vallenae.timepicker.aic

vallenae.timepicker.aic(arr)[source]

Akaike Information Criterion (AIC) for arrival time estimation.

The AIC picker basically models the signal as an autoregressive (AR) process. A typical AE signal can be subdivided into two parts. The first part containing noise and the second part containing noise and the AE signal. Both parts of the signal contain non deterministic parts (noise) describable by a Gaussian distribution.

Parameters:

arr (ndarray) – Transient signal of hit

Return type:

Tuple[ndarray, int]

Returns:

  • Array with computed detection function

  • Index of the estimated arrival time (max value)

References

  • Molenda, M. (2016). Acoustic Emission monitoring of laboratory hydraulic fracturing experiments. Ruhr-Universität Bochum.

  • Bai, F., Gagar, D., Foote, P., & Zhao, Y. (2017). Comparison of alternatives to amplitude thresholding for onset detection of acoustic emission signals. Mechanical Systems and Signal Processing, 84, 717-730.

  • van Rijn, N. (2017). Investigating the Behaviour of Acoustic Emission Waves Near Cracks: Using the Finite Element Method. Delft University of Technology.