Journal of Jilin University(Engineering and Technology Edition) ›› 2024, Vol. 54 ›› Issue (4): 1038-1044.doi: 10.13229/j.cnki.jdxbgxb.20220671

Previous Articles    

Bridge extreme stress dynamic prediction based on improved Gaussian mixed particle filter new algorithm

Xue-ping FAN1,2(),Yue-fei LIU1,2   

  1. 1.Key Laboratory of Mechanics on Disaster and Environment in Western China of the Ministry of Education，Lanzhou University，Lanzhou 730000，China
    2.School of Civil Engineering and Mechanics，Lanzhou University，Lanzhou 730000，China
  • Received:2022-05-23 Online:2024-04-01 Published:2024-05-17

RICH HTML

 1   

PDF (PC)

155

Abstract:

The extreme stress data is taken as a time series， an improved Gaussian mixed particle filter（IGMPF） dynamic prediction new approach of bridge extreme stresses is proposed. Firstly， the dynamic nonlinear model， which provides state equation and monitored equation for the particle filter， is built with the monitored bridge extreme stress data； then， the EM algorithm is introduced to estimate the probability density function（PDF） of the target state and embedded in the Gaussian mixed particle filter（GMPF）； further， with the IGMPF prediction approach， structural stresses are dynamically predicted based on the monitored extreme stress data； finally， the monitored stress data of an actual bridge is provided to illustrate the feasibility and application of the proposed models and methods. The result shows that the proposed algorithm has good prediction accuracy， can apply to real engineering.

Key words: structural engineering, extreme stress, dynamic nonlinear model, expectation maximization algorithm, Gaussian mixed particle filter

CLC Number: 

  • TU391

Fig.1

Flow chart of proposed algorithm"

Fig.2

Schematic diagram D section"

Fig.3

Monitored extreme stress data"

Fig.4

Initial data and monitored data"

Fig.5

Prediction result of monitoring stress"

Fig.6

Predicted MSE of 50 consecutive times"

