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LMS Test.Lab Modal: FRF Sum

Creator
Creator

Working on a LMS Test.Lab modal with a lot of data points and want to sum them up by component name.  Used to do this in Cada with UPA.  Any tricks I could use?

8 REPLIES

Re: LMS Test.Lab Modal: FRF Sum

Siemens Genius Siemens Genius
Siemens Genius

I believe this can be done as follows.  If my instructions are not clear, let me know:

 

1. In ‘Modal Data Selection’ worksheet you can create a ‘FRF Set’ based on component name.  Picture below.

frfset.png

 

2. In either the ‘Polymax’ or ‘Time MDOF’ curvefitter bandwidth selection screen, you can select the ‘FRF Set’ under the ‘Modal Data Selection’ button (upper left).  Then create a sum (lower left).  Picture below.

frfsum.png

 

The sum will be accessible in a folder in the Navigator worksheet.

 

Let me know if this works for you.

 

 

 

 

 

Re: LMS Test.Lab Modal: FRF Sum

Creator
Creator

Thanks.  Should work.

Re: LMS Test.Lab Modal: FRF Sum

Creator
Creator

Just be aware that Re[FRFSum] = [Sum(ABS(Re[FRF_n])]/N or Number of FRFs in the set, Same for Im[FRFSum]

Re: LMS Test.Lab Modal: FRF Sum

Experimenter
Experimenter

Hello to all,

 

I have some question for this topic:

 

- what represent mathematicaly the FRF Sum? (where I can find documentation about this?)

- what means calculate this FRF Sum for a n-excitation axes and m-point of reponse (eg.triaxial acelerometers) so with a n*m*3 FRF matrix 

- can I use this as overall FRF to identify modes using PolyMAX or MDOF?

 

Thanks in advance for your reply

 

Guglielmo

Re: LMS Test.Lab Modal: FRF Sum

Siemens Legend Siemens Legend
Siemens Legend

Hello Guglielmo,

 

The math was presented in the last reply.  An FAQ from the GTAC support website's solution center is available here and also attached:  https://solutions.industrysoftware.automation.siemens.com/view.php?sort=desc&q=FRF+sum&dt=faq&file_t...

 

So, basically the Real part of the FRF sum is the average of the Absolute value of the Real part of the FRFs in Modal Data Selection.  The Imaginary part of the FRF sum is the average of the Absolute value of the Imaginary part of the FRFs in Modal Data Selection.  We do it in this manner so that the Peaks and Values do not average to zero.  If you consider the Imaginary part (for example) they both represent resonances.

 

All FRFs that are included in Modal Data Selection are included in the FRF Sum.

 

Yes, the FRF Sum is a useful tool (as well as the Mode Indicator Functions) for identifying modes.

 

 

Re: LMS Test.Lab Modal: FRF Sum

Experimenter
Experimenter
Hello Kevin_Grennier,

could you explain again, what represent mathematicaly the FRF Sum? Because i can´t open your link.

Thanks for your Reply.

Liu

Re: LMS Test.Lab Modal: FRF Sum

Siemens Legend Siemens Legend
Siemens Legend

Hello ,  if you are a customer on support you can access the FAQs on the GTAC support site with your webkey login and password.    We have some videos on creating the webkey, reaching support and using the GTAC support site at:

 https://www.youtube.com/playlist?list=PL1m1vu8_quoBjav-o5AM7VUawM-Gr8B-s

 

I believe the math is described in the text of the replies as well.  I will repeat it here and explain it:

 

Basically the Real part of the FRF sum is the average of the Absolute value of the Real part of the FRFs in Modal Data Selection.  The Imaginary part of the FRF sum is the average of the Absolute value of the Imaginary part of the FRFs in Modal Data Selection.  We do it in this manner so that the Peaks and Values do not average to zero.  If you consider the Imaginary part (for example) they both represent resonances.

 

Consider a torsion  mode.  The left edge woudl have positive imaginary value A and the right edge would haved negative imaginary value -A.  If we average them we would get zero, so we take their absolute value and average that for the Imaginary part of the FRF Sum (which is Imaginary value of A).  We repeat that for the Real parts as well.

Re: LMS Test.Lab Modal: FRF Sum

Experimenter
Experimenter
Hello Kevin_Grenier,

thanks for your explain. You are so professional! Smiley Happy

Liu