Software implementation for acoustic emission event detection and parameter calculation

Abstract

This work consists of the development of software that can identify acoustic emission events faster than the acquisition rate, and use them to compute the evolution of local parameters, which can be used as precursors of local and global collapse. The program was developed in Python, using a moving window with a floating threshold in which events are detected using the Short-Term Energy technique. The end is detected using the Zero-Cross-Rate, and is a part of the program that still needs improvement in accuracy. Overall, the program shows good performance and promising results for event detection and parameter calculation.

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