BACKGROUND OF THE PROJECT
AIM - To develop a very low cost system, which can be
used in the Electromagnetic Compatibility (EMC)
testing of all electronic equipments in a large scale
manufacturing industry and also for the purpose of
Education.
Here it is proposed to carry out the EMC test in open
space along with a noise cancellation algorithm, instead
of doing it inside an anechoic chamber.
INTRODUCTION
Nowadays Electromagnetic compatibility (EMC)
must be maintained in all electronic equipments
manufactured.
Electromagnetic Compatibility (EMC) is the ability of
electrical or electronic equipment/systems to
function in the intended operating environment
without causing or experiencing performance
degradation due to unintentional EMI.
SOURCE
EMI
VICTIM
PROBLEM DEFINITION
Very costly setup, limited size of the Device Under
Test, etc.,
Cost of an anechoic chamber of dimension 52’’ by
23’’ by 12’’ is 100,000$.
The construction and maintenance complexity of
the anechoic chamber is very high.
Many educational institutions are not affording
anechoic chamber due to high cost.
1, 2 - Broadband Antenna (Log Periodic Dipole Array),
 5 - Spectrum Analyzer.
(A) – Impedance Matching network.
VIEW RESULTS
IMPLIMENTATION
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DUT
AMBIENT NOISE
WHY LPDA?
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 An antenna forms the interface between the free
space and the transmitter or receiver. The choice of an
antenna normally depends on factors such as gain
and the bandwidth an antenna can offer.
 Log-periodic dipole array (LPDA) antennas offer a
wider bandwidth and can have gains as high as 10 dB.
 The other advantage of this antenna is that its
input impedance can be set to the desired value by
selecting the appropriate diameter for the dipole
elements.
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ANTENNA DESIGN
DESIGN INPUTS
Lowest frequency
Highest frequency
Structure Constant Tau
Structure Constant Sigma
Feeder Z
Feeder Dia.
500.0
1000.0
0.80
0.17
50
1.26
MHz
MHz
ohm
inches
DESIGN OUTPUTS
Number of Elements (N)
Array Gain (dBi).
Structure constant sigma
Boom Length
length of longest element
diameter of longest element
stub length
Feeder separation
8
6.3
0.17
15.39
11.80
0.25
2.95
1.03
dBi
inches
inches
inches
inches
inches
ELEMENT POSITION AND LENGTH DATA
(inches)
(inches)
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(inches)
(inches)
Element Number
Length
Half length Separation Position
8
11.803
5.902
7
9.443
4.721
4.013
4.013
6
7.554
3.777
3.210
7.224
5
6.043
3.022
2.568
9.792
4
4.835
2.417
2.055
11.847
3
3.868
1.934
1.644
13.490
2
3.094
1.547
1.315
14.805
1
2.475
1.238
1.052
15.857
0.000
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SPECTRUM ANALYZER SET UP
The signal from the antenna is analog in nature. It
has to be converted into digital signal for further
processing, which is achieved by using spectrum
analyzer.
The Spectrum Analyzer is remote controlled by
using a Personal Computer. RS-232 is used to
connect the spectrum analyzer with the P.C.
Remote control software of GWGSP 810 is used
for this purpose.
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Interface Between Spectrum Analyzer
and P.C.
RS 232
SPECTRUM
ANALYZER
P.C.
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Remote Control Software of GWGSP810
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EMI (GUI) WINDOW
ADAPTIVE FILTERING
Filter input
Desired input
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ADAPTIVE FILTER
(BDLMS)
Error Signal
Adaptive filtering is used to remove the ambient
noises.
 In adaptive filtering the filter coefficients are
updated for arrival of every new sample such that
the mean square error value is maintained
minimum.
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ANTENNA BANDWIDTH MEASUREMENT
DUT
+

NOISE
NOISE 
TEST SIGNAL INPUTS
DUT
+

NOISE
NOISE 
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CLMS Output
LMS Output
BDLMS Output
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REAL TIME SIGNAL INPUTS
DUT
+

NOISE
NOISE 
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LMS Output
CLMS Output
BDLMS Output
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COMPARISON RESULTS
LMS Vs CLMS
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CLMS Vs BDLMS 
LMS Vs BDLMS 
IMPLEMENTATION
This project can be implemented in real time
working environment in either of the two ways.
The TYPE-I implementation – Application
dependent system (Can be used in Industries).
ADVANTEGES
No increase in the manufacturing cost except a
change in the present assembly line process.
Reduction in Manufacturing cost of the electronic
goods.
Reduction in maintenance complexity.
The TYPE-II implementation – Application
independent system (Can be used for educational
purposes).
ADVANTEGES
Very low cost portable system which can be
afforded by all educational institutions.
A single system can be used to study all the effects
involving the usage of anechoic chamber.
Easy handling and simplicity.
There is no restriction in the size of DUT.
FUTURE WORK:
The capturing of EMI signal will be done in Time
domain to reduce the measurement time.
To improve the efficiency of the entire system, the
Signal processing step is going to be implemented
in the time domain.
We have also planned to improve the efficiency of
ambient noise cancellation process.
REFERENCE
 [1]
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P.S.R.Diniz, Adaptive Filtering: Algorithms and Practical
Implementation. Kluwer Academic Press, Boston, MA, USA, 1997.
[2] S.Haykin, Adaptive Filter Theory. Prentice Hall, Englewood Cliffs, NJ,
USA, 3rd edition, 1996.
[3] T.Shinozuka, and A.Sugiura, “Reduction of Ambient Noise in EMI
Measurement,” IEEE International Symposium On Electromagnetic
Compatibility Digest, September 8-10, Nagoya, Japan, pp. 24-28, 1989.
[4] P.Parhami, M.Marino, S.Watkins, and E.Nakauchi, “Innovative
precompliance test methodology using ambient cancellation and
coherence detection techniques,” IEEE International Symposium On
Electromagnetic Compatibility, August 2-6, Seattle, USA, vol. 2, pp.
1022-1025, 1999.
[5] S.Braun, M.Al-Qedra, and P. Russer, “A novel Realtime Time-domain
Measurement System based on Field Programmable Gate Arrays,” 17th
International Zurich Symposium On Electromagnetic Compatibility,
Feb. 27 -March 3, Singapore, pp. 501-504, 2006. Best Student Paper.
 [6]
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J.A.Apolindrio Jr., M.L.R. de Campos and P.S.R.Diniz,
“Binormalized Data-reusing LMS algorithm with optimized stepsize
sequence” 2004.
[7] J.A.Apolindrio Jr., M.L.R. de Campos and P.S.R.Diniz, “Convergence
analysis of the Binormalized Data- Reusing LMS Algorithm,”
Proceedings of the European
Conference on Circuit Theory and Design, Budapest, Hungary, 1997.
[8] B.Widrow, J.McCool, and M.Ball, “The Complex LMS Algorithm,”
Proceedings of the IEEE, vol.63, no.4, pp. 719-720, April 1975.
[9] Arnd Frech, Amer Zakaria, Stephan Braun, Peter Russer “Ambient
Noise Cancelation with a Time domain EMI Measurement System
using Adaptive Filtering”, Institute for High-Frequency Engineering,
Munich, Germany.
THANK YOU