1,3, 吕黎曙1,3   

  1. 1.湖南科技大学 机电工程学院,湘潭 411201
    2.华侨大学 制造工程研究院,厦门 361021
    3.湖南科技大学 难加工材料高效精密加工湖南省重点实验室,湘潭 411201
  • 收稿日期:2022-05-31 修回日期:2022-06-12 接受日期:2022-07-13 出版日期:2022-08-09 发布日期:2022-08-08
  • 通讯作者: 邓朝晖 E-mail:edeng0080@vip.sina.com
  • 基金资助:
    湖南省创新型省份建设专项经费(2020GK2003);NFSC-浙江两化融合联合基金(U1809221);湖南省自然科学基金(2020JJ4309);湖南省自然科学联合基金(2021JJ50116)

Review on on⁃line monitoring of chatter in cutting process

Yiwen LI1,3, Zhaohui DEND2,3(), Tao LIU1,3, Rongjin ZHUO1,3, Zhongyang LI1,3, Lishu LV1,3   

  1. 1.School of Mechanical Engineering,Hunan University of Science and Technology,Xiangtan 411201,China
    2.Institute of Manufacturing Engineering,Huaqiao University,Xiamen 361021,China
    3.Hunan Provincial Key Laboratory of High Efficiency and Precision Machining of Difficult-to-Cut Materials,Hunan University of Science and Technology,Xiangtan 411201,China
  • Received:2022-05-31 Revised:2022-06-12 Accepted:2022-07-13 Online:2022-08-09 Published:2022-08-08
  • Contact: Zhaohui DEND E-mail:edeng0080@vip.sina.com
  • Supported by:
    Special Fund for the Construction of Hunan Innovative Province(2020GK2003);NFSC-Zhejiang Joint Foundation for the Integration of Industrialization and Informatization(U1809221);Natural Science Foundation of Hunan Province of China(2020JJ4309);Municipal Joint Fund for Natural Science of Hunan Provincial(2021JJ50116)

摘要:

颤振是航空航天加工制造等领域中广泛存在的问题,深入开展切削加工过程中颤振在线监测研究对于进一步提升颤振抑制效果、保障加工系统稳定运行具有重要意义。根据颤振在线监测所需的实时性和精确性的要求,围绕数据采集、在线特征提取及颤振识别进行综述,首先介绍了3种颤振数据采集方法的特点,然后深入归纳与分析了颤振特征应用情况及影响颤振特征提取的关键因素,接着比较并总结了基于有监督学习和无监督学习的颤振识别技术的特点,最后总结并展望了目前颤振在线监测所存在的问题及发展趋势,可为未来颤振在线监测研究提供参考。

关键词: 切削加工颤振, 在线监测, 数据采集, 信号处理, 有监督学习, 无监督学习, 颤振识别

Abstract:

Chatter is a widespread problem in aerospace manufacturing and other fields. In-depth research on on-line monitoring of chatter in cutting process is of great significance to further improve the suppression effect of chatter and ensure the stable operation of machining system. According to the real-time and accuracy requirements of the chatter online monitoring, this paper focuses on data acquisition, online feature extraction, and chatter recognition. Firstly, the characteristics of three kinds of chatter data acquisition methods are summarized, and then the application of chatter features and the key factors affecting chatter feature extraction are elaborated and analyzed. Later, the characteristics of chatter recognition techniques based on the supervised and unsupervised learning are compared and summarized. Finally, problems existed in the current on-line chatter monitoring and the development trend in the future are discussed, which can provide reference for the research of on-line chatter monitoring in the future.

Key words: cutting chatter, on-line monitoring, data acquisition, signal processing, supervised learning, unsupervised learning, chatter recognition

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