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EXAMPLE OF CUBIC B-SPLINE REPRESENTING A MAGNETIC HYSTERESIS LOOP.

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Presentation on theme: "EXAMPLE OF CUBIC B-SPLINE REPRESENTING A MAGNETIC HYSTERESIS LOOP."— Presentation transcript:

1 EXAMPLE OF CUBIC B-SPLINE REPRESENTING A MAGNETIC HYSTERESIS LOOP

2 B is the flux density in Tesla H is the magnetic field strength in Amps/meter BACKGROUND

3 Given a ferromagnetic core wrapped in wire Apply a square wave voltage Results in a magnetic hysteresis loop  Increasing voltage  Decreasing voltage

4 MODELING THIS LOOP Accurate hysteresis loop model can save time Use a cubic spline approximation based on experimental data B can be determined for any H value

5 Paint application is very useful Use the cursor to find pixel points* Select as many points as we wish for the model Be careful! Pixel origin is in upper left corner GET TO THE POINT S *

6 SEE IT IN ACTION

7 Find y of any point (x-hat) on the spline Binary search algorithm to find polynomial Specify end conditions Solve system of equations for coefficients: a,b,c,d ONCE YOU HAVE THE POINTS P 3 (x hat ) = a 3 + b 3 (x hat - x 3 ) + c 3 (x hat - x 3 ) 2 + d 3 (x hat - x 3 ) 3

8 The binSearch() function assumes all points are given with increasing x values Two sets of points are defined  One for positive voltage  One for negative voltage Splint() function does the rest  Use zero slopes at endpoints for this case  Plot or display values The binSearch() function assumes all points are given with increasing x values Two sets of points are defined  One for positive voltage  One for negative voltage Splint() function does the rest  Use zero slopes at endpoints for this case  Plot or display values MATLAB AND SOME LOGIC

9

10 DIFFERENT END CONDITIONS

11 % A and B must be entered with ascending x’s A = [100,333;129,307;167,264;210,192;254,143; ,111;345,87;377,76;423,62;478,53]; B = [100,333;128,330;196,314;262,287;302,262; ,223;373,181;413,120;455,75;478,53]; % Enter the origin pixel point O = [290,194]; % Enter the points at the first positive tic marks tic_x = [377,194]; % 50 tic mark to right of origin tic_x_label = 50; tic_y = [290,164]; % 0.1 tic mark up from origin tic_y_label = 0.1; n = 100; % number of xhats to compute % (higher means smoother curve) scx=tic_x_label/abs(tic_x(1)-O(1)); scy=tic_y_label/abs(tic_y(2)-O(2)); AA=(A-ones(length(A),1)*O)*[scx 0;0 -scy]; BB=(B-ones(length(B),1)*O)*[scx 0;0 -scy]; plot(AA(:,1),AA(:,2),'b*') hold on; grid on; plot(BB(:,1),BB(:,2),'r*') AAintx = linspace(min(AA(:,1)),max(AA(:,1)),n); BBintx = AAintx; AAinty=splint(AA(:,1),AA(:,2),AAintx,0,0); BBinty=splint(BB(:,1),BB(:,2),BBintx,0,0); plot(AAintx,AAinty,'b') plot(BBintx,BBinty,'r') THE CODE

12 splint Cubic-spline interpolation with various end conditions Synopsis: yhat = splint(x,y,xhat) yhat = splint(x,y,xhat,endType) yhat = splint(x,y,xhat,fp1,fpn) [yhat,a,b,c,d] = splint(x,y,xhat) [yhat,a,b,c,d] = splint(x,y,xhat,endType) [yhat,a,b,c,d] = splint(x,y,xhat,fp1,fpn) Input: x,y = vectors of discrete x and y = f(x) xhat = (scalar or vector) x value(s) where interpolant is evaluated endType = (string, optional) either 'natural' or 'notaKnot'; used to select either type of end conditions. End conditions must be same on both ends. Default: endType='notaKnot'. For fixed slope end conditions, values of f'(x) are specified, not endType fp1 = (optional) slope at x(1), i,e., fp1 = f'(x(1)) fpn = (optional) slope at x(n), i,e., fpn = f'(x(n)); Output: yhat = (vector or scalar) value(s) of the cubic spline interpolant evaluated at xhat. size(yhat) = size(xhat) a,b,c,d = (optional) coefficients of cubic spline interpolants CODE: SPLINT() PARAMETERS


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