Алгоритм оценки временного окна сигнала «белый шум» в

реклама
,
1, 2014
629.11.012.533
.
,
.
,
.
. .
.
E-mail: kafasu@vgta.vrn.ru
.)
.
.
.
. (473) 255-38-75
.
.-
.
.
.
)
. (473) 226-18-88
,
E-mail: nik.to77@mail.ru
Associate Professor A.A. Khvostov, professor S.G. Tikhomirov,
senior lecturer D.I. Rebrikov
(Voronezh, Russia. state Univeritying. technology.) Department of information and control
systems. phone (473) 255-38-75
E-mail: kafasu@vgta.vrn.ru
lecturer A.A. Nikitchenko
(Military-air academy of a name of professor N.E. Zhukovskii and Iu.A. Gagarin)
Department of research and designing of airdromes. Phone, (473) 226-18-88
E-mail: nik.to77@mail.ru
»
Algorithm for estimating the time window signal
"white noise" in the problems of acoustic
spectrometry elastomers
.
«
»
-
.
«
»
-
.
«
»
.
,
,
,
.
«
(
»
-
)
,
.
«
»,
.
.
Summary. In article the problem of choice of an optimum time interval and a quantization step at measurement of
spectral characteristics of objects with using «white noise» signal with restrictions by technical possibilities of signal registration is considered. In the application of "white noise" as a stationary perturbing signal problems arise with the presence of
distortions in the frequency spectrum due to the limited resolution of the digital recording device. When used in experimental
studies of digital technology there is the possibility of distortion due to restrictions on the time signal "white noise" for a fixed
number of points of the signal due to limited recording memory oscilloscope. For small time intervals distortion occurs in the
low frequency region of the spectrum and at large intervals signal is distorted in the high-frequency area due to the lower
sampling rate and, accordingly, the loss of information. To minimize distortions in the spectrum of the emitted signal it is
proposed selection algorithm of the time window signal type "white noise" fixed (in the sense of the amount of sampling
points) in terms of sample tasks for acoustic spectrometry based on the estimation of parameters of a linear function that approximates the spectrum and characterizing the linear trend.
:
,
,
,
.
Keywords: white noise spectrum, time interval, quantization step.
©
68
.,
.,
.,
., 2014
,
1, 2014
n 1
fm
[1].
»
«
Sj
fm -
tj
j t
f,
-
j 0
mj
Sj
n
,
k
1,
1,
(2)
, m
, j
m
m
;
.
.
,
i
,
.
:
Flinfit
-
«
»
L1, L2
,
i
.
-
,
:
S
,
,
-
(3)
L1,i
.
-
L2,i ,
L1,i
i
1
n
n
fj
j 1
2
fj
L1 , L2
(4)
min
-
-
.
(
1).
30
«
»
(
-
25
,
)
,
-
20
.
15
:
10
;
;
3
0
-
3
1 10
2 10
3
3 10
3
4 10
,
,
----
,
.
«
»
1.
.
.
f
i–
f,
:
F
i
i
, i 1, Kt ,
F-
,
-
L1,i
i–
(1)
.
-
-
, Kt –
-
.
L1,i (
)
.
S t
f
[2]
Mathcad 15 [3]:
,
L1,i
69
,
1, 2014
-
-
,
«
»
-
:
ti
t
,
HIOKI 7076,
RIGOL DS 1102
(5)
»
L1,i
«
(
-112-0.6
2).
-
0,6
1 10
1
.
3
200
800
.
,
2
»
2,
«
-
,
-
,
-
.
L1,i
3
i=1; i<N; i++
ti
i
.
4
«
3
i-
-
L1,i
»
«
ti
»
ti ,
3
.
,
,
5
«
-
»
L1,i
6
.
,
0.01
7
5 10
3
L1,i
L1,i , L2,i
0
L1,i
8
L1,i
9
2.
«
70
5 10
3
0.01
3
1 10
0.01
0.1
1
10
100
ti,
3.
».
3
1 10
i«
».
,
1, 2014
(
(
25
100
0,001
)
0,01
)
-
,
.
4
,
,
.
«
-
,
«
(3),
»
»,
-
-112-0.6,
-
RIGOL DS 1102.
50
100
200
40
1
5
1
f
30
20
10
10
0
0
50
100
,
4.
«
»
.
,
-
,
(4) (1
,
-
)
5
.
[4].
«
,
»,
5
-
,
(3) (
,
5)
-
2
.
.
0.8
10
0.6
1
100
0.4
f
10
)
10
0.2
0
5.
0
100
«
200
»
,
.
71
,
1, 2014
,
-
.
-
«
.
»,
REFERENCES
1
.,
,
, 2007. 500 .
2
.,
.:
:
-
.
. .:
, 1971. 316 .
. Mathcad 2001:
, 2001. 621 .
.,
.,
.
-
3
.
.
.
:
4
.,
//
. 2008. 1(31). . 124-126.
5 Honerkamp J., Roths T., Maier D., Friedrich C. et al. Determination of the relaxation time
spectrum from dynamic moduli using an edge
preserving regularization method. Rheologica Acta, 2000, vol. 3, no. 2, pp. 163-173.
72
1 Malkin A.Ia., Isaev A.I. Reologiia:
kontseptsii, metody prilozheniya [Rheology: concepts, application methods]. Sent-Petersburg, Professiia, 2007. 500 p. (In Russ.).
2 Dzhenkins G., Vatts D. Spektralnyi analiz
i ego prilozheniia [Spectral analysis and its applications]. Moscow, Mir, 1971. 316 p. (In Russ.).
3 D’iakonov V. Mathcad 2001 [Mathcad
2001]. Sent-Petersburg, Piter, 2001. 621 p. (In Russ.).
4 Bitiukov V.K., Tikhomirov S.G., Khvostov A.A., Zaichikov M.A. Estimation of polymer
quality parameters with frequence spectra of strength
module. Sistemy upravleniia i in-formatsionnye
tekhnologii. [Control systems and Information technology], 2008, no. (31), pp. 124-126. (In Russ.).
5 Honerkamp J., Roths T., Maier D., Friedrich C. et al. Determination of the relaxation time
spectrum from dynamic moduli using an edge preserving regularization method. Rheologica Acta,
2000, vol. 3, no. 2, pp. 163-173.
Скачать