Appliance of Elman neural networks in damage diagnosis of radial gate

• Published in: 2010 International Conference on Mechanic Automation and Control Engineering pp. 1037 - 1040
• Main Authors: Zhang Jianwei, Zhang Yina
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2010
• Subjects: Analytical models; Civil engineering; damage identification; Elman neural network; Home appliances; Large-scale systems; Monitoring; Neural networks; Numerical simulation; radial gate; Rivers; simulation analysis; Structural engineering; Water conservation
• ISBN: 9781424477371; 1424477379
• DOI: 10.1109/MACE.2010.5536732

Damage diagnosis and health monitoring of large-scale structures are becoming a hot research subject in the present structural engineering circle. Elman neural network is presented to identify and locate the crack damage of a radial gate located in the middle reaches of the main stream of the Jialing River. This method is an aggregation neural networks and pattern identification. And also make the combined index as input data of Elman neural networks, and make the damaged locations and degree as output data. Numerical simulation results show that Elman neural network method can make a better diagnosis for single and multiple damage identification.