An output-only modal analysis (OMA) approach is presented to obtain the direct frequency response function (FRF) at the tip of the tool in micromilling setups. White noise input is provided using acoustic excitation and the resulting vibrations are measured using a laser Doppler vibrometer (LDV). Autoregressive (AR) identification is used to extract the natural frequencies and damping ratios of the structural modes of the milling setup, and mass-sensitivity analysis is used to obtain modal stiffness values. The accuracy of the tool tip FRFs that are constructed using OMA is verified by comparing them against the FRFs that are measured using impulse hammer tests. The direct FRF at the tool tip is an essential component in predicting and avoiding excessive and unstable vibrations in milling operations, and the presented approach provides a practical method for the direct measurement of the tool tip FRF in micromilling where the application of traditional hammer tests is not possible.

Issue Section:
Research Papers
Keywords:
Micro machining, Micro milling
Topics:
Damping, Excitation, Hammers, Impulse (Physics), Micromilling, Milling, Modal analysis, Stiffness, Vibration, White noise, Acoustics, Frequency response

References

1.
Altintaş
,
Y.
, and
Budak
,
E.
,
1995
, “
Analytical Prediction of Stability Lobes in Milling
,”
CIRP Ann.-Manuf. Technol.
,
44
(
1
), pp.
357
–
362
.
Google Scholar
Crossref
Search ADS
 
2.
Ewins
,
D. J.
,
1984
,
Modal Testing: Theory and Practice
, Vol.
15
,
Research Studies Press
,
Letchworth, UK
.
3.
Singh
,
K. K.
,
Kartik
,
V.
, and
Singh
,
R.
,
2015
, “
Modeling Dynamic Stability in High-Speed Micromilling of Ti–6Al–4V Via Velocity and Chip Load Dependent Cutting Coefficients
,”
Int. J. Mach. Tools Manuf.
,
96
, pp.
56
–
66
.
Google Scholar
Crossref
Search ADS
 
4.
Jin
,
X.
, and
Altintas
,
Y.
,
2013
, “
Chatter Stability Model of Micro-Milling With Process Damping
,”
ASME J. Manuf. Sci. Eng.
,
135
(
3
), p.
031011
.
Google Scholar
Crossref
Search ADS
 
5.
Filiz
,
S.
, and
Ozdoganlar
,
O. B.
,
2008
, “
Microendmill Dynamics Including the Actual Fluted Geometry and Setup Errors—Part II: Model Validation and Application
,”
ASME J. Manuf. Sci. Eng.
,
130
(
3
), p.
031120
.
Google Scholar
Crossref
Search ADS
 
6.
Schmitz
,
T. L.
, and
Donalson
,
R.
,
2000
, “
Predicting High-Speed Machining Dynamics by Substructure Analysis
,”
CIRP Ann.-Manuf. Technol.
,
49
(
1
), pp.
303
–
308
.
Google Scholar
Crossref
Search ADS
 
7.
Malekian
,
M.
,
Park
,
S. S.
, and
Jun
,
M. B.
,
2009
, “
Modeling of Dynamic Micro-Milling Cutting Forces
,”
Int. J. Mach. Tools Manuf.
,
49
(
7
), pp.
586
–
598
.
Google Scholar
Crossref
Search ADS
 
8.
Park
,
S.
, and
Rahnama
,
R.
,
2010
, “
Robust Chatter Stability in Micro-Milling Operations
,”
CIRP Ann.-Manuf. Technol.
,
59
(
1
), pp.
391
–
394
.
Google Scholar
Crossref
Search ADS
 
9.
Peeters
,
B.
, and
De Roeck
,
G.
,
2001
, “
Stochastic System Identification for Operational Modal Analysis: A Review
,”
ASME J. Dyn. Syst. Meas. Control
,
123
(
4
), pp.
659
–
667
.
Google Scholar
Crossref
Search ADS
 
10.
Hermans
,
L.
, and
Van der Auweraer
,
H.
,
1999
, “
Modal Testing and Analysis of Structures Under Operational Conditions: Industrial Applications
,”
Mech. Syst. Signal Process.
,
13
(
2
), pp.
193
–
216
.
Google Scholar
Crossref
Search ADS
 
11.
Ahmadi
,
K.
, and
Altintas
,
Y.
,
2014
, “
Identification of Machining Process Damping Using Output-Only Modal Analysis
,”
ASME J. Manuf. Sci. Eng.
,
136
(
5
), p.
051017
.
Google Scholar
Crossref
Search ADS
 
12.
Wan
,
M.
,
Feng
,
J.
,
Ma
,
Y.-C.
, and
Zhang
,
W.-H.
,
2017
, “
Identification of Milling Process Damping Using Operational Modal Analysis
,”
Int. J. Mach. Tools Manuf.
,
122
, pp. 120–131.
13.
Zaghbani
,
I.
, and
Songmene
,
V.
,
2009
, “
Estimation of Machine-Tool Dynamic Parameters During Machining Operation Through Operational Modal Analysis
,”
Int. J. Mach. Tools Manuf.
,
49
(
12
), pp.
947
–
957
.
Google Scholar
Crossref
Search ADS
 
14.
Li
,
B.
,
Cai
,
H.
,
Mao
,
X.
,
Huang
,
J.
, and
Luo
,
B.
,
2013
, “
Estimation of CNC Machine–Tool Dynamic Parameters Based on Random Cutting Excitation Through Operational Modal Analysis
,”
Int. J. Mach. Tools Manuf.
,
71
, pp.
26
–
40
.
Google Scholar
Crossref
Search ADS
 
15.
Gagnol
,
V.
,
Le
,
T.-P.
, and
Ray
,
P.
,
2011
, “
Modal Identification of Spindle-Tool Unit in High-Speed Machining
,”
Mech. Syst. Signal Process.
,
25
(
7
), pp.
2388
–
2398
.
Google Scholar
Crossref
Search ADS
 
16.
Schmitz
,
T. L.
, and
Smith
,
K. S.
,
2008
,
Machining Dynamics: Frequency Response to Improved Productivity
,
Springer Science & Business Media
, New York.
17.
Brincker
,
R.
, and
Ventura
,
C.
,
2015
,
Introduction to Operational Modal Analysis
,
Wiley
, Hoboken, NJ.
18.
Ibrahim
,
S.
,
Asmussen
,
J.
, and
Brincker
,
R.
,
1995
, “Modal Parameter Identification From Responses of General Unknown Random Inputs,” Aalborg University, Aalborg, Denmark, Technical Report No.
72
.http://svibs.com/solutions/literature/1996_2.pdf
19.
Bendat
,
J. S.
, and
Piersol
,
A. G.
,
1980
,
Engineering Applications of Correlation and Spectral Analysis
,
Wiley-Interscience
,
New York
, p.
315
.
20.
Van Overschee
,
P.
, and
De Moor
,
B.
,
2012
,
Subspace Identification for Linear Systems: Theory-Implementation-Applications
,
Springer Science & Business Media
, New York.
21.
Oppenheim
,
A. V.
,
1999
,
Discrete-Time Signal Processing
,
Prentice Hall
, Upper Saddle River, NJ.
22.
Iokhvidov
,
I. S.
,
1982
,
Hankel and Toeplitz Matrices and Forms
,
Birkhauser
,
Boston, MA
.
23.
Manufacturing Automation Laboratories, 2017, “Cutpro,” Manufacturing Automation Inc., Vancouver, BC, Canada, accessed Nov. 20, 2017, www.malinc.com
Copyright © 2018 by ASME
You do not currently have access to this content.