Application of Active Noise Control for Air-Conditioning System

Application of Active Noise Control for Air-Conditioning System

a Lik Wei, Foong, b Ka Fei, Thang, c Wai Meng, Chin a, b School of Engineering, Asia Pacific University of Technology & Innovation

Technology Park Malaysia, Bukit Jalil, 57000 Kuala Lumpur, Malaysia c R&D department, OYL Manufacturing Company Sdn, Bhd, Taman Perindustrian Bukit Rahman

Putra, 47000, Sungai Buloh, Selangor, Malaysia a [email protected], b [email protected], c [email protected]

ABSTRACT

The focus of the paper is on evaluating active noise

control (ANC) systems for effective noise reduction

of the outdoor unit of air-conditioning system. The

first problem intended to be solved is that the noise

created by the outdoor unit will lead to noise-

pollution to the environment. The second problem is

that the noise emitting from the compressor of air-

conditioning system varied with respect to time. The

third problem is that the chosen ANC system must

be able to cope with low and high frequency of the

noise signal. The developed system to deal with

aforementioned problems is the PC-based ANC

system with normalised least-mean-square (NLMS)

algorithm. Based on the testing result obtained, the

average noise-reduction in actual outdoor unit is 0.9

dBA. The obtained result is encouraging and will

form the foundation for future work on the same area.

KEYWORDS

Active Noise Control, Normalised Least-Mean-

Square, Outdoor Unit, Air-Conditioning System,

Noise Reduction.

1 INTRODUCTION

Nowadays, air-conditioning system plays an

important role in our daily life either at homes,

offices, industries and so on. This is because the

air-conditioning system can produce cooling air

in order to lower ambient temperature as to

provide more thermal comfort in the indoor

environment.

However, most of the conventional air-

conditioning system will produce some

unwanted noise to the surrounding where the

most of the noise are caused by the operation of

compressor of air-conditioning system whereby

the noise level is around 60 to 70 Decibel (dB).

Eventually, the noise created by the compressor

will cause noise pollution to the environment

since the compressor is running continuously

while the air-conditioning system is switched on.

As a result, the noise pollution will directly

affect the human mental stress, health problem

and even hearing problem due to high noise

level.

Therefore, the main purpose of the research is to

reduce or control the noise level created by air-

conditioning system such that the health and

hearing of human can be preserved effectively.

Basically, there are two main approaches to

reduce or control the noise level which are

passive noise control (PNC) and active noise

control (ANC) [1].

Previously, the passive noise control is to use

the passive sound silencer or the insulation in

order to absorb noise energy so that the output

of system will produce less noise. However, the

passive noise control works best in high

frequency only such as above 250 Hz [1]. This

is because the dimension of sound silencer is

dependent on the wavelength of the noise signal.

If dealing with low frequency noise signal, then

the wavelength of noise signal is longer. This

will cause the dimension or size of the sound

silencer become larger which leads to cost

inefficiency and impracticality.

Therefore, the best approach that deals with low

frequency noise signal is to use ANC method

whereby a power source such as speaker is used

to generate the same amplitude but with anti-

phase sound wave to the input noise signal in

order to create a destructive interference

condition so that both sound waves will be

cancelling each other as to reduce the unwanted

noise [2].

Proceedings of the International Conference on Electrical and Electronic Engineering Telecommunication Engineering, and Mechatronics, Kuala Lumpur, Malaysia, 2015

ISBN: 978-1-941968-18-5 ©2015 SDIWC 14

Several ANC applications have been proposed

by researchers. ANC were used, specifically the

modified-filtered-u LMS algorithm (MFU-

LMS), to minimise the noise of short acoustic

duct application like pipe system of vehicle

engine with high convergence rate [3]. Besides,

the filter-x LMS (FxLMS) has been proposed in

order to minimise the acoustic noise in a yacht

cabin adaptively by using two sub-woofers and

four error microphones [2]. On the other hands,

a modified feedback ANC (MFANC) algorithm

has been proposed by using a low cost

microcontroller unit (MCU) known as PIC24H

to make a low price ANC headset with good

noise cancellation compared to conventional

headset that require high cost digital signal

processor (DSP) [4].

