Lamb Wave Propagation-based Damage Identification for Quasi-isotropic CF/EP Composite Laminates Using Artificial Neural Algorithm: Part II - Implementation and Validation
- 1 February 2005
- journal article
- Published by SAGE Publications in Journal of Intelligent Material Systems and Structures
- Vol. 16 (2), 113-125
- https://doi.org/10.1177/1045389x05047600
Abstract
Active transducer networks using distributed piezoelectric actuator/sensor were designed in terms of a concept of ‘Standard Sensor Unit’ (SSU). Functionally integrating the artificial neural networks well-trained by Damage Parameters Database (DPD) developed in Part I, an active online structural health monitoring (SHM) system was configured on a VXI platform, which was then validated by quantitatively identifying hole-type defects in quasi-isotropic [0/45/-45/90]s CF/EP (T650/F584) composite laminates. The system has exhibited excellent ability to quantitatively assess the damaged parameters, including presence, location, geometric identity, and orientation. Additionally, the reliability and performance of the SHM system on the inherent network configurations, such as architecture, training pattern, training function, and distribution of transducers, were also evaluated.Keywords
This publication has 4 references indexed in Scilit:
- Lamb wave-based quantitative identification of delamination in CF/EP composite structures using artificial neural algorithmComposite Structures, 2004
- An intelligent signal processing and pattern recognition technique for defect identification using an active sensor networkSmart Materials and Structures, 2004
- A damage identification technique for CF/EP composite laminates using distributed piezoelectric transducersComposite Structures, 2002
- DETECTION OF ANOMALOUS STRUCTURAL BEHAVIOUR USING WAVELET ANALYSISMechanical Systems and Signal Processing, 2002