pyExSi 0.3

pyExSi - Excitation signals as used in structural dynamics and vibration fatigue

Supported excitation signals are:

• pulse (e.g. half-sine)

• random:

  • uniform random distribution

  • normal random distribution

  • pseudorandom distribution

• random, defined by power spectral density (PSD):

  • stationary Gaussian

  • stationary non-Gaussian

  • non-stationary non-Gaussian random process

• burst random

• sine sweep

Simple example

A simple example on how to generate random signals on PSD basis:

import pyExSi as es
import numpy as np


N = 2**16 # number of data points of time signal
fs = 1024 # sampling frequency [Hz]
t = np.arange(0,N)/fs # time vector

# define frequency vector and one-sided flat-shaped PSD
M = N//2 + 1 # number of data points of frequency vector
freq = np.arange(0, M, 1) * fs / N # frequency vector
freq_lower = 50 # PSD lower frequency limit  [Hz]
freq_upper = 100 # PSD upper frequency limit [Hz]
PSD = es.get_psd(freq, freq_lower, freq_upper) # one-sided flat-shaped PSD

#get gaussian stationary signal
gausian_signal = es.random_gaussian((N, PSD, fs)

#get non-gaussian non-stationary signal, with kurtosis k_u=10
#amplitude modulation, modulating signal defined by PSD
PSD_modulating = es.get_psd(freq, freq_lower=1, freq_upper=10)
#define array of parameters delta_m and p
delta_m_list = np.arange(.1,2.1,.5)
p_list = np.arange(.1,2.1,.5)
#get signal
nongaussian_nonstationary_signal = es.nonstationary_signal(N,PSD,fs,k_u=5,modulating_signal=('PSD', PSD_modulating),param1_list=p_list,param2_list=delta_m_list)