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Development of Active Noise Control (ANC)

System for an Acoustic Duct Venkata Ratnam T

#, *Seetha Ramaiah P

+

#Vibration Studies Division

Naval Science & Technological Laboratory, DRDO,

Ministry of Defence, Visakhapatnam-530027, AP, India

ratnamtv2k6@gmail.com +CS&SE Department, Andhra University

Visakhapatnam, AP, India

psrama@gmail.com

Abstract - The aim of this paper is to design and implement Active

Noise Control (ANC) System for reducing periodic noise in an

acoustic duct. The embedded computer based ANC System

comprises sensors, actuators and pre and post conditioning

amplifiers. The developed ANCS is a generic design platform that

can be applied for designing adaptive feed forward ANC and

feedback ANC. The paper also presents the noise control

methodology adopted for reducing periodic noise generated by a

noise source from the electronic noise generator connected to the

primary speaker attached to the one end of acoustic duct. Adaptive

feed forward ANC technique is used with Filtered-X Least Mean

Square (FXLMS) algorithm using FIR digital filter. Experimental

results are presented for active cancellation of sinusoidal noise at

octave band frequencies from 63 Hz to 1 kHz. The noise reduction

obtained at these frequencies was observed up to 45 dB.

I. INTRODUCTION

The Active Noise Control (ANC) is a technique that can

reduce the noise emitted from a variety of sources that are

present in our daily lives. Many noise sources, particularly

those produced by man-made machines, exhibit periodic or

tonal noise. This periodic noise allows a more effective

solution as each repetition of the noise is similar to the last

and the predictability of the noise allows creation of an

accurate anti-noise signal. The method is both a cost-effective

and practical noise control measure.

Active Noise Control (ANC) is an emerging area of

research with a great scope for application in different fields

[1] [2] [5]. Most of the researchers proposed modeling and

simulation studies on active noise control in acoustic ducts

using MATLAB/ LabView [14-17]. Active noise controller

can be practically implemented using different strategies.

The active noise controllers can be functionally divided into

feedback and feedforward controllers. Feedback controllers

can be realized with both analog and digital technology, but

feedforward systems operate usually only at digital

domain[18].

The ANC technique has not yet gained any real commercial

breakthrough, perhaps because of the many physical

parameters that have to be taken into consideration in order to

successfully design and install an ANC System. However,

some commercial products designed to attenuate noise in

ventilation systems are available, such as ActiveSilencerTM

Duct manufactured by Silentium [19] and hybrid active/

passive silencer ActA® manufactured by TechnoFirst [20].

Our work deals with practical implementation of active noise

control system for reducing periodic noise generated in an

acoustic duct.

The commercial applications include but are not limited to

the following:

• Active mufflers for automobiles, trucks and light machinery.

• Aircraft cabin silencing [10].

• Active noise-reducing headphones.

• Mufflers for environmental pollution control equipment.

• Active noise cancellation for Heating Ventilation and Air

Conditioning (HVAC) equipment in commercial buildings,

shipboard applications and clean rooms [7].

Active Noise Cancellation makes use of the notion of

destructive interference. When two sinusoidal waves

superimpose, the resulting waveform depends on the

frequency amplitude and relative phase of the two waves. If

the original wave and the inverse of the original wave

encounter at a junction at the same time, total cancellation

occur as shown in Fig. 1.

Fig. 1 Physical Concept of ANC

+ =

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II. DEVELOPMENT OF ANC SYSTEM FOR AN ACOUSTIC DUCT

An embedded computer based active noise control system

for an acoustic duct has been designed and implemented using

EZ-ANC System [12] that consists of embedded computer

based on ADSP-2181 system [13] with noise control software.

The noise control methodology adopted for reducing noise

generated by a primary speaker fitted to the acoustic duct is

single channel adaptive feed forward active noise control

technique[3] that uses filtered-x Least Mean Square (FxLMS)

algorithm with FIR filter. The functional block diagram of

single channel adaptive feed forward ANC as applied to the

acoustic duct is shown in Fig. 2.

Fig. 2 Functional Block Diagram

A. DESCRIPTION OF ANC SYSTEM

The ANC system includes physical plant (acoustic duct) for

noise propagation, a noise source (primary speaker), reference

and error microphones (sensors), loud speakers (actuators),

Active Noise Control Development System (EZ-ANC) as

noise controller, and associated instrumentation such as power

amplifiers, pre-amplifiers, and sound measuring equipment.

The reference sensor measures the unwanted noise and

produces a reference signal that is correlated to and

characterises the spectral content of the unwanted noise. This

reference signal is fed forward to the controller so that it can

determine the proper control signal before the noise has

reached the listening location. The control system uses this

reference signal to create a control signal to drive a loud

speaker which creates a cancelling noise that will attenuate the

unwanted noise when combined at the error sensor. The error

sensor measures the residual noise after the unwanted noise

and control signal have combined and sends an error signal

back to the controller to adapt the control system in an attempt

to further reduce the error. The control system adaptively

modifies the control signal to minimize the residual error[4].

The anti-noise signal is generated by the EZ-ANC system

continuously after processing the input signals (reference and

error microphone signals) according to the various ANC

parameters. The EZ-ANC system processes the input signals

by executing noise control program invoked upon RESET

with the execution of communication program through PC as

terminal (using a terminal emulation program, KERMIT) that

is connected to the serial port of EZ-ANC. KERMIT software

has been used in this project to program into EZ-ANC

system’s software. The ANC parameters such as number of

errors, number of controls, sample rate selection, adjusting

input and output gains, control filter, adaptive algorithm,

system identification, storing data, uploading & downloading

data and programs to and from the host computer-PC. The

generated anti-noise control signal is fed to the actuator-Loud

Speaker. The processing logic of input signals is based on the

use of Filtered-X LMS algorithm, for adaptive feed forward

control[6][9]. A brief description of the principle of adaptive

feed forward ANC system with Filtered-X LMS algorithm for

an acoustic duct is given below:

B. ADAPTIVE FEED FORWARD ANC

The theoretical FXLMS algorithm is implemented in the

practical EZ-ANC development system for achieving reduced

noise source propagated through air handling duct that is

shown in the Fig. 3.

