Fei Wang, Zetao Li, H. Man, Jianhua Du
2025.5.21International Journal of Decision Support System Technology
tlooto Summary
The research results show that the algorithm has a steady-state error of 0.0327% under large disturbances, a signal-to-noise ratio of 35.832 dB, and a computation time of 55.291 ms, demonstrating good control performance and robustness.
Abstract
With the rapid development of bridge engineering, the requirements for construction accuracy are becoming increasingly high. In response to the shortcomings of existing control methods in dynamically changing environments, this study proposes an intelligent control strategy that integrates neural networks. Real time monitoring of bridge structure displacement through global navigation satellite systems, and dynamic adjustment of cable forces through intelligent hydraulic systems to achieve precise control. The research results show that the algorithm has a steady-state error of 0.0327% under large disturbances, a signal-to-noise ratio of 35.832 dB, and a computation time of 55.291 ms, demonstrating good control performance and robustness. This study has important theoretical and practical significance for improving the accuracy and structural safety of bridge construction.
Citation format
WANG, Fei, et al. Research on bridge tower misalignment and grouting accuracy control based on gnss displacement monitoring and intelligent hydraulic control system. International Journal of Decision Support System Technology, 2025, 17: 1–24.