Non-Normal Dynamic Analysis for Predicting Transient Milling Stability

被引:3
|
作者
Bi, Qingzhen [1 ]
Wang, Xinzhi [1 ]
Chen, Hua [2 ]
Zhu, Limin [1 ]
Ding, Han [1 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Mech Engn, State Key Lab Mech Syst & Vibrat, Shanghai 200240, Peoples R China
[2] Dalian Maritime Univ, Marine Engn Coll, Dalian 116026, Peoples R China
基金
中国国家自然科学基金;
关键词
milling stability; transient vibration; transient growth; transient stability; DELAY-DIFFERENTIAL EQUATIONS; SEMI-DISCRETIZATION METHOD; CHATTER STABILITY; GENERAL FORMULATION; SYSTEMS;
D O I
10.1115/1.4039033
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A transient milling stability analysis method is presented based on linear dynamics. Milling stability is usually analyzed based on asymptotic stability methods, such as the Floquet theory and the Nyquist stability criterion. These theories define stability that can return to equilibrium in an infinite time horizon under any initial condition. However, as a matter of fact, most dynamic processes in milling operations occur on a finite time scale. The transient vibration can be caused by some disturbance in practical milling process. Heavy transient vibrations were observed in existing works, though the machining parameters were selected in the stability zone determined by the asymptotic stability method. The strong transient vibrations will severely decrease the machining surface quality, especially for small workpieces in which the majority of machining process is executed in a short period of time. The analysis method of the transient milling stability is seldom studied, and only some experiments and conjectures can be found. Here the transient milling stability is defined as transient energy growth in a finite time horizon, and the prediction method of transient stability is proposed based on linear dynamics. The eigenvalues and non-normal eigenvectors of the Floquet transition matrix are all used to predict the transient milling stability, while only eigenvalues are employed in the traditional asymptotic stability analysis method. The transient stability is finally analyzed by taking the maximum vibration energy growth and the maximum duration time of transient energy growth in a finite time for optimal selection of processing parameters.
引用
收藏
页数:7
相关论文
共 50 条
  • [1] Transient Rayleigh-Benard-Marangoni convection due to evaporation: a linear non-normal stability analysis
    Doumenc, F.
    Boeck, T.
    Guerrier, B.
    Rossi, M.
    JOURNAL OF FLUID MECHANICS, 2010, 648 : 521 - 539
  • [2] Direct tolerance analysis of mechanical assemblies with normal and non-normal tolerances for predicting product quality
    Hassani, H.
    Khodaygan, S.
    INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING, 2022, 35 (07) : 743 - 760
  • [3] Analysis of Covariance with Non-normal Errors
    Senoglu, Birdal
    Avcioglu, Mubeccel Didem
    INTERNATIONAL STATISTICAL REVIEW, 2009, 77 (03) : 366 - 377
  • [4] Non-normal stability analysis of a shear current under surface gravity waves
    Ambrosi, D.
    Onorato, M.
    JOURNAL OF FLUID MECHANICS, 2008, 609 : 49 - 58
  • [5] Anomalous Transient Amplification of Waves in Non-normal Photonic Media
    Makris, K. G.
    Ge, L.
    Tuereci, H. E.
    PHYSICAL REVIEW X, 2014, 4 (04):
  • [6] Non-parametric stability measures for analysing non-normal data
    Paul, A. K.
    Paul, Ranjit Kumar
    Das, Samarendra
    Behera, S. K.
    Dhandapani, A.
    INDIAN JOURNAL OF AGRICULTURAL SCIENCES, 2015, 85 (08): : 1097 - 1101
  • [7] Independent component analysis for non-normal factor analysis
    Hyvärinen, A
    Kano, Y
    NEW DEVELOPMENTS IN PSYCHOMETRICS, 2003, : 649 - 656
  • [8] An analysis of non-normal Markovian extremal droughts
    Sharma, TC
    HYDROLOGICAL PROCESSES, 1998, 12 (04) : 597 - 611
  • [9] FACTOR-ANALYSIS FOR NON-NORMAL VARIABLES
    MOOIJAART, A
    PSYCHOMETRIKA, 1985, 50 (03) : 323 - 342
  • [10] Non-normal stability of embedded boundary methods through pseudospectra
    Rapaka, Narsimha Reddy
    Samtaney, Ravi
    JOURNAL OF COMPUTATIONAL PHYSICS, 2018, 373 : 975 - 999