Estimating the damping ratio from the waveform graph

AI Thread Summary
The discussion focuses on estimating the damping ratio, forced frequency, and natural frequency from a waveform graph. The logarithmic decrement method is used to calculate the damping ratio, with initial estimates of peak values leading to a damping ratio of approximately 0.0356 and a damped frequency of 2 kHz. However, discrepancies arise when simulating the results in PSpice, as the simulated damping ratio appears too low compared to the expected waveform. Participants clarify their calculations and peak selections, leading to the realization that absolute peak values were incorrectly used instead of relative values from the baseline. The conversation concludes with a request for assistance in estimating axis sensitivities for the waveform plot.
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Homework Statement



From the waveform shown below, estimate
a) the damping ratio ζ (you may compare response with a standard chart);
b) the forced or damped frequency of oscillation; and
c) the natural or undamped frequency of oscillation.
img_0041-jpg.114478.jpg

Homework Equations



Since the waveform is under damped, I'm attempting to use the logarithmic decrement method, described here: http://en.wikipedia.org/wiki/Logarithmic_decrement

\sigma = \frac{1}{n}\ln\frac{x(t)}{x(t + nT)}
\zeta = \frac{1}{\sqrt{1 + \left(\frac{2\pi}{\sigma}\right)^2}}
f_d = \frac{1}{T}
f_n = \frac{f_d}{\sqrt{1 - \zeta^2}}

The Attempt at a Solution



I have estimated the first two peaks from the graph as:
p_1 = 0.438\text{ V} \text{ at } 0.27\text{ ms}
p_2 = 0.350\text{ V} \text{ at } 0.77\text{ ms}

Using the above equations:
\begin{align}<br /> \sigma &amp;= \ln\left(\frac{p_1}{p_2}\right)\\<br /> &amp;= \ln\left(\frac{0.438}{0.350}\right)\\<br /> &amp;= 0.224\\<br /> \text{and}\\<br /> \zeta &amp;= \frac{1}{\sqrt{1 + \left(\frac{2\pi}{0.224}\right)^2}}\\<br /> &amp;= 0.0356\\<br /> f_d &amp;= \frac{1}{0.77 \times 10^{-3} - 0.27 \times 10^{-3}}\\<br /> &amp;= 2\text{ kHz}\\<br /> f_n &amp;= \frac{2000}{\sqrt{1 - 0.0356^2}}\\<br /> &amp;= 2001\text{ Hz}<br /> \end{align}<br />

The problem is that I'm not sure I believe the results. I'm trying to verify the results by putting them back into the second order characteristic equation:
\begin{align}<br /> \text{C.E.} &amp;= s^2 + 2\zeta{\omega}_{n}s + {\omega}_{n}^2\\<br /> &amp;= s^2 + (2 \times 0.0356 \times 2\pi \times f_n)s + (2\pi \times f_n)^2\\<br /> &amp;= s^2 + 895s + 158071624<br /> \end{align}<br />
then simulating that with a Laplace block in PSpice. However, the simulated waveform doesn't match the one above. The frequency is correct, but the damping ratio is too low -- playing about with the numbers, I find I need to increase the damping ratio to approximately ##2.8\zeta## to get the waveform looking correct.

I don't know if there is a problem in my method and the results are wrong, or if my simulation is in error (or possibly both!). Can someone please help?

Thanks,
Chris
 
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I got different results. My fn was about 2009 Hz and my ζ = 0.0974. I estimated fd = 2000 Hz and peak ratio = 1.85.

I can't check your math since you did not define n and σ. You were aware that x = 0 corresponds to 250 mV, right?

I did notice that (my ζ)/(your ζ) was about the number you thought it should be.
 
I didn't consider ##x(0)##. I guess it makes sense as the wave seems to be settling to 250 mV, but I don't see how it is relevant. As I understand the method, you estimate based on two successive positive peaks, which I have done.

Which peaks did you use and what did you estimate their coordinates to be?

In my calculations I chose the first two consecutive peaks, thus ##n = 1## (I should have been more explicit about that). Why do you say that I haven't defined ##\sigma## though? I did show my working, repeated below:
\begin{align}<br /> \sigma &amp;= \ln\left(\frac{p_1}{p_2}\right)\\<br /> &amp;= \ln\left(\frac{0.438}{0.35}\right)\\<br /> &amp;= 0.224<br /> \end{align}<br />
 
Ah! Don't worry, I've figured out where I've gone wrong, helped by your comment about ##x(0)##. I've incorrectly used the absolute peak values, rather than their relative values from ##x(0)##.

Thanks for the help!
 
Uploading waveform image again, since the link in the original post is now broken and I can't figure out how to edit the post.
IMG_0041.jpg
 
does anyone know how to estimate the x and y-axis sensitivities if you were given this plot?
 
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