The ThreePointDetector class#

class pylife.stress.rainflow.ThreePointDetector(recorder=None)[source]#

Count rainflow cycles with the classic three-point criterion.

Use this detector for general load collectives when the three-point method is the desired rainflow convention. The detector reports loop start and end loads to pylife.stress.rainflow.LoopValueRecorder or, when sample indices are needed, to pylife.stress.rainflow.FullRecorder. The recorder collective can then be transformed to load amplitude, load range, mean load, and number of cycles for fatigue assessment in pylife.strength.fatigue.

Parameters:

recorder (pylife.stress.rainflow.AbstractRecorder, optional) – Recorder receiving detected loop loads in MPa. If not given, a new pylife.stress.rainflow.LoopValueRecorder is created. Use pylife.stress.rainflow.FullRecorder to store the sample indices of the two turning points in addition to the load values.

See also

pylife.stress.rainflow.FourPointDetector

Count cycles with the four-point criterion.

pylife.stress.rainflow.FKMDetector

Count cycles by the classic FKM procedure.

pylife.stress.rainflow.FullRecorder

Store loop loads and sample indices.

Notes

The three-point detector evaluates a start point \(S\), the following front point \(F\), and the following back point \(B\). A closed loop is counted when the back point reaches beyond the start-front excursion,

\[|B - F| \ge |F - S|,\]

and the front is not part of an already closed loop or an uncovered front residual. When a loop closes, the same back point may also close older open loops. The recorded loop values are reversal loads in MPa; their peak-to-peak load range is \(L_R = |L_F - L_S|\) and their load amplitude is \(L_a = L_R / 2\).

The detector supports chunked processing. Repeated calls to process() continue the count across chunk boundaries; set flush=True only for the final chunk if the last sample shall be considered a turning point.

Examples

>>> from pylife.stress.rainflow import ThreePointDetector
>>> detector = ThreePointDetector()
>>> detector.process([0.0, 3.0, -1.0, 2.0, -2.0, 0.0], flush=True) is detector
True
>>> detector.recorder.collective
   from   to
0  -1.0  2.0

Inject a pylife.stress.rainflow.FullRecorder explicitly when sample indices are needed in addition to the loop loads:

>>> from pylife.stress.rainflow import FullRecorder
>>> detector = ThreePointDetector(recorder=FullRecorder())
>>> detector.process([0.0, 3.0, -1.0, 2.0, -2.0, 0.0], flush=True) is detector
True
>>> detector.recorder.collective
   from   to  index_from  index_to
0  -1.0  2.0           2         3
__init__(recorder=None)[source]#

Instantiate a three-point detector.

Parameters:

recorder (pylife.stress.rainflow.AbstractRecorder, optional) – Recorder receiving detected loop loads in MPa. The recorder must implement record_values(); recorders that also implement record_index() receive sample indices. If not given, a new pylife.stress.rainflow.LoopValueRecorder is created.

process(samples, flush=False)[source]#

Process a chunk of load samples.

Parameters:

  • samples (array_like) – Load samples in MPa. The detector extracts turning points and combines them with residual turning points from previous chunks.

  • flush (bool, optional) – Force processing of the last value as a turning point. Default is False. See pylife.stress.rainflow.FourPointDetector.process() for the streaming consequences of flushing.

Returns:

The detector itself, so that repeated process() calls can be chained.

Return type:

ThreePointDetector