Journal of Jilin University(Engineering and Technology Edition) ›› 2020, Vol. 50 ›› Issue (2): 557-564.doi: 10.13229/j.cnki.jdxbgxb20190082

Previous Articles    

Urban bridge performance decay model based on survival analysis

Yu FANG(),Li-jun SUN()   

  1. The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai 201804, China
  • Received:2019-01-18 Online:2020-03-01 Published:2020-03-08
  • Contact: Li-jun SUN E-mail:1610049@tongji.edu.cn;ljsun@tongji.edu.cn

RICH HTML

 5   

PDF (PC)

389

Abstract:

By using bridge inspection records in Shanghai urban bridge management system, this paper established a probabilistic prediction model of bridge performance deterioration based on survival analysis. At the same time, Weibull distribution functions are used to describe the performance decay behavior of various bridge components in different condition states. The results show that the current urban bridges in Shanghai have a relatively short duration at condition rating A and B, and the decay speed of the deck system and superstructure is higher than the substructure. Applied a practical example of network-level bridge decay prediction from 2016 to 2018, the differences between the regression analysis, Markov chain and survival analysis method are compared. It is verified that the survival analysis model has higher prediction accuracy.

Key words: road engineering, bridge performance, prediction model, survival analysis, Weibull-distribution

CLC Number: 

  • U418

Table 1

Classification of urban bridge intact state"

等级状态BCI范围养护对策
A级完好[90,100]日常养护
B级良好[80,90)保养小修
C级合格[66,80)针对性小修或中修工程
D级不合格[50,66)检测评估后进行中修、大修或加固工程
E级危险[0,50)检测评估后进行大修、加固、或改建工程

Fig.1

BCI state change trend in Shanghai city"

Fig.2

Duration of bridge performance decay process"

Table 2

Inspection records in BMS database since 2004"

年份桥梁数量检测记录数有效记录数
20041 3901 091652
20051 5501 357839
20061 6011 447936
20071 6441 4861 035
20081 7481 6081 151
20091 8041 5901 193
20101 8991 6861 267
20111 9721 7271 331
20121 9111 7561 458
20131 9821 8011 569
20142 1771 9921 709
20152 3052 0271 820

Table 3

Estimated parameters of Weibull distribution"

等级部位βγ
A全桥1.272 114.121 6
桥面系1.193 713.176 1
上部结构1.281 814.421 2
下部结构1.244 314.222 4
B全桥1.205 715.901 6
桥面系1.371 215.833 9
上部结构1.084 415.118 5
下部结构1.367 521.437 8
C全桥1.211 022.841 9
桥面系1.379 519.291 7
上部结构1.116 315.407 2
下部结构1.166 721.839 4
D全桥1.251 622.158 4
桥面系1.574 923.934 5
上部结构1.385 227.225 3
下部结构1.391 229.411 2

Fig.3

Survival function for different intact states"

Table 4

Mean durations at different intact state"

状态等级全桥桥面系上部结构下部结构
均值累计均值累计均值累计均值累计
A1313121213131313
B1528152714272033
C2149184514422053
D2170226725672781

Table 5

Proportion of urban bridges at different intact state"

年份状态等级
ABCDE
201569.6024.365.560.490.00
201649.7541.557.441.170.09
201752.4039.617.150.800.04
201852.2441.275.820.590.08

Table 6

Model prediction results and relative errors"

