Skip to main content

Morlet Wave Modal Identification.

Project description

MWModal - Morlet-Wave Modal Identification

This is the Python implementation of the Morlet-Wave Modal identification method which is based on the [1].

This package is created within the MSCA IF 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

https://zenodo.org/badge/DOI/10.5281/zenodo.7002905.svg https://github.com/ladisk/MorletWaveModal/actions/workflows/python-package.yml/badge.svg

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

MorletWaveModal-0.6.3.tar.gz (7.3 kB view hashes)

Uploaded Source

Built Distribution

MorletWaveModal-0.6.3-py3-none-any.whl (7.6 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page