The document describes a study on using active noise control to reduce low frequency interior noise through destructive interference. It discusses noise sources below 500Hz, reviews active noise control principles using adaptive filters and the LMS algorithm, and presents results from simulations and a laboratory experiment that demonstrate noise reduction at an error microphone through adaptive control. Future applications discussed include noise reduction in aircraft, ships, and vehicles to improve occupant comfort and performance.

1. A Study on Noise Reduction in an Enclosed
Space by Destructive Interference
By
Lt Col (Dr) RM Monaragala
Maj KVP Dhammika
Flt Lt EPDR Edirisinghe

2. Content
• Background
• Aim
• ANC Principles
• Literature Review
• Practical Experiment and Results
• Future Applications
• Conclusion
• Questions

3. Background

4. Research on noise control has become
important

5. Exposure to the noise may result in deafness
and cardiovascular complaints.

6. Acute effects of noise include changes in
performance efficiency.

7. Noise Sources

8. Air Condition fan, aircraft propeller noises fall
below 500 Hz

9. Interior Noises
• Propeller Noise: Inside an aircraft.
– Single low frequency, around 200 to 400 Hz.
• Engine Noise: Inside an automobile.
– Single low frequency , around 200 to 300 Hz.
• Road Noise: Inside an automobile.
– Wide band low frequency noise from tires on road
– Range from 100 Hz to 500 Hz.

10. Interior Noises
• Aerodynamic Noise: Wind noise
– High frequency noise above 1000 Hz.
– Caused by wind sweeping through partly openings to the vehicle
interior
• Air Condition fan Noise
– Passes through air condition ducts to an enclosed space
• Structure borne vibrations
– Low frequency noise.

11. Active Noise Control (ANC)
Primary Noise Waveform Anti Noise Waveform
Residual Noise

12. Aim
To develop Active Noise Controller to reduce
low frequency noise and use for the defence
applications.

13. Importance of Reducing Interior Noise Level
• Minimize the fatigue on driver & passengers in
an automobile
• Improve the audio environment (for music)
• Improve the comfort of passengers
• Make the class rooms Quiet

14. ANC Principles

15. Noise
• Broadband Noise
- Ex: Low-frequency sound of a jet plane, the
impulse noise of a gunshot.
• Narrowband Noise
- Ex: The noise caused by a car’s combustion
engine.

16. Noise Reduction Methods
• Active Method
– Effective to reduce Noise up to 500 Hz.
• Passive Method
–Effective to reduce Noise beyond 500 Hz.

17. Passive Methods
• Sound absorption
• Sound isolation
• Vibration isolation
• Vibration damping
• Mufflers

18. An ANC system can be effective across the
entire noise spectrum, but it is particularly
appropriate at low frequencies of up to 500 Hz,
where passive systems are less effective.

19. Destructive Interference

20. ANC is developing rapidly due to improvements
in noise control, often with potential benefits
in size, weight, volume, and cost.

21. Different Kinds of ANC
ANC systems are divided into three different
groups.
• Global free space cancellation
• Zone-of-silence cancellation
• Cavity and duct cancellation

22. Feed Back ANC System

23. Feed Forward ANC System

24. Narrowband Feed Forward ANC System

25. Destructive Interference

26. The resulting sound is null, the sound energy is
transformed into heat

27. The net result is no sound at all.

28. Literature Review

29. A microphone & a loudspeaker to generate a
canceling sound was first proposed & patented
by Lueg in 1936.

30. Burgess developed a duct-noise cancellation
system based on adaptive filter theory in 1981.

31. Later in the 1980s, Digital Signal Processing was
Developed

32. The specialized DSPs were designed for real-
time numerical processing of digitized signals.

33. Adaptive Filters – LMS Algorithm

34. Adaptive Filters
• The principle is to calculate an output that is
equal to the unwanted disturbance by
minimizing the error signal.
• The disturbance will then be cancelled by
superposition of the inverted output of the
filter on it.

35. ANC Controller
• The ANC Controller is a Finite Impulse Response Filter.
• It computes the anti phase audio signal using a Least
Mean Square Error algorithm.

36. LMS Algorithm
• Output Signal Calculated as
• Primary Signal (input to ANC)
• Weight vector at time n
 )1(..)1()()(  Nnxnxnxnx
 T
N
T
nwnwnwnw )(..)()()( 110 




1
0
)()()(
N
i
i inxnwny

37. LMS Algorithm
• Then the output signal y(n) in equation can be
expressed by the vector operation
• The error (difference in phase between the
primary and secondary) can be written as
)()()()( ndnxnwne T

)()()()()(
1
0
inxnwnxnwny
N
i
i
T
 



38. Optimization
• Objective of the LMS algorithm is to find the
optimal weight vector where, the mean square
value of the error signal e(n) is minimized.
• This results in the weight vector to be updated
as:
)().()()1( nenxnwnw 
)()( nxnxT

 
20 

39. Practical Experiment and Results

40. ANC Simulation Model
The concept was simulated using Labview based on
the following model:

41. Initial ANC Experimental Model With
Labview

42. ANC Simulation With Labview
Wide band Noise
Spectrum without ANC
Wideband Noise Spectrum
with ANC

43. PSD of Noise at Error
Microphone Without Control
PSD of Noise at Error
Microphone with Control using
the LMS Algorithm

44. Initial Test Results Obtained With JAVA
Experimental Model

45. Initial Test Results Obtained With JAVA
Experimental Model

46. Future Applications

47. ANC Application In Defence
• Aid to reduce aircraft interior noise
• Aid to reduce engine vibration noise in cabins
of ships
• Reduce engine boom in a tank interior
• Reduce the Air-condition fan noise inside the
Classroom

48. Future Plans
• Develop the same model to obtain more
filtered effect.
• Develop the circuitry for the use of opened
space to reduce environmental noise.
• Develop the circuitry for the use of airfield to
reduce jet aircraft engine noise.

49. Conclusion
• The different control methods available today
for active noise control were studied.
• The adaptive filters based on the LMS algorithm
were chosen.
• Labview model and JAVA model were developed
to test the ANC level & to obtain graphical views
of controlled signal.
• The model will be developed in future for the
defence applications.

50. • ?

54. Interior Noise Spectrum

55. Passive Techniques
– Sound Absorption
Sound Absorbing
Material
RigidWall
Reflected Sound
Pressure (Pr)
Incident Sound
Pressure (Pi)
2
1
r
i
P
P
NAC 
Noise Absorption
Coefficient
Back

56. Time Series Data of Input Noise Without Control

57. Time Series Data of Noise at Error Microphone With
an Adaptive Controller Using a Step
Size of 0.01 for the LMS Algorithm

58. Time Series Data of Noise at Error Microphone With
an Adaptive Controller Using a Step
Size of 0.1 for the LMS Algorithm

59. Developed ANC Laboratory Experimental
Model
REFERENCE
MICROPHONE
PRIMARY SOUND
SOURCE
ERROR
MICROPHONE
POWER AMPLIFIER
#2
POWER AMPLIFIER
#1
PRE AMPLIFIER #1
PRE AMPLIFIER #2 M6259 DATA ACQUISITION
CARD
PC
ENCLOSURE