This paper presents an alternative ANC system

known as PC-based ANC system that can be

used to reduce the noise-level of outdoor unit for

air-conditioning application. Normalised LMS

(NLMS) algorithm is proposed for the system in

which its simulation results and the actual

testing at outdoor unit of air-conditioning

system will be discussed in the following

sections.

2 DESIGN AND METHODOLOGY

In this section, the concepts, processes and

algorithms of the proposed ANC system will be

discussed in the following sub-sections.

2.1 Proposed Methodology

PC-based ANC system is a type of ANC system

which applies NLMS algorithm to perform

noise reduction operation. The operation of the

proposed system is illustrated in Figure 1.

First of all, the input microphone is used to

collect the original noise signal from the

outdoor unit of air-conditioning system. Next,

the computer laptop will act as a controller

where it is used to analyse the behaviour and

characteristics of original noise signal obtained

from input microphone such as amplitude,

frequency and phase angle.

After the signal has been analysed, it will send

a corresponding signal to an output speaker in

order to generate an anti-phase signal with same

amplitude and frequency but 1800 degree out of

phase with respect to original noise signal as to

reduce the noise level. The error microphone is

used to collect the residual noise signal after

undergoes the ANC process so that it can

provides feedback to the controller in order to

generate an updated anti-phase signal to reduce

the outdoor unit noise adaptively.

Figure 1: Block diagram of the proposed ANC system

On the other hands, the computation of LMS

algorithm involves three main steps which are

filter output, estimation error and tap-weight

adaptation [5]:

FilterOutput:

� ��

�� 1�

Estimationerror:

# �� $ �� 2�Tapweightadaptation:

� � + 1� � � �� + ,- + ‖� ��‖/ # �� 3�


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From Equation (1), the latest output of the filter

is always dependent on current filter coefficient

which is h(n) and previous input samples which

is x(n –k) so that latest filter output able to

reduce present noise signal of a system such as

the compressor of outdoor unit.

From Equation (2), error e(n) indicates that the

difference between output of unknown system

and filter output in order to verify how much the

noise signal of a system has been reduced by

FIR filter model. For example, if the estimation

error is equal to zero, this meaning that the noise

signal of a system was cancelled totally by

output of filter. Therefore, the main objective is

to minimise the estimation error as low as

possible so that the compressor noise of outdoor

unit will be greatly reduced to the environment.

From Equation (3), α is an adaption constant

where it is used to maximise convergence factor

of NLMS algorithm in order to adapt the noise

signal of outdoor unit faster so that the noise

cancellation performance is increased

effectively when compared with pure LMS

algorithm. Besides, normalisation constant c is

used to stabilise the NLMS algorithm in order to

reduce the estimation error to as low as possible.

As a result, the speed of adaptation for NLMS is

greater than pure LMS algorithm so that the

noise signal of outdoor unit can be reduced

faster.

2.2 Simulation Results

The algorithm is simulated to verify that

whether the NLMS algorithm is able to deal

with the simulated noise signal at multiple

frequencies. From Figure 2, the input noise

signal consists of three different frequencies

signal which is 100, 300 and 500 Hz at different

period from 0 to 3.2 seconds.

From Figure 3, the desired anti-phase signal is

the desired signal that needs to be generated by

the loudspeaker. Basically, the desired anti-

phase signal is the input noise signal with 1800

degree out of phase such that both noise signal

and anti-phase signal are cancelling each other

so as to create a destructive interference and to

contribute minimal residual noise to the

environment.

From Figure 4, the actual anti-phase signal is the

actual signal produced by the speaker to cancel

the noise. Basically, the waveform of actual

anti-phase signal is similar to the desired anti-

phase signal. However, the difference between

both waveforms is the time taken to reach the

desired amplitude. This is because the NLMS

algorithm requires certain time to adapt the

behaviour of noise signal.

From Figure 5, the residual signal is the

remaining noise signal emitted to the

environment that is audible by human after

undergoing the cancellation process. Initially at

0 second, the positive and negative amplitudes

of residual signal are +0.62 and -0.5

respectively due to the NLMS algorithm have

not started to adapt the single frequency noise

with 100 Hz. However right after, both positive

and negative amplitudes of residual signal starts

to decrease gradually until zero at around 0.1

second onwards. The reason of this situation

happened is because the NLMS algorithm starts

to adapt waveform of noise signal at different

frequency.

