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 pyEMAFor new code, use sdypy-EMA directly:
pip install sdypy-EMAfrom sdypy import EMABasic 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:
Display stability chart
a.select_poles()The stability chart displayes calculated poles and the user can hand-pick the stable ones.
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 coefficientsReconstruction:
There are two types of reconstruction possible:
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.
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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Release files for pyEMA 0.31.0
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