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fatpack provides functions and classes for fatigue analysis of data series.

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Gunnstein/fatpack

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fatpack

Python package for fatigue analysis of data series. The package requires numpy.

Installation

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

Usage

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.

example_img

Additional examples are found in the examples folder.

Support

Please open an issue for support.

Contributing

Please contribute using Github Flow. Create a branch, add commits, and open a pull request.