However at 1 second, the amplitude of residual

signal increases instantly from 0 to +0.8 and -

0.8 respectively because another noise signal

which is a combination of 100 and 300 Hz

together is introduced from 1 to 2 seconds.

Therefore, NLMS algorithm requires certain

time to adapt this new noise signal. As a result,

the amplitude of this residual signal is decreased

gradually after 1 second in order to reach zero at

around 1.15 seconds.

Remarks:

1 = number of adjustable filter order

� = number of instant for impulse response

where 1 � 1 ≥ � ≥ 0

� �� = filter coefficient

� � � �� = tap filter

4 = step size

,= adaption constant where 0 <, < 2

-= normalization constant where - < 1

‖� ��‖/= squared Euclidean norm

� �� = input signal


ISBN: 978-1-941968-18-5 ©2015 SDIWC 16

Similarly at 2 seconds, since another noise

signal combine with 100, 300 and 500 Hz are

introduced at 2 seconds, then NLMS algorithm

require certain time to adapt this new signal

again and then try to reduce it until reach zero at

around 2.25 seconds. Since only involve three

different frequencies noise signal, therefore the

residual noise signal will remain zero after 2.25

seconds onwards until another noise signal is

introduced again.

In summary, the proposed NLMS algorithm

able to reduce or cancel the noise signal with

multiple frequencies successfully. Therefore,

this means that the algorithm is capable of

reducing the noise of outdoor unit of air-

conditioning system since the noise consists of

multiple frequencies in real-world application.

Figure 2: Waveform of input noise signal for NLMS

algorithm

Figure 3: Waveform of desired anti-phase signal for

NLMS algorithm

Figure 4: Waveform of actual anti-phase signal for

NLMS algorithm

Figure 5: Waveform of residual signal for NLMS

algorithm

3 IMPLEMENTATION AND TESTING

In this section, the constructional details and

working principle of the system implementation

at the actual outdoor unit will be illustrated in

the following sub-sections.

3.1 System Implementation

The implementation of the proposed system is

illustrated in Figure 6. In this case, one audio

amplifier circuit has been deployed as an ANC

circuit to generate the anti-phase signal since the

noise source is coming from the actual outdoor

unit system not the simulated noise signal like

preliminary testing. Besides, a smart-phone was

used as a noise-level meter in order to measure

the original noise-level and residual noise-level

of the outdoor-unit system.


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On the other hand, before the commencement of

test, the temperature of the reverberation room

and the anechoic room were set at 27 0C and 35 0C respectively. The operating mode of indoor

unit system is set as cooling mode. Besides, the

anechoic room is an echo-free room where it is

used to absorb all the reflection of sound as well

as isolate all the environmental noise in order to

capture the outdoor unit’s noise completely.

Figure 6: Configuration of PC-based ANC system at

outdoor-unit system

The compressor is generating highest noise

level as it is pumping the refrigerant with very

high pressure whereas this high pressure

refrigerant is very noisy. Therefore, the

microphone and speaker of ANC circuit are

placed inside the outdoor unit where they are

placed near the compressor.

Since the noise generated by compressor is

coming directly to the front side of the outdoor

unit, therefore the speakers must be placed

opposite to noise direction as illustrated in

Figure 7. Besides, the microphone is positioned

facing the compressor to capture the noise

effectively.

3.2 Testing Results

Once the air-conditioning system was switched-

on for cooling mode, the outdoor-unit started to

operate where the compressor started to

generate some noise. The noise-level reduction

at various frequencies of actual outdoor-unit

system is recorded in order to check whether the

proposed PC-based ANC system has been able

to reduce the noise-level in the actual

application. Table 1(a) to 1(c) illustrates the

noise-level reduction obtained.

