计算机技术与发展2026，Vol.36Issue(9)：15-23,30,10.DOI:10.20165/j.cnki.ISSN1673-629X.2026.0078
基于STM32的城市地下空间智能防汛监控系统设计
Design of an Intelligent Flood Monitoring System for Urban Underground Space Based on STM32
摘要
Abstract
To address the issues of high false alarm rates caused by water wave disturbances and the limited computing power of edge nodes in urban underground space flood monitoring,an STM32-based heterogeneous data fusion adaptive measurement and control sys-tem is designed.Methodologically,a dynamic weighting model based on spatio-temporal statistical features is first constructed.This model adaptively assigns weights according to the long-term variance and short-term deviation of sensor data to suppress random errors from single sources at the root.Secondly,to overcome the lack of a Floating Point Unit(FPU)in microcontrollers,a Q15 format-based fixed-point fuzzy Kalman filtering algorithm is proposed.By utilizing a 2D lookup table to dynamically adjust the measurement noise co-variance matrix,complex floating-point matrix operations are reconstructed as efficient integer shift operations.Experimental results indi-cate that within the 10～40 mm effective measurement range,the maximum absolute error is controlled within 1.65 mm,and the corre-sponding maximum relative error does not exceed 5.5%,while the goodness of linear fit is improved to above 0.98.Compared with the standard floating-point filtering algorithm,the single operation time of the fixed-point algorithm is reduced from 820 μs to 68 μs,impro-ving the computational efficiency by approximately 12.05 times,and the step response convergence time is shortened to 200 ms.In con-clusion,the proposed method effectively addresses the challenge of high-precision real-time filtering for low-cost edge nodes,signifi-cantly improving the robustness and response speed of flood monitoring in complex fluid environments.However,limited by experimental conditions,this study only verifies the effectiveness of the algorithm on a small-scale model,providing technical support for future large-depth field monitoring and multi-node collaborative perception.关键词
地下空间防汛/边缘计算/多源数据融合/定点模糊卡尔曼滤波/韧性防灾/STM32Key words
underground space flood control/edge computing/multi-source data fusion/fixed-point fuzzy Kalman filter/resilient disaster prevention/STM32分类
信息技术与安全科学引用本文复制引用
邱炳文,李小玉..基于STM32的城市地下空间智能防汛监控系统设计[J].计算机技术与发展,2026,36(9):15-23,30,10.基金项目
国家自然科学基金项目(32560419) （32560419）
大学生创新训练计划项目(dxscx2025258) （dxscx2025258）
