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Experimental and operational modal analysis.

Project description

Experimental and operational modal analysis

Check out the documentation.

New in version 0.26

  • include (or exclude) upper and lower residuals

  • driving point implementation (scaling modal constants to modal shapes)

  • implementation of the LSFD method that assumes proportional damping (modal constants are real-valued)

  • FRF type implementation (enables the use of accelerance, mobility or receptance)

Basic usage

Make an instance of Model class:

a = pyema.Model(

Compute poles:


Determine correct poles:

The stable poles can be determined in two ways:

  1. Display stability chart


The stability chart displayes calculated poles and the user can hand-pick the stable ones.

  1. If the approximate values of natural frequencies are already known, it is not necessary to display the stability chart:

approx_nat_freq = [314, 864]

After the stable poles are selected, the natural frequencies and damping coefficients can now be accessed:

a.nat_freq # natrual frequencies
a.nat_xi # damping coefficients


There are two types of reconstruction possible:

  1. Reconstruction using own poles (the default option):

H, A = a.get_constants(whose_poles='own')

where H is reconstructed FRF matrix and A is a matrix of modal constants.

  1. Reconstruction on c using poles from a:

c = pyema.Model(frf_matrix, frequency_array, lower=50, upper=10000, pol_order_high=60)

H, A = c.get_constants(whose_poles=a)

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