Figure 7: The placement of microphone and speaker of

ANC circuit inside the outdoor unit system

From Tables 1(a) to 1(c), the noise-level

reduction is the difference between the residual

noise signal after undergoing ANC operation

and the original noise level before undergoing

ANC operation. If the noise-level reduction is

positive value, it means that the ANC circuit

was able to reduce the noise level successfully,

otherwise it will be in negative value. Based on

the table, the highest noise level reduction is 1.9

dB at the noise frequency of 91.7 Hz and the

lowest noise-level reduction is -1.9 dB at noise

frequency of 4.10 kHz. From Table 1(c), the

overall noise level (dBA) is the average noise

level that combines all the noise frequencies

together. The overall noise level before and after

undergoing ANC operation are 57.1 dBA and

56.7 dBA respectively. This means that the

overall residual noise level is relative less than

original noise-level by 0.4 dB which indicates

the proposed ANC system is able to reduce the

outdoor unit noise averagely by 0.4 dB. As a

result, the aim of this project is achieved

successfully.


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Table 1(a): Noise level reduction at noise frequencies

from 46 Hz to 365 Hz in outdoor-unit application

Cooling Mode

Noise

Frequency

(Hz)

Noise level measured by 1 meter

front side of outdoor unit (dB)

Original

noise

level

Residual

noise level

Noise level

reduction

46.0 53.4 51.9 1.5

48.7 52.1 52.9 -0.9

51.7 43.7 43.5 0.2

54.6 44.0 44.4 -0.3

57.9 41.2 40.9 0.2

61.3 39.5 39.9 -0.4

64.9 37.6 38.3 -0.7

68.8 37.3 37.9 -0.6

72.9 38.4 38.4 0.0

77.2 41.0 40.8 0.2

81.8 45.0 45.1 -0.1

86.6 47.9 48.3 -0.4

91.7 49.9 48.0 1.9

97.2 46.0 45.7 0.2

103 43.5 42.4 1.1

109 39.0 38.5 0.5

115 39.5 39.4 0.0

122 40.6 40.8 -0.2

130 43.7 44.2 -0.5

137 45.1 44.7 0.4

145 48.5 47.7 0.8

154 42.0 41.7 0.3

163 40.9 40.9 0.0

173 41.9 41.8 0.1

183 42.2 41.8 0.4

194 44.6 43.6 1.0

205 39.8 39.8 0.0

218 39.7 39.9 -0.2

230 39.9 39.4 0.4

244 39.4 38.9 0.6

259 38.6 38.5 0.1

274 39.8 40.0 -0.2

290 48.8 48.8 0.0

307 41.8 41.4 0.3

325 38.4 38.4 0.0

345 39.0 38.9 0.1

365 38.3 38.3 0.0

Table 1(b): Noise level reduction at noise frequencies

from 387 Hz to 3.07 kHz in outdoor-unit application

Cooling Mode

Noise

Frequency

(Hz)



Original

noise

level

Residual

noise level

Noise level

reduction

387 39.3 39.3 -0.1

410 37.5 37.7 -0.2

434 39.5 39.5 0.0

460 40.1 40.8 -0.7

487 45.5 45.1 0.4

516 37.7 38.0 -0.2

546 37.0 37.1 -0.1

579 37.0 37.1 -0.1

613 38.3 38.9 -0.6

649 36.1 36.3 -0.2

688 36.2 36.0 0.2

729 36.0 35.9 0.1

772 38.0 37.5 0.5

818 37.1 36.5 0.6

866 36.9 37.2 -0.3

917 37.2 37.0 0.2

972 38.2 38.1 0.0

1.03k 38.0 37.8 0.3

1.09k 37.6 37.2 0.3

1.15k 35.9 36.1 -0.1

1.22k 38.2 38.0 0.1

1.30k 37.7 38.0 -0.3

1.37k 37.0 37.2 -0.2

1.45k 35.6 36.2 -0.7

1.54k 36.7 36.7 0.0

1.63k 35.3 34.9 0.5

1.73k 37.4 36.9 0.4

1.83k 36.0 36.4 -0.4

1.94k 33.2 33.7 -0.5

2.05k 32.3 32.3 0.0

2.18k 32.6 32.7 0.0

2.30k 32.2 32.3 -0.1

2.44k 34.4 34.4 0.0

2.59k 33.6 34.4 -0.8

2.74k 46.0 45.4 0.6

2.90k 52.1 51.4 0.7

3.07k 34.6 34.1 0.5


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Table 1(c): Noise level reduction at noise frequencies

from 3.25 kHz to 10.9 kHz in outdoor-unit applications

Cooling Mode

Noise

Frequency

(Hz)



