Strategies for reliable automatic onset time picking of acoustic emissions and of ultrasound signals in concrete.
Determining the onset of transient signals like seismograms, acoustic emissions or ultrasound signals is very time consuming if the onset is picked manually. Therefore, different approaches exist, especially in seismology. The concepts of the most popular approaches are summarized. An own approach adapted to ultrasound signals and acoustic emissions, based on the Akaike Information Criterion (AIC), is presented. The AIC-picker is compared to an automatic onset detection algorithm based on the Hinkley criterion and also adapted to acoustic emissions. Manual picks performed by an analyst are used as reference values. Both automatic onset detection algorithms are applied to ultrasound signals which are used to monitor the setting and hardening of concrete. They are also applied to acoustic emissions recorded during a pull-out test. The AIC-picker produces sufficient reliable results for ultrasound signals where the deviation from the manual picks varies between 2% and 4%. Concerning acoustic emissions, only 10% of the events result in a mislocation vector greater than 5mm. It can be shown that our AIC-picker is a reliable tool for automatic onset detection for ultrasound signals and acoustic emissions of varying signal to noise ratio.
Kurz
Jochen H
JH
Institute of Construction Materials, University of Stuttgart, Pfaffenwaldring 4, 70550 Stuttgart, Germany. kurz@iwb.uni-stuttgart.de
Grosse
Christian U
CU
Reinhardt
Hans-Wolf
HW