年份模型A级B级C级
预测误差预测误差预测误差
2016回归51.43316.316121.32187
马氏链42.351529.822819.71165
生存57.741631.01259.3326
2017回归46.341213.736528.22295
马氏链37.692829.012722.29212
生存56.57831.63209.7036
2018回归38.472620.845028.99398
马氏链33.543627.94324.37319
生存55.28632.282210.1474
1 孙立军. 道路与机场设施管理学[M]. 北京: 人民交通出版社, 2009.
2 周志星. 混凝土梁桥结构技术状况退化预测研究[D]. 重庆: 重庆交通大学土木工程学院, 2016.
Zhou Zhi-xing. Research on degradation prediction of structural status of concrete beam bridges[D]. Chongqing: College of Civil Engineering, Chongqing Jiaotong University, 2016.
3 Mishalani R G, Madanat S M. Computation of infrastructure transition probabilities using stochastic duration models[J]. Journal of Infrastructure Systems, 2002, 8(4): 139-148.
4 吉婉欣. 城市桥梁使用性能衰变分析与预测研究[D]. 上海: 同济大学交通运输工程学院, 2014.
Ji Wan-xin. Deterioration analysis and forecasting model of urban bridges[D]. Shanghai: School of Transportation Engineering, Tongji University, 2014.
5 杨良, 孙立军. 钢筋混凝土桥梁使用性能衰变特征分析[J]. 武汉理工大学学报： 交通科学与工程版, 2014, 38(5): 989-992.
Yang Liang, Sun Li-jun. Analysis of service performance decay characteristic of reinforced concrete bridge[J]. Journal of Wuhan University of Technology (Transportation Science and Engineering), 2014, 38(5): 989-992.
6 陈长. 交通基础设施管理系统技术结构研究[D]. 上海: 同济大学交通运输工程学院, 2005.
Chen Zhang. Research on technical structure of transportation infrastructure management system[D]. Shanghai: School of Transportation Engineering, Tongji University, 2005.
7 Roelfstra G, Hajdin R, Adey B, et al. Condition evolution in bridge management systems and corrosion-induced deterioration[J]. Journal of Bridge Engineering, 2004, 9(3): 268-277.
8 肖萍. 桥梁技术状况评价与预测[D]. 西安: 长安大学土木工程学院, 2003.
Xiao Ping. Evaluation and prediction of bridge technology status[D]. Xi'an: College of Civil Engineering, Chang'an University, 2003.
9 Su D, Nassif H, Hwang E S. Probabilistic approach for forecasting long term performance of girder bridges[R]. TRB Committee AHD35 Bridge Management， Washington DC, United States， 2015.
10 Li L, Sun L, Ning G. Deterioration prediction of urban bridges on network level using markov-chain model[J]. Mathematical Problems in Engineering, 2014(7): 1-10.
11 中华人民共和国住房和城乡建设部. CJJ 99-2017城市桥梁养护技术标准[M]. 北京: 中国建筑工业出版社, 2017.
12 曾胜男, 孙立军. 基于构件的桥梁缺损状况分层加权评价方法[J]. 同济大学学报： 自然科学版, 2006, 34(11): 1475-1478, 1498.
Zeng Sheng-nan, Sun Li-jun. A hierarchy-weight evaluation method of bridge distress condition[J]. Journal of Tongji University (Natural Science), 2006, 34(11): 1475-1478, 1498.
13 Morcous G. Performance prediction of bridge deck systems using Markov chains[J]. Journal of Performance of Constructed Facilities, 2006, 20(2): 146-155.
14 Veshosky D, Beidleman C R, Buetow G W, et al. Comparative analysis of bridge superstructure deterioration[J]. Journal of Structural Engineering, 1994, 120(7): 2123-2136.
15 Agrawal A K, Kawaguchi A, Chen Z. Deterioration rates of typical bridge elements in New York[J]. Journal of Bridge Engineering, 2010, 15(4): 419-429.
16 van Casteren J. Power system reliability assessment using the weibull-markov model[D]. Sweden: Licentiate Thesis, Electric Power Engineering Department, Chalmers University of Technology, 2001.
17 Fang Y, Li L, Chen Z, et al. Prediction model of concrete girder bridge deterioration in Shanghai using weibull-distribution method[C]∥Transportation Research Board 96th Annual Meeting, Washington DC, United States, 2017: 202-217.
18 Madanat S M, Karlaftis M G, Mccarthy P S. Probabilistic infrastructure deterioration models with panel data[J]. Journal of Infrastructure Systems, 1997, 3(1): 4-9.
