In this section
@article{Morse:2017:10.1016/j.ymssp.2017.05.047,
author = {Morse, L and Sharif, Khodaei Z and Aliabadi, MH},
doi = {10.1016/j.ymssp.2017.05.047},
journal = {Mechanical Systems and Signal Processing},
pages = {107--128},
title = {Reliability based impact localization in composite panels using Bayesian updating and the Kalman filter},
url = {http://dx.doi.org/10.1016/j.ymssp.2017.05.047},
volume = {99},
year = {2017}
}
TY - JOUR
AB - In this work, a reliability based impact detection strategy for a sensorized composite structure is proposed. Impacts are localized using Artificial Neural Networks (ANNs) with recorded guided waves due to impacts used as inputs. To account for variability in the recorded data under operational conditions, Bayesian updating and Kalman filter techniques are applied to improve the reliability of the detection algorithm. The possibility of having one or more faulty sensors is considered, and a decision fusion algorithm based on sub-networks of sensors is proposed to improve the application of the methodology to real structures. A strategy for reliably categorizing impacts into high energy impacts, which are probable to cause damage in the structure (true impacts), and low energy non-damaging impacts (false impacts), has also been proposed to reduce the false alarm rate. The proposed strategy involves employing classification ANNs with different features extracted from captured signals used as inputs. The proposed methodologies are validated by experimental results on a quasi-isotropic composite coupon impacted with a range of impact energies.
AU - Morse,L
AU - Sharif,Khodaei Z
AU - Aliabadi,MH
DO - 10.1016/j.ymssp.2017.05.047
EP - 128
PY - 2017///
SN - 1096-1216
SP - 107
TI - Reliability based impact localization in composite panels using Bayesian updating and the Kalman filter
T2 - Mechanical Systems and Signal Processing
UR - http://dx.doi.org/10.1016/j.ymssp.2017.05.047
UR - http://www.sciencedirect.com/science/article/pii/S0888327017303114
UR - https://www.elsevier.com/
UR - http://hdl.handle.net/10044/1/48864
VL - 99
ER -
