集成电路与嵌入式系统2025，Vol.25Issue(7)：50-56,7.DOI:10.20193/j.ices2097-4191.2025.0012
卡尔曼滤波在桥梁支座监测系统中的应用
Application of Kalman filter in bridge health monitoring system
摘要
Abstract
Aimed at the problem of data noise interference in bridge bearing tilt angle and stress monitoring,a real-time monitoring data preprocessing system based on Kalman filtering is designed.The system uses classical Kalman filtering algorithm to preprocess the tilt angle and stress data collected by the sensor,which effectively suppresses the noise interference.Based on the parallel computing advan-tage of FPGA,the functions of data acquisition,filtering and transmission are realized,and the monitoring data of bridge bearings are dynamically displayed in real time combined with the upper computer.The experimental results show that the signal-to-noise ratio of the filtered stress signal is 32.10 dB,the mean square error is 0.051 8,the correlation coefficient is 0.581 1,and the variance ratio is 0.701 8.The SNR,MSE,correlation coefficient and variance ratio of inclination signal after filtering are 33.98 dB,0.041 8,0.703 2 and 0.629 1,respectively,indicating that the filtering algorithm can effectively suppress noise interference.The developed system exhibits remarkable stability and reliability,achieving rapid data processing ability meanwhile satisfying the needs of real-time monitoring of bridge bearing inclination and stress.Additionally,this paper uses ASIC process to design the Kalman filter algorithm chip,and realizes the Kalman filter circuit based on 180 nm CMOS process.The clock frequency is 160 MHz,and the comprehensive area is 599 131 μm2.关键词
FPGA/卡尔曼滤波/实时监测/ASICKey words
FPGA/Kalman filter/real-time monitoring/ASIC分类
信息技术与安全科学引用本文复制引用
邵炼,黄俊珂,邹璨,寻滔源,杨森,邹望辉..卡尔曼滤波在桥梁支座监测系统中的应用[J].集成电路与嵌入式系统,2025,25(7):50-56,7.基金项目
湖南省重点研发计划项目(2023GK2036) （2023GK2036）
湖南省教育厅科学研究项目(23A0260) （23A0260）
