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KAIST: Korea Advance Institute of Science and Tech(4000 undergrad, 4000 grad, 600 faculty members)
NOVIC: Center for Noise and Vibration Control(7+7 faculty members, 35 M.Sc. 50 Ph.D. about 500 graduates since)
C.W. Lee: Rotor Dynamics, Golf Dynamics Younsik Park: Structural Modification and Modal Analysis
Kwang-Joon Kim: Vibration Isolation J.G. Ih: BEM, BEM holography, Active Control
Youngjin Park: Active Sound Control, HRTF Customization Jungwoo Choi: 3D sound and audio
Yang-Hann Kim
Korea Advanced Institute of Science and Technology (KAIST) Center for Noise and Vibration Control (NOVIC)
[email protected] 2013. 4. 29.
Sound Visualization & Manipulation
3 Sound Visualization and Manipulation
Introduction
We can take a picture using a camera
4 Sound Visualization and Manipulation
Sound Visualization
Can we take the picture of sound?
5 Sound Visualization and Manipulation
Sound Manipulation
Or, can we draw the picture of sound?
6 Sound Visualization and Manipulation
Sound visualization and manipulation
See what we want using microphone array
Draw what we want using loudspeaker array
Sound Visualization Sound Manipulation
Sound Visualization
8 Sound Visualization and Manipulation
Introduction
[†]
[†] SMInstruments
9 Sound Visualization and Manipulation
What is sound visualization?
Color organ by Bainbridge Bishop(1893,US)
Sound Color
[†]
[†] A souvenir of the color organ, with some suggestions in regard to the soul of the rainbow and the harmony of light, Bainbridge Bishop, The De Vinne Press, 1893.
The first attempt to visualize the sound
10 Sound Visualization and Manipulation
What is sound visualization?
Many means to express organ sound [†] Sound field by five in-phase monopoles
[†]
Sound Color
11 Sound Visualization and Manipulation
MAPPING
Sound visualization as a mapping
Measured data Acoustic image
12 Sound Visualization and Manipulation
Sound visualization as a mapping
[†] This illustration is a modified version of the figure, pp.111-112, Science with a Smile (Robert L. Weber, Institute of Physics Publishing, 1992)
The result of sound visualization depends on the selection of basis function
[†]
Measured data Acoustic image
Mapping
13 Sound Visualization and Manipulation
Category of sound visualization
Two popular visualization methods using different types of basis functions
Provides information of the source surface. (pressure, particle velocity, intensity..)
Non-parametric method
Parametric method
Sound Visualization
Acoustic Holography Beamforming
Only provides information of the source location.
14 Sound Visualization and Manipulation
I. Acoustic Holography
One-dimensional case
0( , )p x t
0 0( , ) ( ) j tp x t P x e ω−=
0xx =
1xx =
1( , ) ?p x t =
What is Measured
Propagation or Prediction
0 1( )jk x xe− −×1( , )p x t =What We
See
1 0( | ; )H x x ω×
15 Sound Visualization and Manipulation
What we see (sound field)
What is measured: (pressure & velocity on the boundary)
I. Acoustic Holography
Three-dimensional case
Propagation (or prediction)
Kirchhoff-Helmholtz integral equation
O 0r
r 0S
0n……
……
( ) ( ) ( ) ( )0
00
000
00
| ;1( ;4
|;) ;;
S
G r r fG r r
P rP r
fP rf Sf f d
nnπ∂
= − ∂ ∂
∂∫
( )0;P r f
( ; )P r f
16 Sound Visualization and Manipulation
Prediction of Mona Lisa’s image by Acoustic Holography
I. Acoustic Holography: example
Measurement plane
What we see What is measured
Propagation
Source plane
17 Sound Visualization and Manipulation
II. Beamforming
Plane wave propagation model
measured pressure
sin ( 1) sin1Tjkd jk M de eθ θ− = W
scan vector (modeled signal)
[ ]1 2 3 4T
MP P P P P=P
[ ]1 2 3 4T
MW W W W W=W
d
sθ
x
y
sθ
1PMP
1WMW
1
1 M
iM =∑
2|P |ower( ) HEθ = P W
mP
mW
θ
Scan vector W is the basis function of beamforming method.
