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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.

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Presentation on theme: "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."— Presentation transcript:

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2 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.

3 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.

4 SOURCE VICTIM EMI

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6 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.

7  1, 2 - Broadband Antenna (Log Periodic Dipole Array),  5 - Spectrum Analyzer.  (A) – Impedance Matching network. VIEW RESULTS IMPLIMENTATION

8 DUT AMBIENT NOISE HOME

9 WHY LPDA? HOME  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.

10 ANTENNA DESIGN DESIGN INPUTS Lowest frequency500.0MHz Highest frequency1000.0MHz Structure Constant Tau0.80 Structure Constant Sigma0.17 Feeder Z50ohm Feeder Dia.1.26inches DESIGN OUTPUTS Number of Elements (N)8 Array Gain (dBi).6.3dBi Structure constant sigma0.17 Boom Length15.39inches length of longest element11.80inches diameter of longest element0.25inches stub length2.95inches Feeder separation1.03inches HOME

11 ELEMENT POSITION AND LENGTH DATA (inches) Element NumberLengthHalf lengthSeparationPosition 811.8035.9020.000 79.4434.7214.013 67.5543.7773.2107.224 56.0433.0222.5689.792 44.8352.4172.05511.847 33.8681.9341.64413.490 23.0941.5471.31514.805 12.4751.2381.05215.857 HOME

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14 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. HOME

15 Interface Between Spectrum Analyzer and P.C. SPECTRUM ANALYZER P.C. RS 232 HOME

16 Remote Control Software of GWGSP 810 HOME

17 EMI (GUI) WINDOW HOME

18 ADAPTIVE FILTERING  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. ADAPTIVE FILTER (BDLMS) Filter input Desired input Error Signal HOME

19 DUT +  NOISE ANTENNA BANDWIDTH MEASUREMENT NOISE  HOME

20 DUT +  NOISE TEST SIGNAL INPUTS NOISE  HOME

21 CLMS Output LMS Output BDLMS Output

22 HOME REAL TIME SIGNAL INPUTS DUT +  NOISE NOISE 

23 HOME LMS Output CLMS Output BDLMS Output

24 HOME LMS Vs CLMS COMPARISON RESULTS

25 HOME CLMS Vs BDLMS  LMS Vs BDLMS 

26 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.

27  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.

28 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.

29 REFERENCE  [1] 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.

30  [6] 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.

31 THANK YOU


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