Trigger¶

class acoular.tprocess.Trigger¶

Bases: TimeOut

Class for identifying trigger signals. Gets samples from source and stores the trigger samples in trigger_data().

The algorithm searches for peaks which are above/below a signed threshold. A estimate for approximative length of one revolution is found via the greatest number of samples between the adjacent peaks. The algorithm then defines hunks as percentages of the estimated length of one revolution. If there are multiple peaks within one hunk, the algorithm just takes one of them into account (e.g. the first peak, the peak with extremum value, …). In the end, the algorithm checks if the found peak locations result in rpm that don’t vary too much.

result(num)¶

Python generator that processes the source data and yields the time-signal block-wise.

This method needs to be implemented by the derived classes.

Parameters:

numint

This parameter defines the size of the blocks to be yielded (i.e. the number of samples per block)

Yields:

numpy.ndarray

Two-dimensional output data block of shape (num, num_channels)