•  
  •  
 

Abstract

Bridge health monitoring provides important support for daily operation and maintenance management of bridges. Meanwhile, real-time analysis, evaluation and early warning of bridge health monitoring data are the core requirements for enhancing bridge monitoring and safety protection, which can help grasp the operation status of bridge structures in real time and guard against major safety risks of bridge operation. This paper combined traditional signal processing and statistical analysis with modern machine learning and deep learning, and developed a platform for real-time analysis and warning of bridge health monitoring data based on Matlab-JAVA integration. Online cleaning, feature extraction, performance evaluation and safety warning of health monitoring data were included to realize automatic analysis of monitoring data, real-time evaluation of structural conditions, and timely warning of abnormal status. Finally, the main functions of the monitoring data analysis and warning platform were demonstrated by taking the Julong super major bridge project as an example. Practice shows that the platform realizes fast and accurate analysis of health monitoring data, and has excellent data analysis and operation efficiency.

Publication Date

9-14-2023

DOI

10.14048/j.issn.1671-2579.2023.04.022

First Page

137

Last Page

140

Submission Date

March 2025

Reference

[1] 杜彦良, 孙宝臣, 吴智深, 等. 关于建立健全交通基础设施长寿命安全保障体系的战略思考[J]. 中国工程科学, 2017, 19(6): 1-5. DU Yanliang, SUN Baochen, WU Zhishen, et al. Strategies for establishing and perfecting long-life security strategy of transportation infrastructure[J]. Strategic Study of CAE, 2017, 19(6): 1-5. [2] LI H N，LI D S，REN L，et al.Structural health monitoring of innovative civil engineering structures in mainland china[J].Structural Monitoring and Maintenance，2016，3(1)：1‑32. [3] 杨晓霞, 候锐锋. Visual C#.NET, DELPHI, JAVA与MATLAB接口技术的研究[J]. 云南大学学报(自然科学版), 2008, 30(S2): 247-249. YANG Xiaoxia, HOU Ruifeng. Research on interfacing technology between visual C#. NET, DELPHI, JAVA and MATLAB[J]. Journal of Yunnan University (Natural Sciences Edition), 2008, 30(S2): 247-249. [4] HU W H, SAID S, ROHRMANN R G, et al. Continuous dynamic monitoring of a prestressed concrete bridge based on strain, inclination and crack measurements over a 14-year span[J]. Structural Health Monitoring, 2018, 17(5): 1073-1094. [5] 涂成枫, 刘泽佳, 张舸, 等. 面向桥梁长期健康监测的大数据处理技术及应用[J]. 实验力学, 2017, 32(5): 652-663. TU Chengfeng, LIU Zejia, ZHANG Ge, et al. Processing technique and application of big data oriented to long-term bridge health monitoring[J]. Journal of Experimental Mechanics, 2017, 32(5): 652-663. [6] 任普. 基于大数据的桥梁监测数据清洗方法研究[D]. 南京: 东南大学, 2019. REN Pu. Research on cleaning method of bridge monitoring data based on big data[D]. Nanjing: Southeast University, 2019. [7] CATBAS F N, SUSOY M, FRANGOPOL D M. Structural health monitoring and reliability estimation: long span truss bridge application with environmental monitoring data[J]. Engineering Structures, 2008, 30(9): 2347-2359. [8] DING Y L, ZHAO H W, DENG L, et al. Early warning of abnormal train-induced vibrations for a steel-truss arch railway bridge: case study[J]. Journal of Bridge Engineering, 2017, 22(11): 05017011. [9] DENG Y, LI A Q, CHEN S R, et al. Serviceability assessment for long-span suspension bridge based on deflection measurements[J]. Structural Control and Health Monitoring, 2018, 25(11): e2254. [10] 胡奇宇. 广州市北二环高速公路聚龙特大桥设计[J]. 铁道勘测与设计, 2004(4): 59-62. HU Qiyu. Design of julong bridge of guangzhou north second ring expressway[J]. Railway Survey and Design, 2004(4): 59-62.

Download

Share

COinS