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# http://www.apache.org/licenses/LICENSE-2.0
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__author__ = "Johannes Mueller"
__maintainer__ = __author__
import numpy as np
from pylife.rainflow_ext import threepoint_loop
from .general import AbstractDetector
[docs]
class ThreePointDetector(AbstractDetector):
r"""Classic three point rainflow counting algorithm.
.. jupyter-execute::
from pylife.stress.timesignal import TimeSignalGenerator
import pylife.stress.rainflow as RF
ts = TimeSignalGenerator(10, {
'number': 50,
'amplitude_median': 1.0, 'amplitude_std_dev': 0.5,
'frequency_median': 4, 'frequency_std_dev': 3,
'offset_median': 0, 'offset_std_dev': 0.4}, None, None).query(10000)
rfc = RF.ThreePointDetector(recorder=RF.LoopValueRecorder())
rfc.process(ts)
rfc.recorder.collective
Alternatively you can ask the recorder for a histogram matrix:
.. jupyter-execute::
rfc.recorder.histogram(bins=16)
We take three turning points into account to detect closed hysteresis loops.
* start: the point where the loop is starting from
* front: the turning point after the start
* back: the turning point after the front
A loop is considered closed if following conditions are met:
* the load difference between front and back is bigger than or
equal the one between start and front. In other words: if the
back goes beyond the starting point. For example (A-B-C) and
(B-C-D) not closed, whereas (C-D-E) is.
* the loop init has not been a loop front in a prior closed
loop. For example F would close the loops (D-E-F) but D is
already front of the closed loop (C-D-E).
* the load level of the front has already been covered by a prior
turning point. Otherwise it is considered part of the front
residuum.
When a loop is closed it is possible that the loop back also
closes unclosed loops of the past by acting as loop back for an
unclosed start/front pair. For example E closes the loop (C-D-E)
and then also (A-B-E).
::
Load -----------------------------
| x B F x
--------/-\-----------------/-----
| / \ x D /
------/-----\-/-\---------/-------
| / C x \ /
--\-/-------------\-----/---------
| x A \ /
--------------------\-/-----------
| x E
----------------------------------
| Time
.. _subsection_TP: ../demos/rainflow.ipynb#Classic-Three-Point-Counting
"""
[docs]
def __init__(self, recorder):
"""Instantiate a ThreePointDetector.
Parameters
----------
recorder : subclass of :class:`.AbstractRecorder`
The recorder that the detector will report to.
"""
super().__init__(recorder)
[docs]
def process(self, samples, flush=False):
"""Process a sample chunk.
Parameters
----------
samples : array_like, shape (N, )
The samples to be processed
flush : bool
Whether to flush the cached values at the end.
For explanations see :meth:`~pylife.stress.rainflow.FourPointDetector.process`
Returns
-------
self : ThreePointDetector
The ``self`` object so that processing can be chained
"""
samples = np.asarray(samples)
if len(self._residuals) == 0:
residuals = samples[:1]
else:
residuals = self._residuals[:-1]
turns_index, turns_values = self._new_turns(samples, flush)
turns = np.concatenate((residuals, turns_values, samples[-1:]))
turns_index = np.concatenate((self._residual_index, turns_index.astype(np.uintp)))
highest_front = np.argmax(residuals)
lowest_front = np.argmin(residuals)
(
from_vals,
to_vals,
from_index,
to_index,
residual_index
) = threepoint_loop(turns, turns_index, highest_front, lowest_front, len(residuals))
self._recorder.record_values(from_vals, to_vals)
self._recorder.record_index(from_index, to_index)
self._residuals = turns[residual_index]
self._residual_index = turns_index[residual_index[:-1]]
self._recorder.report_chunk(len(samples))
return self