Novelty detection based on elastic wave signals measured by different techniques

Authors

  • Piotr Nazarko
  • Leonard Ziemiański

Keywords:

Artificial neural networks, damage detection, structural health monitoring, elastic waves, non-destructive testing

Abstract

The paper discusses the results of laboratory experiments in which three independent measurement techniques were compared: a digital oscilloscope, phased array acquisition system, a laser vibrometer 3D. These techniques take advantage of elastic wave signals actuated and sensed by a surface-mounted piezoelectric transducers as well as non-contact measurements. In these experiments two samples of aluminum strips were investigated while the damage was modeled by drilling a hole. The structure responses recorded were then subjected to a procedure of signal processing, and features' extraction was done by Principal Components Analysis. A pattern database defined was used to train artificial neural networks for the purpose of damage detection.

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Published

2017-01-25

Issue

pp. 317-330

Section

Articles

How to Cite

Nazarko, P., & Ziemiański, L. (2017). Novelty detection based on elastic wave signals measured by different techniques. Computer Assisted Methods in Engineering and Science, 19(4), 317-330. https://cames3.ippt.pan.pl/index.php/cames/article/view/82