Detection of Defective Element in a Space Borne Planar Array with Far-Field Power Pattern Using Particle Swarm Optimization

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1 IOSR Joural of Electroics ad Commuicatio Egieerig (IOSR-JECE e-issn: ,p- ISSN: Volume, Issue 3, Ver. IV (Ma - Ju.2015, PP Detectio of Defective Elemet i a Space Bore Plaar Arra with Far-Field Power Patter Usig Particle Swarm Optimizatio Vishal Puri 1, Shaveta Puri 2 1 Departmet of ECE, CoET, BGSB Uiversit, Rajouri, Idia. 2 Departmet of ECE, CoET, BGSB Uiversit, Rajouri, Idia. Abstract: Particle swarm optimizatio techique is a soft computig approach that ca be used i variet of egieerig applicatios. I this paper the optimizatio techique viz., PSO is used i detectio of defective elemet i space bore plaar arra. Detectio of defective elemet i a space bore applicatio requires optimized approach A calibratio sstem ca be used i satellite itself but i case of a failure, calibratio ca also be defective. So the good solutio will be locatio of failig elemet from exteral data ad optimizatio scheme ca be used for the detectio. PSO is used as a optimizatio tool that detects the defective elemet usig power values that are beig, received. Kewords: PSO, IE3D, Plaar-arra (PA, Cost-fuctio. I. Itroductio Particle swarm Optimizatio is used as optimizatio scheme for the detectio of failed elemet i a arra. A satellite has arras with ma elemets ad PSO optimizatio techique miimizes the cost fuctio, which is differece of power error ad fudametal power equatio represetig defective elemet i terms of positio. Now whe a elemet is completel defective PSO is used to detect the defective locatio values ad the result is compared with alread desiged values i order to fid the defective elemet. II. Particle Swarm Optimizatio PSO is a populatio based iterative parallel search algorithm that models social behavior of a flock of birds. Sice its itroductio i [1], PSO has see ma modificatios ad has bee adapted to differet eviromets [2]. Ma versios of PSO have bee proposed ad applied to solve optimizatio problems i diverse fields [2]. PSO cosists of a populatio (or a swarm of s particles, each of which represets a potetial solutio. The particles explore a -dimesioal solutio space i search of the global solutio, where represets the umber of parameters to be optimized, x ad coordiates of a ode this problem. Each particle i occupies a positio Xid ad moves with a velocit V id, 1 i s ad 1 d. Fitess of a particle is determied from its positio i the search space. The fitess is defied i such a wa that a particle closer to the global solutio has higher fitess value tha a particle that is far awa. Each particle has a memor to store pbest id, the positio where it had the highest fitess, ad gbest, the maximum of pbest id of all particles. The gbest particle represets the best solutio foud so far. At each iteratio k, velocit vid ad positio Xid of each particle are updated usig (1 ad (2. vid(k + 1 = w.v id (k +c1. rad 1.(pbest id X id + c2. rad 2 (gbestd Xid (1 X id (k + 1 = X id (k + v id (k + 1 (2 Here, rad1 ad rad2 are radom umbers that rage betwee 0 ad 1 with a uiform distributio.. III. Implemetatio Let us cosider a plaar arra of N idetical ad equall orieted elemets. Assumig that the elemets are located over the x- plae, the far field patter, expressed i db, ca be calculated usig the followig expressio [5]: N 1 P(, log ( fe(,. I e jk si ( xcos si 2 Where I is the relative excitatio of the -elemet located at the positio give b( x,, fe(θ, φ is the elemet patter, ad (θ, φgives the agular positio of the field poit [5-7]. Usig a cost fuctio, the method compares the Error i measured radiatio patter with that correspodig to the arra with a give cofiguratio of failed/correct elemets. The optimizatio techique used is PSO. The miimizatio helps i detectig failed elemets. DOI:.9790/ Page

Detectio of Defective Elemet i a Space Bore Plaar Arra with Far-Field Power Patter. J [ P P(, ] Where J is a cost fuctio, P is the value of error. P (θ, φ is the value of the power patter of elemet.

