Rational Fraction Polynomial Method

Modal parameter estimation from frequency response function using rational fraction polynomials meth

Description

The Frequency Response Function (FRF) is a complex valued function defined over a frequency range. The process of identifying parameters from this type of measurement is commonly called curve fitting or parameter estimation.
Rational Fraction Polynomial method (RFP method) perform curve fitting on these measurements (FRFs) to identify the modal parameters (natural frequencies, damping ratios, mode shape) of the predominant modes of vibration of the structure, but it can also be used for identifying poles, zeros and resonances of the combined electro-mechanical-acoustic system.

For his help in this code, I want to give thanks to:
Professor Michael Friswell
Department of Mechanical Engineering
University of Wales Swansea.

• MATLAB release: MATLAB 6.0 (R12)

[anwar dasuki]

thanks for guti, your program is excellent

[Eric Davis]

Very nice implementation. It would be nice to allow the order of the polynomials to be any values of choice.

[Jaroislaw Zwolski]

In my opinion it is very good and efficient. I've tested it many times an id looks OK. Thanks a lot.

[Ronald Faassen]

You should change the line
T=sparse(diag(rec))*thetamatrix(:,1:c-1);
into
T=diag(sparse(rec))*thetamatrix(:,1:c-1);
this drastically improves speed.

[Ignacio Munoz]

Excellent code. Impressive implementation of the RFP method in Matlab. Very good.

[erliang zhang]

 

[Martin Larsen]

Excellent curvefitter, except out-of-band modes are not handled, as far as I can see.
(A resonance outside the curvefitters selected frequency range causes a poor fit).
It should be possible to fix it by adding a
1/(i*2*pi*f) for the modes below the selected range and a i*2*pi*f for the modes above

[Ozan Anac]

Very good code!! It helped a lot!!
You stated at the description part the mode shapes can also be found,but the output of the code does not include the mode shapes. It includes the modal constants. How can we go from modal constants to mode shapes?

[Esteban Quiroz]

Very useful code. It is also neatly programmed and commented. Thanks for posting it!

[Jan Hoeft]

 

[Thitiwat Santidhanyaroj]

Thank you

[VIJAYAKUMAR]

Good work..

[Stéphane TURPAULT]

Very good code !

I agree with Ronald Faassen, and I would add :
* In orthogonal.m : "P" and "jk" should be initialised
* In rfp.m : "alpha", "Residuos" and "Polos" should be initialised

That helps to avoid OUT OF MEMORY errors in case of large data vectors input (because during a for loop, when you fill a vector or a matrix, a temporary vector or matrix is created if no initialisation is done).

[Vinay]

Good one!

[Sherif]

 

[oddo]

here is the same with Excel:
www.noisestructure.com/products/MPE_MDOF.php

[Yilin]

Thanks a lot! You just did what I want to do..........

[Kammoun]

good work

[Mac Rodge]

Hi,

Nice work!!!

But if I have a non-linear parameter in the equation like (x1-x2)^2, then how to obtain FRF for non-linear term?