Why Are Mean and RMS Values Close to 30 in Dynamic Signal Analysis?

[krnhseya]

Homework Statement

comment on nature and meaning of results in terms of analysis of dynamic signals.
(why do i see these results and what should we do to increase the accuracy of these two values)

Homework Equations

y=30+(2cos(6*pi*t))

both mean value and rms value come out to be very close to 30ish. (29~31)

The Attempt at a Solution

i really have no idea...rounding errors?

 

[Delphi51]

mean and rms values have to do with signals that vary with time.
They are different ways to average the signal over time.
They normally give quite different answers. For example, the 120 V on a home plugin would is 120 V RMS but has a mean of zero volts.
If you look up the term "root mean square" in your textbook and/or internet, you should find some examples to build up your experience to the point where you can say something about a signal that has a mean of 29 and and rms of 31.

 

[nlightner]

The mean value and rms value are two commonly used measures in signal analysis. The mean value is a measure of the average value of a signal, while the rms value is a measure of the effective or "root mean square" value of a signal.

In the given equation, the mean value and rms value are both close to 30, which is expected since the constant term in the equation is 30. This means that the signal has an average value of 30, and an effective value of approximately 30 as well.

In terms of analysis of dynamic signals, these results can provide information about the overall trend and magnitude of the signal. However, they may not give a complete picture of the signal's behavior over time. For example, a signal with a mean value of 30 and an rms value of 30 could have a different shape and frequency content compared to a signal with the same mean value but a higher rms value. Therefore, it is important to also consider other measures and techniques, such as Fourier analysis, to fully understand the dynamic behavior of a signal.

To increase the accuracy of the mean value and rms value, it is important to have a large number of data points and to minimize any sources of error, such as rounding errors or noise in the signal. Additionally, using more advanced signal processing techniques, such as digital filtering, can help to improve the accuracy of these values.