pyEMA

Experimental and operational modal analysis.

---

pyEMA is a port of sdypy-EMA, which is part of the SDyPy project. The code is maintained in sdypy-EMA; this package makes the same code available under the pyEMA name, so that existing code keeps working.

Please report issues and open pull requests at sdypy-EMA.

Installing pyEMA also installs sdypy-EMA. These two imports give the same code:

import pyEMA
from sdypy import EMA as pyEMA

For new code, use sdypy-EMA directly:

pip install sdypy-EMA

from sdypy import EMA

---

Basic pyEMA usage

Make an instance of Model class:

a = pyEMA.Model(
    frf_matrix,
    frequency_array,
    lower=50,
    upper=10000,
    pol_order_high=60
    )

Compute poles:

a.get_poles()

Determine correct poles:

The stable poles can be determined in two ways:

1. Display stability chart

a.select_poles()

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

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

approx_nat_freq = [314, 864]
a.select_closest_poles(approx_nat_freq)

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

Reconstruction:

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.

2. 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)