1 Bao Y Q, Beck J L, Li H. Application compressive sampling for accelerometer signals used in structural health monitoring[C]∥The 8th International Conference on Damage Assessment of Structures, Beijing, China, 2009: 455-462.
2 Zhang Y, Li J. Wavelet-based vibration sensor data compression technique for civil infrastructure condition monitoring[J]. Journal of Computing in Civil Engineering, 2006, 20(6): 390-399.
3 Tropp J A, Gilbert A C. Signal recovery from random measurements via orthogonal matching pursuit[J]. IEEE Transactions on Information Theory, 2007, 53(12): 4655-4666.
4 李惠, 周文松, 欧进萍, 等. 大型桥梁结构智能健康监测系统集成技术研究[J]. 土木工程学报, 2006, 39(2): 46-52.
Li Hui, Zhou Wen-song, Jin-ping Ou, et al. A study on system integration technique of intelligent monitoring systems for soundness of long-span bridges[J]. China Civil Engineering Journal, 2006, 39(2): 46-52.
5 李爱群, 缪长青, 李兆霞, 等. 润扬长江大桥结构健康监测系统研究[J]. 东南大学学报, 2003, 33(5): 544-548.
Li Ai-qun, Miao Chang-qing, Li Zhao-xia, et al. Health monitoring system for the Runyang Yangtse River Bridge[J]. Journal of Southeast University, 2003, 33(5): 544-548.
6 宗周红, 褚福鹏, 牛杰. 基于响应面模型修正的桥梁结构损伤识别方法[J]. 土木工程学报, 2013(2):115-122.
Zong Zhou-hong, Chu Fu-peng, Niu Jie. Damage identification methods of bridge structures using response surface based on finite element model updating[J]. China Civil Engineering Journal, 2013, 46(2):115-122.
7 宗周红, 周儒勉, 郑沛娟. 基于健康监测的桥梁结构损伤预后和安全预后研究进展及挑战[J]. 中国公路学报, 2014, 27(12): 46-57.
Zong Zhou-hong, Zhou Ru-mian, Zheng Pei-juan. Damage and safety prognosis of bridge structures based on structural health monitoring: progress and challenges[J]. China Journal of Highway and Transport, 2014, 27(12): 46-57.
8 魏锦辉, 任伟新. 基于响应面方法的桥梁静动力有限元模型修正[J]. 公路交通科技, 2015, 32(2): 68-73.
Wei Jin-hui, Ren Wei-xin. Static and dynamic bridge finite element model updating based on response surface method[J]. Journal of Highway and Transportation Research and Development, 2015, 32(2): 68-73.
9 Abudayyeh O Y, Barbera J, Abdelqader I, et al. Towards sensor-based health monitoring systems for bridge decks: a full-depth precast deck panels case study[J]. Advances in Civil Engineering, 2015, 2010(1): 1-14.
10 赵卓. 基于ARMA模型的伊通河桥监测数据建模与可靠度分析[D]. 哈尔滨: 哈尔滨工业大学土木工程学院, 2012
Zhao Zhuo. Health monitoring data modeling and reliability analysis for Yitong river bridge based on ARMA model[D]. Harbin: School of Civil Engineering, Harbin Institute of Technology, 2012.
11 樊学平. 基于验证荷载和监测数据的桥梁可靠性修正与贝叶斯预测[D]. 哈尔滨: 哈尔滨工业大学土木工程学院, 2014.
Fan Xue-ping. Bridge reliability updating and Bayesian prediction based on proof loads and monitored data[D]. Harbin: School of Civil Engineering, Harbin Institute of Technology, 2014.
12 Fan X P. Bridge extreme stress prediction based on Bayesian dynamic linear models and non-uniform sampling[J]. Structural Health Monitoring, 2017, 16(3): 253-261.
13 Han H, Ding Y S, Hao K R, et al. An evolutionary particle filter with the immune genetic algorithm for intelligent video target tracking[J]. Computers & Mathematics with Applications, 2011, 62(7): 2685-2695.
14 樊学平, 刘月飞, 吕大刚. 应用高斯粒子滤波器的桥梁可靠性在线预测[J]. 哈尔滨工业大学学报, 2016, 48(6): 164-169.
Fan Xue-ping, Liu Yue-fei, Da-gang Lyu. On-line reliability prediction of bridges based on Gaussian particle filter[J]. Journal of Harbin Institute of Technology, 2016, 48(6): 164-169.
15 樊学平, 刘月飞, 吕大刚. 桥梁极值应力的改进高斯混合粒子滤波器动态预测[J]. 同济大学学报: 自然科学版, 2016, 44(11): 1660-1666.
Fan Xue-ping, Liu Yue-fei, Da-gang Lyu. Improved Gaussian mixed particle filter dynamic prediction of bridge monitored extreme stress[J]. Journal of Tongji University, 2016, 44(11): 1660-1666.
16 Fan X P, Liu Y F. Dynamic extreme stress prediction of bridges based on nonlinear mixed Gaussian particle filtering algorithm and structural health monitoring data[J]. Advances in Mechanical Engineering, 2016, 8(6): 1-10.
17 Kushary D. The EM algorithm and extensions[J]. Technometrics, 1997, 40(3): 260-260.
18 于金霞, 刘文静, 汤永利. 粒子滤波重采样算法研究[J]. 微计算机信息, 2010, 26(16): 44-45.
Yu Jin-Xia, Liu Wen-jing, Tang Yong-li. Study on the resampling algorithms of particle filter[J]. Microcomputer Information, 2010, 26(16): 44-45.
[1] Yi-fan LIU,Zhi-wei MIAO,Chen SHEN,Xiang-dong GENG. Evaluation of mechanical properties of non-uniform corroded rebars based on Monte Carlo method [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(4): 1007-1015.
[2] Xue-ping FAN,Heng ZHOU,Yue-fei LIU. Time⁃variant reliability analysis of bridge members based on Gaussian Copula⁃Bayesian dynamic models [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(2): 485-493.
[3] Xue-ping FAN,Heng ZHOU,Yue-fei LIU. Multi⁃process Bayesian dynamic combinatorial prediction of time⁃variant reliability for bridges [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(8): 2332-2338.
[4] Er-gang XIONG,Zhong-wen GONG,Jia-ming LUO,Tuan-jie FAN. Experiment on cracks in reinforced concrete beams based on digital image correlation technology [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(4): 1094-1104.
[5] Xiao-dong WANG,Ning-jing LI,Qiang LI. Experimental on crushing of concrete beams by high⁃voltage pulse discharge [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(2): 496-504.
[6] Ya-chuan KUANG,Li-bin CHEN,Chao-ju LI,Yu-hao HE. Analysis of mechanical properties of stud shear connectors [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(2): 538-546.
[7] Li-zhao DAI,Liang ZHOU,Xiao-wen YANG,Lei WANG. Meso-scale numerical simulation of interfacial bond behavior of corroded RC beams based on connector element [J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(10): 2886-2896.
[8] Yun-peng CHU,Xin-hui SUN,Ming LI,Yong YAO,Han-jie HUANG. Wind pressures on a circular hyperbolic⁃paraboloid roof subjected to a simulated downburst [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(8): 1826-1833.
[9] Yong YAO,Liu-feng SU,Ming LI,Yun-peng CHU,Han-jie HUANG. Wind load characteristics of double⁃sided spherical shell roof under downburst [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(3): 615-625.
[10] Ya-chuan KUANG,Zhe-xuan SONG,Yin-hu LIU,Xiao-fei MO,Liang-ming FU,Shi-quan LUO. Experiment on mechanical properties of new type assembled double-cabin utility tunnel [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(3): 596-603.
[11] Yi-hong WANG,Qiao-luo TIAN,Guan-qi LAN,Sheng-fa YAO,Jian-xiong ZHANG,Xi LIU. Experimental research on the mechanical properties of concrete column reinforced with 630 MPa high⁃strength steel under large eccentric loading [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(11): 2626-2635.
[12] Yong-zhi GONG,Jin-hua KUANG,Fu-long KE,Quan ZHOU,Xiao-yong LUO. Experiment on seismic behavior of assembled shear wall joints connected by ultra high performance concrete [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(10): 2367-2375.
[13] Xue-ping FAN,Guang-hong YANG,Zhi-peng SHANG,Xiao-xiong ZHAO,Qing-kai XIAO,Yue-fei LIU. Dynamic reliability fusion prediction of long-span bridge girder considering structural serviceability [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(1): 144-153.
[14] Fu-shou LIU,Qi WEI,Wen-ting XU,Guo-jin TAN. Damage detection of truss structures based on elastic wave propagation and spectral element method [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(6): 2087-2095.
[15] Xue-ping FAN,Guang-hong YANG,Qing-kai XIAO,Yue-fei LIU. Optimal R-vine copula information fusion for failure probability analysis of long-span bridge girder [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(4): 1296-1305.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd