During the Matlab part of this course, you already worked with the Matlab and th

Question

During the Matlab part of this course, you already worked with the Matlab and the DAQ board for: Digital output to control analog motors (ML3.2) Analog input for measuring the voltage (ML3.3) rightarrow LV5DAQ_Analog_In_task.vi Displaying both signal and it's spectrum (ML4.2) rightarrow use of FFT_spectrum vi Dealing with noisy signals (ML4.4) Measuring the frequency response of a differentiator (EL8.3) a) Retrieve the Matlab programs mentioned above Doing measurements with the colorimeter through Matlab has three parts: Controlling all settings of the Colorimeter setup. Acquiring data (voltage versus time) Analyzing the data b) Prepare a Matlab code which measures the voltage versus time (block) signal/waveform, comparable to the signals in FA2c. Store voltage and time data.

Explanation / Answer

a) >>>ML 3.2 program for Digital output to control analog motors

% CREATE A SESSION AND ADD 4 OUTPUT CHANNELS

A = daq.createSession('ni');

addDigitalChannel(A,'Dev2','port0/line0:3','OutputOnly')

% DEFINE MOTOT STEPS

% Each cycle of 4 steps turns the motor 72 degrees.

% Repeat this sequence 5 times to rotate the motor 360 degrees.

step1 = [1 0 1 0];

step2 = [1 0 0 1];

step3 = [0 1 0 1];

step4 = [0 1 1 0];

% TURN THE MOTOR COUNTERCLOCKWISE

outputSingleScan(A,step1);

outputSingleScan(A,step2);

outputSingleScan(A,step3);

outputSingleScan(A,step4);

% Repeat sequence 50 times to rotate the motor 10 times counterclockwise.

for motorstep = 1:50

outputSingleScan(A,step1);

outputSingleScan(A,step2);

outputSingleScan(A,step3);

outputSingleScan(A,step4);

end

%ROTATE THE MOTOR 72 DEGREE CLOCKWISE BY REVERSING THE STEPS

outputSingleScan(A,step4);

outputSingleScan(A,step3);

outputSingleScan(A,step2);

outputSingleScan(A,step1);

% Turn off all the lines to allow the motor to rotate freely.

outputSingleScan(A,[0 0 0 0]);

>>>>ML 3.3

readVoltage(A, 'A4')

>>>>>ML4.2

Y = fft(A);

P = abs(Y/L);

P1 = P(1:L/2+1);

P1(2:end-1) = 2*P1(2:end-1);

subplot(2,1,1);plot(t,A);title('ORIGINAL SIGNAL');

xlabel('time');ylabel('Amplitude');

subplot(2,2,1);plot(f,P1);

title('Single-Sided Amplitude Spectrum of S(t)')

xlabel('f (Hz)');ylabel('|P1(f)|');

>>>>>>ML4.4

Fs = 1000; % Sampling frequency

T = 1/Fs; % Sampling period

t=0:0.001:1; % time

X = A + 2*randn(size(t)); % A is corrupted by random noise

plot(1000*t(1:50),X(1:50))

title('Signal Corrupted with Random Noise')

xlabel('t (milliseconds)')

ylabel('X(t)')

>>>>EL8.3

Fs = 1000; % sample rate

dt = 1/Fs; % time differential

t = (0:length(drift)-1)*dt; % time vector

df = designfilt('differentiatorfir','FilterOrder',50,...

'PassbandFrequency',100,'StopbandFrequency',120,...

'SampleRate',Fs);

hfvt = fvtool(df,[1 -1],1,'MagnitudeDisplay','zero-phase','Fs',Fs);

legend(hfvt,'50th order FIR differentiator','Response of diff function');

v1 = diff(drift)/dt;

a1 = diff(v1)/dt;

v1 = [0; v1];

a1 = [0; 0; a1];

D = mean(grpdelay(df)); % filter delay

v2 = filter(df,[drift; zeros(D,1)]);

v2 = v2(D+1:end);

a2 = filter(df,[v2; zeros(D,1)]);

a2 = a2(D+1:end);

v2 = v2/dt;

a2 = a2/dt^2;

subplot(4,1,1);plot(t,v1);title('velocity vs time');

xlabel('time');ylabel('velocity');

subplot(4,2,1);plot(t,a1);title('acceleration vs time');

xlabel('time');ylabel('acceleration');

subplot(4,3,1);plot(t,v1);title('velocity vs time');

xlabel('time');ylabel('velocity');

subplot(4,4,1);plot(t,a1);title('acceleration vs time');

xlabel('time');ylabel('acceleration');

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