Remote FxLMS Algorithm for Active Control of Sound in Remote Locations
Iman ArdekaniDepartment of Computing
Unitec Institute of TechnologyAuckland, New Zealand
Waleed AbdullaECE Department
The University of AUcklandAuckland, New Zealand
APSIPA ASC 2014APSIPA Annual Summit and ConferenceCambodia, Dec. 9 – 12, 2014
Outline
• ANC• ANC Analysis in Acoustic Domain• Remote ANC• Adaptive Remote ANC Algorithm• Results• Conclusion
2
2
Active Noise Control – Why?
𝜆
𝜆=𝑐𝑓
wave length (m) sound velocity (m/s)
frequency (Hz)
𝑑
effective passive control
𝑓 (𝐻𝑧) 𝜆 (𝑚)100000.034310000.3431003.343
Passive noise control is bulky and costly for low frequencies!
3
Page 5
Active Noise Control – Acoustic Domain
u(n) : original noise
d(n) : primary noise
Primary Path (G)
Reference mic
Errormic
Secondary Path (H)
d’(n) : secondary noise
v(n) : anti noise d(n) u(n)d’(n) v(n)
e(n)
u(n) v(n)
e(n)
Control System
Control System
Page 6
Active Noise Control – Digital Electronic Domain
W
Gu(n) e(n)
FxLMS
Hv(n)
Control System
d(n)
d'(n)
Minimization of e(n) power through producing v(n) using u(n) and e(n) FxLMS Algorithm
Page 7
Active Noise Control – Research Gap
𝜆 20
Traditional ANC
e(n)
Problems: - very small zone of quiet- space occupied by the error mic
10 dB ZoQ
𝜆 20
e(n)
10 dB ZoQ
Advantage:- effective use of space in quiet zone
Remote ANC (proposed)
Page 8
ANC Analysis in Acoustic Domain – Coordinate System
u(n)
Reference mic
v(n)
L1
e(n)
Control Source
L2
y-axis+
Lo
x-ax
is+
Error mic (ZoQ centre)
Conclusion
• A novel model for the analysis of the ANC systems in
the acoustic domain is proposed.
• Based on this model, a methodology for active noise
control in remote location is developed.
• An adaptive framework for the realization of the
proposed remote ANC system is developed.
• Using remote ANC idea, the space available in the
quiet zone can be used more effectively.
• Future work: targeting 3D zones of quiet in remote
locations instead of a point.
Page 18
𝜆 20
e(n)
10 dB ZoQ
Top Related