TY - GEN
T1 - Aircraft wing structural damage localization research based on RBF neural network
AU - Bao, Pengyu
AU - Yuan, Mei
AU - Song, Hao
AU - Guo, Wei
AU - Xue, Jingfeng
PY - 2011
Y1 - 2011
N2 - In this article, the wing structural damage is identified and located by using modal analysis and Radial Basis Function (RBF) neural network. The finite element model of an aircraft wing is set up which is used for model analysis. The number of network centers is increased gradually which can ensure that the network has a simplest structure; RBF center is determined by K-means clustering algorithm which can improve the representative of each center and improve the training accuracy; the network weights is determined using the concept of pseudo inverse matrix and inverse matrix, which can shorten the training period and improve training efficiency. The computer simulation result shows that this damage identification method has high identification accuracy. The relative error is 1.422%, and the absolute error is 31.28mm. Comparing with the analyzing spar and skin individually, this method has a more spreading value.
AB - In this article, the wing structural damage is identified and located by using modal analysis and Radial Basis Function (RBF) neural network. The finite element model of an aircraft wing is set up which is used for model analysis. The number of network centers is increased gradually which can ensure that the network has a simplest structure; RBF center is determined by K-means clustering algorithm which can improve the representative of each center and improve the training accuracy; the network weights is determined using the concept of pseudo inverse matrix and inverse matrix, which can shorten the training period and improve training efficiency. The computer simulation result shows that this damage identification method has high identification accuracy. The relative error is 1.422%, and the absolute error is 31.28mm. Comparing with the analyzing spar and skin individually, this method has a more spreading value.
UR - https://www.scopus.com/pages/publications/82855176959
U2 - 10.1109/ICCIS.2011.6070302
DO - 10.1109/ICCIS.2011.6070302
M3 - 会议稿件
AN - SCOPUS:82855176959
SN - 9781612841984
T3 - Proceedings of the 2011 IEEE 5th International Conference on Cybernetics and Intelligent Systems, CIS 2011
SP - 57
EP - 62
BT - Proceedings of the 2011 IEEE 5th International Conference on Cybernetics and Intelligent Systems, CIS 2011
T2 - 2011 IEEE 5th International Conference on Cybernetics and Intelligent Systems, CIS 2011
Y2 - 17 September 2011 through 19 September 2011
ER -