2 Detectio of Defective Elemet i a Space Bore Plaar Arra with Far-Field Power Patter. J [ P P(, ] Where J is a cost fuctio, P is the value of error. P (θ, φ is the value of the power patter of elemet. J [ P P(, ]. The miimizatio of this cost fuctio b meas of PSO algorithm allows us to calculate that positio where the value of error is equal to defective elemet power. 2X2 plaar arra is desiged so x ad has specific value i the followig equatio, N jk si ( x cos si (, log ( (,. P 2 fe I e 1 Hece for space bore applicatio there are two coditios. 1. Arra etwork workig properl. 2. Arra etwork is damaged. 1 Arra etwork workig properl. All the elemets givig desired result ad earth statio gets the power which is matchig with desired results, This meas value of P is equal to zero. 2 Arra etwork damaged. Earth statio has far- field power patter sa P 8 whe all the elemets are workig properl, ad whe there is fault i sa a elemet & power of arra is P 7 The error is equal to P = P8 - P 7 3 Applig Particle swarm Optimizatio optimizatio scheme. Elemets are take ad satellite arra etwork is optimized ad the optimizatio is workig for two coditios. DOI:.9790/ Page

3 Detectio of Defective Elemet i a Space Bore Plaar Arra with Far-Field Power Patter. 4 Arra workig properl. PSO whe Arra etwork workig properl, I this case value of P 8 = P 7. P is equal to zero, meaig thereb earth statio is gettig desired values. 5 Arra ot workig properl. Particle Swarm optimizatio whe icorporated i arra etwork, whose elemet is damaged, performs cost fuctio miimizatio ad gives positio value where defective elemet is located. The miimizatio is related to positio, which meas whe miimizatio is achieved, positio is oted which is the positio of defective elemet. 6 Data from IE3D. IE3D is used i atea desig, usig IE3D,2X2 plaar arra is desiged. Far-field patter is simulated usig IE3D.Data whe arra workig properl is take, the damagig elemets oe b oe the far field power value is oted. The error fuctio, which is called Last fuctio, is miimized usig PSO. Applig PSO, for miimizatio of cost fuctio J. J [ P P(, ] Where, N P(, log ( (,. jk si ( x cos si 2 fe Ie 1 Cost fuctio has positio parameter x ad. O miimizatio of cost fuctio b PSO algorithm this leads to desired positio of defective elemet. For testig a elemet is radoml made defective ad the results are compared. 7 Results. At frequec 3.8 GHz, we desig 2x2 plaar arra ad we get above data from IE3D, Radiated power from the arra for various cases as desiged from IE3D is as follows ELEMENT POWER RADIATED ALL CORRECT. FROM ARRAY (W 4 TH INCORRECT (W 3 rd INCORRECT (W 2 d INCORRECT (W 1 st INCORRECT (W Power radiated b elemets for PA. The value of error is calculated which meas, (Whe all 4-elemets are correct, radiated power-(whe a elemet is icorrect, radiated power. I other words, P = Pcorrect Pdefective. Thus calculatig the error b usig the equatio, we get the value of error. ELEMENT POWER ( 4 TH INCORRECT (W 3 rd INCORRECT (W 2 d INCORRECT (W 1 st INCORRECT (W Error i power for PA. Applig data to Particle swarm Optimizatio tool for plaar arra. Now the PSO we take a fuctio which is J J [ P P(, ] P = Error arrived from IE3D ad P(, =Power equatio of idividual patter. Where N P(, log ( (,. jk si ( x cos si 2 fe Ie 1 DOI:.9790/ Page

