TY - JOUR
T1 - Damage-induced acoustic emission source identification in an advanced sandwich composite structure
AU - Sikdar, Shirsendu
AU - Ostachowicz, Wiesław
AU - Pal, Joy
N1 - Funding Information:
The research work is funded by the Polish National Science Centre (NCN) under grant agreement number: UMO-2016/23/N/ST8/01326 in the frame of the PRELUDIUM12 project.
Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2018/10/15
Y1 - 2018/10/15
N2 - This paper proposes an acoustic emission (AE) based real-time health monitoring framework to efficiently identify the probable damage initiation/propagation locations in advanced sandwich composite structures. Towards this, numerical simulations and laboratory experiments on damage-induced AE-wave propagation in an aramid honeycomb composite structure have been carried out using a randomly selected sensory network. The simulation results are successfully validated with laboratory experiments. Eventually, the damage-source/AE-source regions are efficiently identified by applying an evolutionary algorithm – Particle-Swarm-Optimization based monitoring framework, which uses the registered AE-signals from the sensory network. A thorough assessment of different AE-source locations was carried out to evaluate the performance and the robustness of the proposed online monitoring strategy. The results clearly represent the efficiency of the framework for localizing the AE-source locations in such advanced and complex structures. Moreover, the proposed framework is reliable, independent of sensor positions, and not dependent upon the operator's expertise.
AB - This paper proposes an acoustic emission (AE) based real-time health monitoring framework to efficiently identify the probable damage initiation/propagation locations in advanced sandwich composite structures. Towards this, numerical simulations and laboratory experiments on damage-induced AE-wave propagation in an aramid honeycomb composite structure have been carried out using a randomly selected sensory network. The simulation results are successfully validated with laboratory experiments. Eventually, the damage-source/AE-source regions are efficiently identified by applying an evolutionary algorithm – Particle-Swarm-Optimization based monitoring framework, which uses the registered AE-signals from the sensory network. A thorough assessment of different AE-source locations was carried out to evaluate the performance and the robustness of the proposed online monitoring strategy. The results clearly represent the efficiency of the framework for localizing the AE-source locations in such advanced and complex structures. Moreover, the proposed framework is reliable, independent of sensor positions, and not dependent upon the operator's expertise.
KW - Acoustic emission
KW - Aramid honeycomb composite sandwich panel
KW - Damage localization
KW - Particle swarm optimization
KW - Piezoelectric transducer disc sensors
KW - Structural health monitoring
UR - http://www.scopus.com/inward/record.url?scp=85045760472&partnerID=8YFLogxK
U2 - 10.1016/j.compstruct.2018.04.051
DO - 10.1016/j.compstruct.2018.04.051
M3 - Article
AN - SCOPUS:85045760472
VL - 202
SP - 860
EP - 866
JO - Composite Structures
JF - Composite Structures
SN - 0263-8223
ER -