18 Sound Visualization and Manipulation
II. Beamforming: example
Measurement plane
What we see What is measured
Propagation
Source plane
Prediction of Mona Lisa’s image by beamforming
ACOUSTIC HOLOGRAPHY: APPLICATIONS
19
20 Sound Visualization and Manipulation
Moving Frame Acoustic Holography
Magnetic levitation train
• Pressure distribution at source plane (900Hz) • Intensity plot (900Hz)
21 Sound Visualization and Manipulation
Cylindrical Acoustic Holography
King Seong-Deok bell
• Step by step measurement • Microphone array
- Number of microphone: 30 - Aperture size : 4.42 m - Microphone spacing : 0.15 m - Radius of hologram: 0.2 m
BEAMFORMING: APPLICATIONS
22
23 Sound Visualization and Manipulation
Temporal basis function
Source localization using two different basis functions
Beamforming of an impulsive signal interfered by steady sound
24 Sound Visualization and Manipulation
Time domain beamforming of impulsive source localization
Impulsive signal interfered by steady noise
K-21 Infantry Fighting Vehicle 0.8m from top of the turret Idle level (98 dB) Moving 5~20 km/h (106~112 dB))
25 Sound Visualization and Manipulation
Real time implementation using FPGA
Digital MEMS microphone + FPGA(Field Programmable Gate Array)
High Frame Rate Unique Portable Design Light Weight Simple Connection Compact Controller Low Price
Digital MEMS Microphone Array
IP Camera
sbRio-9606
Ethernet Hub
Battery
Note Book
Power Supply
Advantages:
26 Sound Visualization and Manipulation
Real time implementation using FPGA
Engine noise visualization
27 Sound Visualization and Manipulation
Summary of sound visualization
The selection of basis function leads to different results
Beamforming Holography
Measured pressure
28 Sound Visualization and Manipulation
Sound manipulation problem
measurement plane
Sound Visualization
source plane
What if we replace the microphone array with a loudspeaker array?
Sound Manipulation
We can then draw the sound picture using a loudspeaker array !
Sound Manipulation
30 Sound Visualization and Manipulation
[†]
[†] Big Bang Theory S02E09, 2008. Available partly on Youtube (http://www.youtube.com/watch?v=vTcpE9sGmH4&feature=endscreen)
Introduction
31 Sound Visualization and Manipulation
How can he make what he wants to hear at his seat?
cool!
How can we manipulate a sound field at a desired region? : Zone control of sound field
Objective of sound manipulation
32 Sound Visualization and Manipulation
What to draw on the selected zone?
Basis function depends on the impression of sound we want to draw.
Drawing a desired shape of wavefront
Radiating sound ball Focused sound ball
Drawing dot(s) in space
Sound Manipulation
33 Sound Visualization and Manipulation
I. Radiating sound ball: overview
Reproduction of the sound field from a radiating sound ball over the zone of interest
34 Sound Visualization and Manipulation
II. Focused sound ball: overview
Generation of a focused sound ball in the zone of interest
35 Sound Visualization and Manipulation
I. Radiating sound ball: mathematical expression
One-dimensional case
0( , )p x t
0 0( , ) ( ) j tp x t P x e ω−=
0xx =
1xx =
1( , )p x t
What we can control
Propagation (transfer function)
0 1( )jk x xe− −×1( , )p x t =What to
manipulate
Loudspeaker
1 0( | ; )H x x ω×
36 Sound Visualization and Manipulation
I. Radiating sound ball: mathematical expression
Three-dimensional case
( ) ( ) ( ) ( )| ; ,|, ,) ;( s
sS
ss
ss
G r r fG r r fP r f
P r fP r f dS
n n∂
= − ∂ ∂
∂ ∫
Kirchhoff-Helmholtz integral equation
What to manipulate (sound field)
What we can control (pressure & velocity on the boundary)
Propagation (transfer function)
O
sr
rS
sn……
……
Loudspeaker
( )P r
( )sP r
Λ
VVirtual source
37 Sound Visualization and Manipulation
II. Focused sound ball: mathematical expression
Regional sound focusing: acoustic brightness and contrast control[†]
Maximizing energy ratio between acoustically bright zone and dark zone
Find maximum brightness or contrast by eigenvalue analysis
r
0V
pointsM
sH
p
=p Hs
bV dV
tV
Potential energy in Vb
Potential energy in Vd
Potential energy in Vb
Input power Bright zone Dark zone
Hsp =
: Acoustic brightness control : Acoustic contrast control [†] J. -W. Choi and Y. -H. Kim, “Generation of the acoustically bright zone within an illuminated region using multiple sources,” J. Acoust. Soc. Am., Vol. 111(4), pp.1695–1700, 2002.
