MWModal - Morlet-Wave Modal Identification
This is the Python implementation of the method based on the Morlet-wave integral, which is developed for identification of modal parameters from short, noisy and low-dynamic-range signals [1].
This package is created within the H2020-MSCA-IF-2020 project NOSTRADAMUS.
Simple example
A simple example how to identify modal parameters using Morlet-Wave Modal package:
import mwmodal as mwm
import numpy as np
# set time domain
fs = 5000 # sampling frequency [Hz]
T = 2 # signal duration [s]
time = np.arange(T*fs) / fs # time vector
# generate a free response of a SDOF damped mechanical system
w_d = 2*np.pi * 100 # damped natural frequency
d = 0.01 # damping ratio
x = 1 # amplitude
phi = 0.3 # phase
response = x * np.exp(-d * w_d / np.sqrt(1 - d**2) * time) * np.cos(w_d * time - phi)
# set MorletWaveModal object identifier
identifier = mwm.MorletWaveModal(free_response=response, fs=fs)
# set initial natural frequency, estimate damping ratio and identify modal parameters
identifier.identify_modal_parameters(omega_estimated=w_n, damping_estimated=0.005)
References
Metadata
Release files for MorletWaveModal 0.6.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| morletwavemodal-0.6.4-py3-none-any.whl | Python 3 | none | any | Details |
Release files / morletwavemodal-0.6.4-py3-none-any.whl
| Download URL | morletwavemodal-0.6.4-py3-none-any.whl |
|---|---|
| Size | 7.6 kB |
| Tags | Python 3 |
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