Title :
Research of Trustless Deflection Correcting Based on Neural Networks
Author :
Hu, Shunren ; Chen, Weimin
Author_Institution :
Dept. of Electron. Inf. & Autom., Chongqing Inst. of Technol.
Abstract :
The trustless deflection occurred by the acquisition system is the main reason to bring the illusive alarms (above 80%). Although the acquisition system of the bridge structural health monitoring system (BSHMS) is designed by the advanced sensors, for example, the photoelectric imaging deflection meter system and so on. However, the trustless deflection generated by much reason in data acquisition system and transmission system, and these trustless data are unavoidable. A novel method based on the correlation analysis of bridge´s checking points and the RBF neural networks is proposed for correcting nonlinear deflection trustless data. Compared with conventional methods (its MSE is 4.3815), the proposed approach (its MSE is 0.7973) assures more accurate and accords with practice. Simulation results verify the effectiveness of the designed method and theoretical discussions
Keywords :
bridges (structures); condition monitoring; data acquisition; radial basis function networks; structural engineering computing; RBF neural network; advanced sensor; bridge checking point; bridge structural health monitoring system; correlation analysis; data acquisition system; nonlinear deflection trustless data; photoelectric imaging deflection meter system; radial basis function; transmission system; trustless deflection correcting; Automation; Bridges; Data acquisition; Data analysis; Digital cameras; Educational technology; Laboratories; Monitoring; Neural networks; Smart pixels;
Conference_Titel :
Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
Conference_Location :
Jinan
Print_ISBN :
0-7695-2528-8
DOI :
10.1109/ISDA.2006.227
