Soft computing methods in the analysis of elastic wave signals and damage identification

Abstract

An outline of a Structure Health Monitoring (SHM) system is given. A non-destructive technique of elastic wave propagation was used in the presented approach. For the analysis of time signals recorded by piezoelectric transducers, signal processing algorithm has been developed and artificial neural networks have been used. As a consequence, two levels of the damage identification problem have been realized: novelty detection and damage assessment. The systems accuracy and reliability have been verified during laboratory tests of strip specimens made of various materials. It has been proved that the system can be used for the analysis of simple as well as complex signals. Moreover, the system can operate online as an automatic SHM system.

Keywords:

• neural networks
• pattern recognition
• damage identification
• elastic waves
• structural health monitoring

Classification:

• 68T10
• 82-08
• 92B20

Acknowledgments

Apparatus/Equipment purchased in the project No POPW.01.03.00-18-012/09 from the Structural Funds, The Development of Eastern Poland Operational Programme co-financed by the European Union, the European Regional Development Fund.