Radiating Sound Ball: Applications
39 Sound Visualization and Manipulation
3D reproduction of a virtual source
Example
- Nspk = 194(Lebedev quadrature grids), Control source at 2λ, Virtual source at 1λ
40 Sound Visualization and Manipulation
KAIST multichannel loudspeaker system
Implementation
Amplifiers
DA Converters
24ch. Line array
49ch. Spherical array
PC
Wi-Fi
Smart phone or Tablet PC User interface
41 Sound Visualization and Manipulation
Realization Demo: Interface for virtual sources realization
Focused Sound Ball: Applications
43 Sound Visualization and Manipulation
Personal audio system[†]
Regional focusing: applications
A personal audio system can be used without uncomfortable earphones or headsets and bothering user’s neighbors.
[†] J-H Chang, C-H Lee, J-Y Park, and Kim Y-H, “A realization of sound focused personal audio system using acoustic contrast control,” J. Acoust. Soc. Am. 125(4), pp.2091-2097 (2009).
44 Sound Visualization and Manipulation
Regional focusing: applications
Frequencies of interest: 800 Hz ~ 5 kHz
Personal audio system: control results
45 Sound Visualization and Manipulation
Regional focusing: applications
Personal audio system with scattering effect[†]
x(m)
y(m
)
Contrast control
-0.4 0 0.4-0.4
-0.2
0
0.2
x(m)
Contrast control
-0.4 0 0.4-0.4
-0.2
0
0.2<800Hz> <2kHz> ( )ref . 0.1,0totp −Total field soln.
x(m)
Contrast control
-0.4 0 0.4-0.4
-0.2
0
0.2dB
-30
-20
-10
0
10
x(m)
y(m
)
Contrast control
-0.4 0 0.4-0.4
-0.2
0
0.2dB
-30
-20
-10
0
10
x(m)
y(m
)
Contrast control
-0.4 0 0.4-0.4
-0.2
0
0.2dB
-30
-20
-10
0
10
- Effect of listener’s head scattering: ( )ref . 0,0incp ( )ref . 0,0incp
- Control results considering scattering effect: <5kHz>
[†] J-H Chang, J-Y Park, and Kim Y-H, “Scattering effect on the sound focused personal audio system,” J. Acoust. Soc. Am. 125(5), pp.3060-3066 (2009).
46 Sound Visualization and Manipulation
Conclusion
[†] This illustration is a modified version of the figure, pp.111-112, Science with a Smile (Robert L. Weber, Institute of Physics Publishing, 1992)
We can visualize and manipulate any sound field by choosing appropriate basis function!
[†]
Thank you [email protected] soundmasters.kaist.ac.kr
Prof. J. W. Choi
Acknowledgment
Dr. M. H. Song Mr. D. H. Seo, K. W. Kim, K. H. Kim, J. M. Lee,
D. S. Kang, Ph.D. Candidate Ms. M. R. Lee, M.S. Candidate
of NOVIC KAST
SMInstruments
Appendix
49 Sound Visualization and Manipulation
Mona Lisa Beamforming
50 Sound Visualization and Manipulation
Mona Lisa Beamforming
Theory of Sound Focusing
with Four Principles (+ - × ÷)
52 Sound Visualization and Manipulation
Sound Focusing Problem
Manipulation of focused sound beam by adjusting excitation function of loudspeaker array
/ 2
/2( , ) ( )
jkRL
L
eP r dxq xR
θ−
= ∫Excitation function
(unknown)
/ 2 sin
/2( )
jkr L jk x
L
e e dxr
q x θ−
−≈ ∫
( )b θBeam pattern
q
( , )P r q
Loudspeaker array
( )q x
q
( , )P r q
( )q x( , )P r q
…
We can design the beam pattern with four principles(+ - × ÷).
