Abstract

Excitation force of under-chassis active equipment of railway vehicles has a significant impact on the floor vibration of the car body. In order to improve the accuracy of the excitation force identification of active equipment in engineering practice, a new excitation force identification method was proposed by applying modified Sage-Husa adaptive Kalman filter (MSHAKF). First, the advantages of the MSHAKF over conventional Kalman filter (CKF) are introduced. Simulation shows that the MSHAKF has excellent exactness and robustness for active equipment excitation force identification. Finally, a test device for identifying excitation force was established. The infinite impulse response (IIR) low-pass filter is designed by using the bilinear transformation method to eliminate the identification error caused by the frequency multiplication components in the response signal. The experimental result shows that the proposed method is very effective in engineering practice without mastering the noise characteristics of the system.

References

References
1.
Foo
,
E.
, and
Goodall
,
R. M.
,
2000
, “
Active Suspension Control of Flexible-Bodied Railway Vehicles Using Electro-Hydraulic and Electro-Magnetic Actuators
,”
Control Eng. Pract.
,
8
(
5
), pp.
507
518
. 10.1016/S0967-0661(99)00188-4
2.
Gong
,
D.
,
Zhou
,
J.
, and
Sun
,
W.
,
2013
, “
On the Resonant Vibration of a Flexible Railway Car Body and Its Suppression With a Dynamic Vibration Absorber
,”
J. Vib. Control
,
19
(
5
), pp.
649
657
. 10.1177/1077546312437435
3.
Gong
,
D.
,
Zhou
,
J.
, and
Sun
,
W.
,
2016
, “
Influence of Under Chassis Suspended Equipment on High-Speed EMU Trains and the Design of Suspension Parameters
,”
Proc. Inst. Mech. Eng. Part F: J. Rail Rapid Transit
,
230
(
8
), pp.
1790
1802
. 10.1177/0954409715614601
4.
Xue
,
X.
,
Chen
,
X.
,
Zhang
,
X.
, and
Qiao
,
B.
,
2016
, “
Hermitian Plane Wavelet Finite Element Method: Wave Propagation and Load Identification
,”
Comput. Math. Appl.
,
72
(
12
), pp.
2920
2942
. 10.1016/j.camwa.2016.10.019
5.
Turco
,
E.
,
2005
, “
A Strategy to Identify Exciting Forces Acting on Structures
,”
Int. J. Numer. Methods Eng.
,
64
(
11
), pp.
1483
1508
. 10.1002/nme.1418
6.
Yu
,
L.
, and
Chan
,
T. H. T.
,
2003
, “
Moving Force Identification Based on the Frequency–Time Domain Method
,”
J. Sound Vib.
,
261
(
2
), pp.
329
349
. 10.1016/S0022-460X(02)00991-4
7.
Liu
,
Y.
, and
Shepard Jr
,
W. S.
,
2005
, “
Dynamic Force Identification Based on Enhanced Least Squares and Total Least-Squares Schemes in the Frequency Domain
,”
J. Sound Vib.
,
282
(
1
), pp.
37
60
. 10.1016/j.jsv.2004.02.041
8.
Uhl
,
T.
,
2007
, “
The Inverse Identification Problem and its Technical Application
,”
Arch. Appl. Mech.
,
77
(
5
), pp.
325
337
. 10.1007/s00419-006-0086-9
9.
Li
,
K.
,
Liu
,
J.
,
Han
,
X.
,
Jiang
,
C.
, and
Zhang
,
D.
,
2016
, “
Distributed Dynamic Load Identification Based on Shape Function Method and Polynomial Selection Technique
,”
Inverse Probl. Sci. Eng.
,
25
(
9
), pp.
1
20
.
10.
Inoue
,
H.
,
Harrigan
,
J. J.
, and
Reid
,
S. R.
,
2001
, “
Review of Inverse Analysis for Indirect Measurement of Impact Force
,”
ASME Appl. Mech. Rev.
,
54
(
6
), pp.
503
524
. 10.1115/1.1420194
11.
Lin
,
D. C.
,
2010
, “
Input Estimation for Nonlinear Systems
,”
Inverse Probl. Sci. Eng.
,
18
(
5
), pp.
673
689
. 10.1080/17415971003698623
12.
Gunawan
,
F. E.
,
Homma
,
H.
, and
Morisawa
,
Y.
,
2008
, “
Impact Force Estimation by Quadratic Spline Approximation
,”
J. Solid Mech. Mater. Eng.
,
2
(
8
), pp.
1092
1103
. 10.1299/jmmp.2.1092
13.
Vogel
,
C. R.
,
2002
,
Computational Methods for Inverse Problems
,
SIAM
,
Philadelphia, PA
.
14.
Turco
,
E.
,
2017
, “
