Influence of parameters

Smoothing factor (P-AXIS-00784):

The greater the weighting of the current measured value, the lower the filter effect but the faster the reaction to changes in the distance.

Different filter effect due to smoothing factor
Different filter effect due to smoothing factor

Number of measured values - n_cycles (P-AXIS-00413):

The more measured values are included in the filter via P-AXIS-00413, the better the smoothing, but the greater the reaction delay involved. The greater the smoothing factor, the smaller the influence of P-AXIS-00413. Also, the influence of P-AXIS-00413 decreases steadily with increasing numbers due to the exponential weighting.

Different filter effect with varying n_cycles
Different filter effect with varying n_cycles

Example

example

Example parameters: Exponentially weighted averaging filter

kenngr.distc.filter_type   EXPO_MEAN #Filter type

kenngr.distc.n_cycles      30        #Number of included measured values

kenngr.distc.smoothing_factor 0.3    #Smoothing factor