Fig. 3 Adaptive Feed forward ANC using FXLMS algorithm

The Filtered–X Least Mean Square (FXLMS) Algorithm is

a popular Adaptive Algorithm for feed forward ANC

systems[8][11]. Using a digital frequency - domain

representation of the problem, the ideal active noise control

system uses an adaptive filter W(z) to estimate the response of

an unknown primary acoustic path P(z) between the reference

input sensor and the error sensor.

The z-transform of e(n) can be expressed as:

E(z)=D(z)+Y(z)=X(z)*[P(z)+W(z)] (1)

where E(z) is the error signal, X(z) is the input signal, Y(z)

is the adaptive filter output. After the adaptive filter W(z) has

converged, E(z) = 0. Hence equation (1) becomes:

W(z) = - P(z) (2)

which implies that:

y(n) = - d(n) (3)

Therefore, the adaptive filter output y(n) has the same

amplitude but is 180° out of phase with the primary noise d(n).

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When d(n) and y(n) are acoustically combined, the residual

error becomes zero, resulting in cancellation of both sounds

based on the principle of superposition.

III. PRACTICAL IMPLEMENTATION OF ANCS

An experimental setup was made with a wooden acoustic

duct of size 2.44m x 0.33m x 0.33m. A loud speaker (noise

source) is fitted at one end of the acoustic duct and is

connected to a sine generator to create periodic noise. A

cancelling speaker was fitted in the duct at an optimum

location. Type 40 AE ½" - G.R.A.S Sound & Vibration and

Model - ADM-311 Ahuja microphones are used as error and

reference microphones and are separated by 1.90m apart. The

speakers are connected to power amplifiers to adjust the

suitable gain controls. The power amplifiers, pre-amplifiers

and EZ ANC board are mounted on ANCS Hardware.

The practical experimental setup to test the complete

ANCS for tonal noise cancellation is shown in Fig. 4.

Fig. 4 Experimental Setup of ANCS

The primary loud speaker was driven by a sine generator

through an amplifier to generate tonal noise of 1/3 octave

frequencies ranging from 63 Hz to 1000Hz. This primary

speaker was attached to one end of the duct. The core of the

Single channel feed forward ANC system used in these

experiments was an EZ-ANC system from Causal Systems, in

which the filtered-x LMS algorithm was implemented. The

forward path, the path between the loud speaker input and the

error microphone output, was estimated off-line using FIR

filter which was steered with the LMS algorithm. The

secondary source was a loud speaker driven by an amplifier

with a maximum power of 30W per channel into 8 ohms.

IV. RESULTS

From the results obtained from the experimental setup are

presented in Fig. 5 & 6. The Sound Pressure Level (SPL) is

measured when noise source generating tonal noise at octave

frequencies. The SPL measured and compared When ANC

system ON and ANC system OFF is depicted in Figs. 5 & 6 as

bar chart. The blue color indicate When ANC OFF and Pink

color indicates when ANC ON. It can be clearly seen from the

Figs. 5 & 6 that the noise reduction levels in dB for given

noise source at octave frequencies varies from 5- 45 dB.

Fig. 5. Sound Pressure Levels with and without ANC system

Fig. 6. Sound Pressure Levels with and without ANC system

In order to determine the performance of the ANC system,

the sinusoidal periodic noise was generated for frequencies

from 63 Hz to 1000Hz. The noise levels from the error

microphone signal was measured, using 2-ch PicoScope Type

ADC 212 spectrum analyser, when ANC system was off and

when it was turned on. The corresponding Sound Pressure

Levels (SPL) in dB also plotted in both time domain and

frequency domain spectra as depicted in Figs. 7(a) to 7(e).

Red line indicates when ANC OFF and Green line indicate

when ANC ON.

Fig. 7(a) SPL At tonal frequency of 63Hz

Fig. 7(b) SPL At tonal frequency of 125Hz

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Fig. 7(c) SPL At tonal frequency of 250Hz

Fig. 7(d) SPL At tonal frequency of 500Hz

Fig. 7(e) SPL At tonal frequency of 630Hz

Fig. 7(e) SPL At tonal frequency of 1000Hz

V. CONCLUSION

Adaptive feed forward active noise control technique is

used with Filtered-X Least Mean Square (FXLMS) algorithm

using FIR digital filter. The experimental results of tonal noise

cancellation using automatic control of embedded computer

based ANCS shown appreciable reduction in low frequencies

and considerable reduction in high frequencies, i.e., for octave

band frequencies from 63 Hz to 1 kHz. The results are

encouraging and an appreciable reduction of 5 – 45 dB is

observed using ANCS. By using similar methodology, an

attempt can be made for reduction of a fan noise generated in

real life air conditioning duct applications.

ACKNOWLEDGEMENTS

The authors wish to place on record their gratitude to Sri.

S.V. Ranga Rajan, Outstanding Scientist, Director, NSTL,

Visakhapatnam for permitting to publish this paper. They

would also like to acknowledge the contributions of their

colleagues who have directly or indirectly contributed

information to this paper, particularly Sri. PVS Ganesh

Kumar, Scientist 'G', for suggestions and discussions on the

present work.

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