53 Sound Visualization and Manipulation
Uniform Gain: ( )w x
(+) Theorem: Delay-and-Sum
Beam shaping and steering by gain weighting and time delay
( )b θ
Time delay:
( )( ) ( ) j xq x w x e ωτ=
Gain weighting
( ) xxcατ =
( )xτTime delay: ( )xτTime delay:
x
( )q x
54 Sound Visualization and Manipulation
(-) Theorem: Differential Sources
Differential sources can produce a directional radiation pattern despite limitation of the aperture size.
( )b θ
Excitation function for dipole beam pattern
( ) ( ) ( )2 2x xq x x xδ δ∆ ∆
= + − −
x( )q x
x∆ : source spacing
55 Sound Visualization and Manipulation
(x) Theorem: Composition of Beam Patterns
Design various beam shapes by multiplication of beam patterns
( )b θ
x( )q x
( )b θ
x
( )q x
x
( )q xArray of dipoles
56 Sound Visualization and Manipulation
(÷) Theorem: Optimization with Energy Ratio
Maximization of energy ratio
- Acoustic contrast control: - Acoustic brightness control:
Bright zone
Dark zone
bp
dpx
q
Dark zone
Control zone
Maximization of energy ratio between at bright zone and dark zone
Hb bHd d
β =p pp p
Maximize
Maximization of ratio between energy at bright zone and input power
Hb bHα =
p pq q
Maximize
Theory of Virtual Source Generation
58 Sound Visualization and Manipulation
Interior Virtual Source Problem in 1D Case
How can we reproduce 1D sound from a virtual source inside control zone?
1x x0
Right going Left going Virtual source
vx 2x
Control zone
( )
( )( , )v
v
jk x xv
t jk x xv
Ae for x xP x f
Ae for x x
−
− −
≤= <
Target field
: right going wave
: left going wave
59 Sound Visualization and Manipulation
Reproduction of Interior Virtual Source in 1D Case
By considering time-reversed propagation, right going wave can be generated.
1x x0
Virtual source
vx 2x
Control zone
Time-reverse of target field
( )*
, ( )( , )v
v
jk x xv
t tr jk x xv
Ae for x xP x f
Ae for x x
− −
−
≤= <What we can control
(excitation function)
(1,
)*1 1( ; )( , ) vjk
t trx xP x f H x x A xf e for x−= ≤
Propagation (transfer function)
What to manipulate (reproduced field)
60 Sound Visualization and Manipulation
Reproduction of Interior Virtual Source in 1D Case
But time-reversed propagation of omni-directional virtual source generates left going wave as well.
1x x0 vx 2x
Reproduced field by left control sources
Control zone
Reproduced field by right control sources
Control zone
Left going
Right going
Since the left going wave is an artifact, it must be removed!
Virtual source
Virtual source
61 Sound Visualization and Manipulation
Reproduction of Interior Virtual Source in 1D Case
Time-reversed propagation of the directional virtual source can excite the left-side control source to reproduce only right going wave.
1x x0
Directional Virtual source
vx 2x
Control zone
Control sources can be selectively excited for reproducing a directional virtual source.
62 Sound Visualization and Manipulation
2D Reproduction of Interior Virtual Source
- Nspk = 64 (circular array), Control source at 2λ from center
Time-reversed radiation of the directional virtual source can selectively excite the control sources.
x [m]
y [m
]
-3 -2 -1 0 1 2 3-3
-2
-1
0
1
2
3
Target field
Virtual Source
x [m]
y [m
]
-3 -2 -1 0 1 2 3-3
-2
-1
0
1
2
3
Time-reversed field
Circular Control Source Array
Virtual Source
Control source selection
x [m]
y [m
]
-3 -2 -1 0 1 2 3-3
-2
-1
0
1
2
3
Virtual Source
Reproduced field
Circular Control Source Array
Control source gain