extract the envelop of waves

[weitong]

Hello,

     Is there any funtion that is for extracting envelop of waves?

Thanks.

Weitong

[TWGomez]

Not one from LabVIEW that I know of, either the equipment itself supports it and contains a driver for it, or do some calculations on your own, I think...

[Eli_S]

Hi Weitong,

LabVIEW itself does not have envelope detection functions. However, the Sound and Vibration Measurement Suite is an additional toolkit you can purchase which comes with a lot more  functions related to this field, among them envelope detection.

[preston_johnson]

In addition,

the modulation toolkit provides an amplitude demodulation function which can detect envelopes in some signals.  Also the hilbert transform in LabVIEW (full) can be used for envelope detection.

[weitong]

Thank you very much.

I will try it.

[weitong]

Hi, preston.

     I am interested in extracting evelop and even the phase by hilbert transform. Could you give me more information about Hilbert transform?  How to realize it, and what's the algorithm?

Wei Tong

LV7.1

[preston_johnson]

It has been several years since our team investigated the hilbert transform as an envelope detection tool for bearing fault detection.  In the end we took a different approach, the one we package with the sound and vibration measurement suite.  Our new approache uses mixers, shifters, interpolation and decimation techniques.  However, I have attached the hilbert transform example and codes for your review. You'll have to take these as is, as I unfortunately am not an expert and our development team is now focused on the shipping product items.

Hope this helps.

[weitong]

Thank you so much! I am going to study it.

Do you think it is possible to get the phase information by Hilbert Tranform at the same time?

Best,

Wei Tonhg

LV7.1

[rpursley8]

I've used the Hilbert Transform for similar applications.

1.  Take your original signal (X).
2.  Take the Hilbert Transform of it (Y)
3.  Turn it into an analytic signal (X + jY) using one of the complex number functions (X is real part, Y is imaginary part).
4.  If you use another of the complex number functions to get the maginitude (R), this will be the envelope of the signal.
5.  The theta component will be the phase of the signal.
6.  The derivative of the theta component will be the instantaneous frequency of the signal in radians/s.

Essentially, if you looked at your signal in the frequency domain, the Hilbert Transform would change the sign of all of the negative frequency components.  the most basic example is f(x)=cos(x).  The Hilbert transform of this would be H{f(x)} = sin (x).  This means the analytic signal would be A{f(x)} = f(x) + jH{f(x)} or A{f(x)=cos(x) + jsin(x) whose envelope would be [cos(x)]^2 + [sin(x)]^2 = 1.

Since Fourier theorem says that any signal is comprised of sine and cosine components summed together, then the above can be extended to any signal.


Message Edited by rpursley8 on 04-14-2008 12:01 PM

[weitong]

rpursley8, Thank you very much!

Can you introduce me any paper or book about this theory?

Best,

Wei Tong

Message Edited by weitong on 04-16-2008 11:51 PM