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I have data from a vibration experiment on a structure. This data was obtained by attaching an accelerometer to a FFT analyser, which records the data at a high sampling rate (typically in kHz range) and can also perform real-time FFT of the recorded data.

sample signal and its FFT

The image above shows the recorded signal below and the FFT above. The FFT shows all the dominant frequencies in the original signals.

What more patterns/ important data points can I discern from this data, that might have utility ?

For example, one being, the RMS value of the signal. What else ?

Also, the recorded data here as a mat file, which can be loaded in matlab, the data in a variable called Track1.

The physics of the problem: The data is collected from a shake table, a rigid platform, that oscillates back and forth, so the sharp edges in the original signal periodically, representing the point of return.

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Remember that you are observing a system (the structure) driven by an input (shake table). Assuming linearity, the FFT result was caused by the shake table and the structure. You should be able to pick out the various components to identify mechanical resonances in the structure. For instance, you should see a strong component at the frequency of the shake table. Exactly how to do this in more detail is out of my domain, as I am an electrical, not mechanical, engineer.

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  • $\begingroup$ I would eventually put an accelerometer on a structure, which would be fastened to the shake table, the results above are for accelerometer attached directly to shake table. So, ideally i should see a sinusoid on the lower graph (i.e a - t graph) and a single peak in the fft, at the frequency of excitation, but our shake table seems to be a sum of several frequencies. What other patterns / data-point are discernible from the data above ? $\endgroup$
    – Chintan Pathak
    Aug 11 '15 at 8:19
  • $\begingroup$ A quick question Chintan. In the time domain, is the acceleration of the shake table sinusoidal or more like a square wave? $\endgroup$
    – Richard Lyons
    Sep 10 '15 at 9:57
  • $\begingroup$ If there is an input signal, then you could look at this document in order to construct a transfer function. $\endgroup$
    – fibonatic
    Oct 9 '15 at 22:38

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