MATLAB: How to convert accelerometer data from excel into frequency

mpu 6050vibrational frequency

Hello I am trying to convert the accelerometer data I collected from the MPU 6050 in the Z axis to vibrational frequency. I am powering a small vibration motor at 82 duty cycle expected 130 hz according to the data sheet. I got some advice from my teacher to get a live recording instead of my previous post. So I got the live value in ardunio and wrote it to excel. Using this previous post "How to use FFT in matlab using importated data in time domain excel file." I got my data. However I am not even close to my expected frequency. Can someone help me figure out what is wrong?

I used this excel file the first column is time in miliseconds and the last column is what im interested in which is accel readings in the Z axis in gravitational force.

My current output is in Z Readings below but im expecting something closer to the image below with the frequency at 130 hz.

Best Answer

The sampling frequency is too low to detect a 130 Hz vibration:

A = readmatrix('DutyCylce82Vals2.csv');
A(:,1) = A(:,1)*1E-3;                                       % Convert To Seconds
Ts1 = mean(diff(A(:,1)));
Fs1 = 1/Ts1;

This calculates the mean sampling frequency (note that the signal is also not regulalrly sampled, and it needs to be) to be about 41 Hz. In order to detect a 130 Hz vibration, the sampling frequency must be at least 260 Hz (sampling interval at most 3.84 ms), and ideally much higher than that, for example 300 Hz, with a sampling frequency of 3.33 ms.

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MATLAB: Finding the sampling frequency from the following

Sampling frequency is 1 divided by sample rate.

1 / (M seconds per sample) = ? samples per second

and samples per second is Hz .

MATLAB: 2nd order butterworth filter and PCA

With respect to downsampling, use the resample function. I wouldn’t downsample the signal unless you absolutely must for some reason. Most of the time, I use resample to create a unifformly-sampled signal from a non-uniformly-sampled signal, since all signal processing requires uniform sampling. If you do decide to downsample, be sure to change ‘Fs’ to reflect that, if you’re doing the filtering after the downsampling.

I don’t understand this assignmment:

srate = 5000;

If ‘srate’ is your sampling rate, it’s actually ‘Fs’, the sampling frequency, so assign it to ‘Fs’ instead. That’s also the indirect cause of the error you’re getting.

With that correction, the rest of your code should work. (It looks like I wrote it!)

I would also make two change these assignments:

[b,a] = butter(n, Wn);                                   % Calculate Filter Coefficients

[sos,g] = tf2sos(b,a);                                   % Convert To Second-Order Sections For Stability

to:

[z.p,k]] = butter(n, Wn);                                % Calculate Filter Coefficients
[sos,g] = zp2sos(b,a);                                   % Convert To Second-Order Sections For Stability

That will design a better filter that the code I originally wrote.

And of course, use filtfilt to do the actual filtering.

Best Answer

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MATLAB: Finding the sampling frequency from the following

MATLAB: 2nd order butterworth filter and PCA

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