Tools for the Numerical Solution of Inverse Problems in Structural Mechanics: Review and Research Perspectives
,”
Eur. J. Environ. Civil Eng.
,
21
(
5
), pp.
509
554
. 10.1080/19648189.2015.1134673
15.
Hansen
,
P. C.
,
1992
, “
Numerical Tools for Analysis and Solution of Fredholm Integral Equations of the First Kind
,”
Inverse Probl.
,
8
(
6
), pp.
849
872
. 10.1088/0266-5611/8/6/005
16.
Choi
,
H. G.
,
Thite
,
A. N.
, and
Thompson
,
D. J.
,
2007
, “
Comparison of Methods for Parameter Selection in Tikhonov Regularization with Application to Inverse Force Determination
,”
J. Sound Vib.
,
304
(
3–5
), pp.
894
917
. 10.1016/j.jsv.2007.03.040
17.
Hu
,
N.
,
Fukunaga
,
H.
,
Matsumoto
,
S.
,
Yan
,
B.
, and
Peng
,
X. H.
,
2007
, “
An Efficient Approach for Identifying Impact Force Using Embedded Piezoelectric Sensors
,”
Int. J. Impact Eng.
,
34
(
7
), pp.
1258
1271
. 10.1016/j.ijimpeng.2006.05.004
18.
Pezerat
,
C.
, and
Guyader
,
J. L.
,
1995
, “
Two Inverse Methods for Localization of External Sources Exciting a Beam
,”
Acta Acustica
,
3
(
1
), pp.
1
10
.
19.
Pezerat
,
C.
, and
Guyader
,
J. L.
,
2000
, “
Identification of Vibration Sources
,”
Appl. Acoust.
,
61
(
3
), pp.
309
324
. 10.1016/S0003-682X(00)00036-0
20.
Gunawan
,
F. E.
,
Homma
,
H.
, and
Kanto
,
Y.
,
2006
, “
Two-step B-Splines Regularization Method for Solving an Ill-Posed Problem of Impact Force Reconstruction
,”
J. Sound Vib.
,
297
(
1–2
), pp.
200
214
. 10.1016/j.jsv.2006.03.036
21.
Liu
,
J.
,
Meng
,
X.
,
Zhang
,
D.
,
Jiang
,
C.
, and
Han
,
X.
,
2017
, “
An Efficient Method to Reduce Ill-Posedness for Structural Dynamic Load Identification
,”
Mech. Syst. Signal Process.
,
95
(
1
), pp.
273
285
. 10.1016/j.ymssp.2017.03.039
22.
Kazemi
,
M.
,
Hematiyan
,
M. R.
, and
Ghavami
,
K.
,
2008
, “
An Efficient Method for Dynamic Load Identification Based on Structural Response
,”
International Conference on Engineering Optimization
,
Rio de Janeiro, Brazil
, pp.
l
5
.
23.
Ma
,
C. K.
,
Tuan
,
P.
,
Lin
,
D. C.
, and
Liu
,
C.
,
1998
, “
A Study of an Inverse Method for the Estimation of Impulsive Loads
,”
Int. J. Syst. Sci.
,
29
(
6
), pp.
663
672
. 10.1080/00207729808929559
24.
Ma
,
C. K.
, and
Lin
,
D. C.
,
2000
, “
Input Forces Estimation of a Cantilever Beam
,”
Inverse Probl. Eng.
,
8
(
6
), pp.
511
528
. 10.1080/174159700088027745
25.
Ma
,
C. K.
,
Chang
,
J.
, and
Lin
,
D. C.
,
2003
, “
Input Force Estimation of Beam Structure by an Inverse Method
,”
J. Sound Vib.
,
259
(
2
), pp.
387
407
. 10.1006/jsvi.2002.5334
26.
Kalman
,
R. E.
,
1960
, “
A New Approach to Linear Filtering and Prediction Problems
,”
ASME J. Basic Eng.
,
82
(
1
), pp.
35
45
. 10.1115/1.3662552
27.
Ma
,
C. K.
, and
Ho
,
C. C.
,
2004
, “
An Inverse Method for the Estimation of Input Forces Acting on non-Linear Structural Systems
,”
J. Sound Vib.
,
275
(
3–5
), pp.
953
971
. 10.1016/S0022-460X(03)00797-1
28.
Lin
,
D. C.
,
2012
, “
Adaptive Weighting Input Estimation for Nonlinear Systems
,”
Int. J. Syst. Sci.
,
43
(
1
), pp.
31
40
. 10.1080/00207721003764141
29.
Song
,
X.
,
Zhang
,
Y.
, and
Liang
,
D.
,
2017
, “
Input Forces Estimation for Nonlinear Systems by Applying a Square-Root Cubature Kalman Filter
,”
Materials
,
10
(
10
), pp.
1162
1180
. 10.3390/ma10101162
30.
Narasimhappa
,
M.
,
Rangababu
,
P.
,
Sabat
,
S. L.
, and
Nayak
,
J.
,
2012
, “
A Modified Sage-Husa Adaptive Kalman Filter for Denoising Fiber Optic Gyroscope Signal
,”
2012 Annual IEEE India Conference
,
IEEE
.
31.
Sun
,
J.
,
Xu
,
X.
,
Liu
,
Y.
,
Zhang
,
T.
, and
Li
,
Y.
,
2016
, “
FOG Random Drift Signal Denoising Based on the Improved AR Model and Modified Sage-Husa Adaptive Kalman Filter
,”
Sensors
,
16
(
7
), pp.
1073
1091
. 10.3390/s16071073
You do not currently have access to this content.