4 Detectio of Defective Elemet i a Space Bore Plaar Arra with Far-Field Power Patter. This meas J has a value of, N jk si ( x cos si ( log ( (,. J P 2 error fe I e 1 I this equatio we substitute the values of =45, =45, I =1, k=1, ad the fe(, Is calculated which as, ( /82.16 fe(, =, the we substitute the value of x ad The aim of PSO is to miimize the value of J which meas with miimizatio, as radom positio. N jk si ( x cos si 2 ( P error log ( fe(,. I e 0 1 This meas, N jksi ( x cos si 2 log ( (,. P fe I e error 1 so, PSO perform miimizatio ad calculate positio where it matches the result i this wa calculated.these results are tabulated ad compared whe radoml a elemet is made defective. The results are, ELEMENT POSITION X-AXIS POSITION Y-AXIS 4 TH INCORRECT RD INCORRECT ND INCORRECT ST INCORRECT Table-6.21 Positio arrived from BFA for PA. Particle Swarm Optimizatio results Fault i 4 th elemet:- To get started, select MATLAB Help or Demos from the Help meu. ENTER THE VALUE OF = Perror = ENTER THE VALUE OF THETA1 =45 theta1 = 45 fe1 = ENTER THE VALUE OF PHY1 =45 ph1 = 45 XAXIS = YAXIS = Eter the value of X-POSITION positio Eter the value of Y-POSITION positio as = **********************FAULT IN ELEMENT 4************************** >> x ad is DOI:.9790/ Page

5 Y-AXIS POINT Detectio of Defective Elemet i a Space Bore Plaar Arra with Far-Field Power Patter. 0 MINIMIZATION VALUE POSITION OF DEFECTIVE ELEMENT X- AXIS POINT Figure 6.9 Positio ad miimizatio values for defective elemet 4 for plaar arra. The results Thus the results PSO are tabulated below. DEFECT ELEMENT POSITION (X-AXIS POSITION (Y-AXIS O/P BFA D D4 D D3 D D2 D D1 Results from PSO for PA. The results from Particle swarm optimizatio scheme give the positio that is value of x ad, which is i accordace to miimizatio of cost fuctio J. The results whe compared with desiged values cofirms that the PSO scheme ca be used to fid defective elemet i space bore arra. IV. Coclusios The defective elemet detected is as desired. Thus this algorithm ca be used to achieve optimizatio i space bore applicatio ivolvig umerous elemets i a arra. Detectio of defective elemet usig PSO tool with ol far field power values make defective elemet detectio eas with available data. The results suggests that the defective elemet detectio usig Particle Swarm optimizatio tool o basis of ol far field power values is a great boo i all space bore applicatios ivolvig arra. DOI:.9790/ Page

6 Detectio of Defective Elemet i a Space Bore Plaar Arra with Far-Field Power Patter. Refereces [1]. J. Keed ad R. Eberhart, Particle swarm optimizatio, i Proc.IEEE It. Cof. Neural Networks, vol. IV, Perth, Australia, Ja. 1995,pp [2]. X. Hu, Y. Shi, ad R. Eberhart, Recet advaces i particle swarm, i Proc. CEC2004 Cogress o Evolutioar Computatio, vol. 1, Jue 2004, pp [3]. Raghavedra V. Kulkari, Gaesh Kumar Veaagamoorth, Particle swarm optimizatio i wireless sesor etwork: A surve Sstems, Ma, Cberetics, Part C: Applicatios ad Reviews, IEEE Trasactios vol 41, page , March 2011 [4]. S. Mishra, B, K, Paigrahi, M. Tripath, A hbrid adaptive-bacterial-foragig ad feedback liearizatio scheme based d-statcom,iteratioal Coferece o Power SstemTecholog,PowerCo,Volume1, Issue, 21-24,Nov.2004 Vol.1,Page(s: [5]. J.A.Rodriguez,F.Ares,Fidig defective elemets i plaar arra usig geetic algorithm, Progress i Electromagetic Research, PIER 29,,2000, pages [6]. Yeo,B. ad Y.Lu, Arra failure correctio with a geetic algorithm, Ateas ad Propagatio, IEEE Trasactios o Volume 47, Issue 5, Ma 1999 Page(s: [7]. T. J. Peters, A cojugate gradiet-based algorithm to miimize the side lobe level of plaar arras with elemet failures, IEEE Tras. Ateas Propagat., vol. 39, Oct. 1991, pp DOI:.9790/ Page

Particle Swarm Optimization Design of Optical Directional Coupler Based on Power Loss Analysis

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