Python package for fatigue analysis of data series. The package requires numpy.
Either install from the github repository (latest version),
pip install git+https://github.com/gunnstein/fatpack.git
install from the python package index
pip install fatpack
or from the conda-forge:
conda install --channel=conda-forge fatpack
The package provides functionality for rainflow cycle counting, defining endurance curves, mean and compressive stress range correction and racetrack filtering. The code example below shows how fatigue damage can be calculated:
import numpy as np
import fatpack
# Assume that `y` is the data series, we generate one here
y = np.random.normal(0., 30., size=10000)
# Extract the stress ranges by rainflow counting
S = fatpack.find_rainflow_ranges(y)
# Determine the fatigue damage, using a trilinear fatigue curve
# with detail category Sc, Miner's linear damage summation rule.
Sc = 90.0
curve = fatpack.TriLinearEnduranceCurve(Sc)
fatigue_damage = curve.find_miner_sum(S)An example is included (example.py) which extracts rainflow cycles, generates the rainflow matrix and rainflow stress spectrum, see the figure presented below. The example is a good place to start to get into the use of the package.
Additional examples are found in the examples folder.
Please open an issue for support.
Please contribute using Github Flow. Create a branch, add commits, and open a pull request.
