Journal of Materials and Engineering Structures
Volume 10, Numéro 1, Pages 69-80
2023-03-30
Authors : Long Nguyen Ngoc . Thanh Bui Tien . Hanh Hong Nguyen . Thang Le Xuan . Xuan Tung Nguyen . Hoa Tran Ngoc .
In this paper, we propose an efficient approach to enhance the capacity of Artificial Neural Network (ANN) to deal with Structural Health Monitoring (SHM) problems. Over the last decades, ANN has been extensively utilized for damage detection in structures. In order to identify damages, ANN frequently utilizes input information that is based on dynamic features such as mode shapes or natural frequencies. However, this type of data may not be able to detect minor damages if the structural defects are insignificant. To transcend these limitations, in this work, we propose utilizing transmissibility to create input data for the input layer of ANN. Moreover, to deal with local minimum problems of ANN, a combination between the Arithmetic Optimization Algorithm (AOA) and ANN is proposed. The global search capacity of AOA is employed to remedy the local minima of ANN. To evaluate the effectiveness of the proposed approach, a numerical model with different damage scenarios is considered. The suggested approach detects damage location precisely and with higher severity detection precision than the conventional ANN method.
Artificial Neural Network ; Structural Health Monitoring ; Transmissibility ; Arithmetic Optimization Algorithm
Tung Nguyen-xuan
.
Tung Thang Le-xuan
.
Lan Nguyen-ngoc
.
Hoa Tran-ngoc
.
Long Nguyen-ngoc
.
Thanh Bui-tien
.
pages 507-519.
Bui-tien Thanh
.
Le-xuan Thang
.
Tran-viet Hung
.
Nguyen-xuan Tung
.
Nguyen-ngoc Long
.
Dao-thuy Linh
.
Tran-ngoc Hoa
.
pages 411-420.
Beghoul Noureddine
.
Benhallou Hadj
.
pages 183-211.
Hellassa Wassim
.
Boukari Karima
.
pages 52-62.