Original

noise

level

Residual

noise level

Noise level

reduction

3.25k 36.3 35.4 0.9

3.45k 39.4 38.4 1.0

3.65k 37.5 37.5 -0.1

3.87k 34.3 35.2 -0.8

4.10k 37.4 39.3 -1.9

4.34k 42.8 42.5 0.2

4.60k 31.4 32.6 -1.3

4.87k 32.9 33.8 -0.9

5.16k 29.2 29.2 0.0

5.46k 30.8 29.7 1.2

5.79k 29.9 30.3 -0.4

6.13k 30.2 30.8 -0.6

6.49k 35.9 36.1 -0.2

6.88k 35.3 35.4 -0.1

7.29k 36.6 36.4 0.2

7.72k 31.0 31.8 -0.8

8.18k 31.3 32.7 -1.4

8.66k 27.6 28.9 -1.3

9.17k 30.2 29.6 0.5

9.72k 28.5 28.3 0.2

10.3k 27.1 26.8 0.4

10.9k 27.9 28.0 -0.1

Overall

noise level

(dBA)

57.1 56.7 0.4

3.3 Effects of Speaker Placement

The purpose of placing speaker in different

location inside the compressor compartment of

the outdoor-unit system is to evaluate the noise

reduction performance in order to check which

location is able to achieve the best performance.

Figures 8, 9 and 10 illustrates such different

placements.

Figure 8: The speaker of ANC circuit is facing the

compressor (1st Placement)

Figure 9: The speaker of ANC circuit is facing upward

(2nd Placement)

Figure 10: The speaker of ANC circuit is facing side of

the compressor (3rd Placement)


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From the noise-level reduction obtained as

illustrated in Figure 11, the 3rd placement of

speaker has the best performance in terms of

overall noise reduction as it has highest overall

noise-level reduction which is 0.9 dBA if

compared with other two placements which are

0.4 dBA and 0.3 dBA respectively.

Based on this result, it can conclude that

different placements of speaker able to reduce

the noise-level at all noise frequencies.

However, the 3rd placement of speaker which is

the speaker that is facing to the side of

compressor is the most effective placement to

reduce the overall noise level of outdoor unit.

As a result, the 3rd placement of speaker is most

suitable placement used to reduce the outdoor

unit noise effectively.

Figure 11: Comparison of overall noise-level reduction

for different placement of speaker in actual outdoor-unit.

4 CONCLUSION

In actual outdoor unit application, the noise

reduction performance in terms of different

placements of speaker were evaluated. The 3rd

placement which is the speaker is facing to side

of compressor has highest performance where

its overall noise level reduction is 0.9 dBA from

the original noise level of 57.1 dBA. As the

proposed method sounds promising, future

investigation includes using a Raspberry Pi as a

real-time system where it can be installed inside

the outdoor unit system practically to perform

more effective noise level reduction.

REFERENCES

[1] Lawrence, J. G. (1997), Active Noise Control: A

Tutorial for HVAC Designers, American Society of

Heating, Refrigerating and Air-Conditioning

Engineers. p. 43-49.

[2] Peretti, P., Cecchi, S., Romoli, L., Piazza, F. (2014),

Adaptive Feedback Active Noise Control for Yacht

Environments, Control Systems Technology, IEEE

Transactions. 22(2). p. 737-744.

[3] Kim, H. W., Park, H.S., Lee, S.K., Shin, K. (2011),

Mechanical Systems and Signal Processing, 25(1). p.

475-484.

[4] Chang, C. Y., Li, S. T. (2011), Active Noise Control

in Headsets by Using a Low-Cost Microcontroller,

Industrial Electronics, IEEE Transactions. 58(5). p.

1936-1942.

[5] Proakis, J. G., Manolakis, D. G. (2007), Digital

signal processing: principles, algorithms, and

applications (4th edition), Upper Saddle River, N.J.:

Pearson Prentice Hall.


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Application of Active Noise Control for Air-Conditioning System

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