19 Lu P, Pei S, Tolliver D, et al. Data-based evaluation of regression models for bridge component deterioration[C]∥Transportation Research Board 94th Annual Meeting, Washington DC, United States, 2015.
20 Winn E, Burgueno R, Haider S W. Project-and network-level bridge deck degradation models via neural networks trained on empirical data[C]∥Transportation Research Board Meeting, Washington DC, 2013.
21 马泽欣, 刘黎萍, 孙立军. 基于加速加载的在役沥青混合料损伤与疲劳性能[J]. 吉林大学学报: 工学版, 2019, 49(2): 384-391.
Ma Ze-xin, Liu Li-ping, Sun Li-jun. Damage and fatigue performance of in service asphalt mixtures based on accelerated loading test[J]. Journal of Jilin University (Engineering and Technology Edition), 2019, 49(2): 384-391.
22 郭学东, 张立业, 董丽娟, 等. 桥梁系统可靠性评估方法[J]. 吉林大学学报: 工学版, 2012, 42(3): 634-638.
Guo Xue-dong, Zhang Li-ye, Dong Li-juan, et al. Bridge system reliability evaluation method[J]. Journal of Jilin University (Engineering and Technology Edition), 2012, 42(3): 634-638.
[1] Peng-hui WANG,Hong-xia QIAO,Qiong FENG,Hui CAO,Shao-yong WEN. Durability model of magnesium oxychloride-coated reinforced concrete under the two coupling factors [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(1): 191-201.
[2] Ying WANG,Ping LI,Teng-fei NIAN,Ji-bin JIANG. Short-term water damage characteristics of asphalt mixture based on dynamic water scour effect [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(1): 174-182.
[3] Ping WAN,Chao-zhong WU,Xiao-feng MA. Discriminating threshold of driving anger intensity based on driving behavior features by ROC curve analysis [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(1): 121-131.
[4] Rui XIONG,Ning QIAO,Ci CHU,Fa YANG,Bo-wen GUAN,Yan-ping SHENG,Dong-yu NIU. Investigation on low-temperature rheology and adhesion properties of salt-doped asphalt mortars [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(1): 183-190.
[5] Chun-feng ZHU,Yong-chun CHENG,Chun-yu LIANG,Bo XIAO. Road performance experiment of diatomite⁃basalt fiber composite modified asphalt mixture [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(1): 165-173.
[6] Sheng-tong DI,Chao JIA,Wei-guo QIAO,Kang LI,Kai TONG. Loading rate effect of meso⁃damage characteristics of crumb rubber concrete [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(6): 1900-1910.
[7] Yun-long ZHANG,Liu-guang ZHOU,Jing WANG,Chun-li WU,Xiang LYU. Effects of freeze-thaw cycles on mechanical properties of silty sand and subgrade slope stability [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(5): 1531-1538.
[8] Yong PENG,Hua GAO,Lei WAN,Gui-ying LIU. Numerical simulation of influence factors of splitting strength of asphalt mixtures [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(5): 1521-1530.
[9] Xiao⁃zhen LI,Jun⁃zhe LIU,Yan⁃hua DAI,Zhi⁃min HE,Ming⁃fang BA,Yu⁃shun LI. Effect of carbonation on nitrite ion distribution in cement paste [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1162-1168.
[10] Wu⁃jiao XU,Cheng⁃shang LIU,Xin⁃yao LU. Simulation and prediction of surface roughness of 6061 aluminum alloy workpiece after shot peening [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1280-1287.
[11] Tian⁃lai YU,Hai⁃sheng LI,Wei HUANG,Si⁃jia WANG. Shear strengthening of reinforced concrete beam with prestressed steel wire ropes [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1134-1143.
[12] Xiao⁃ming HUANG,Qing⁃qing CAO,Xiu⁃yu LIU,Jia⁃ying CHEN,Xing⁃lin ZHOU. Simulation of vehicle braking performance on rainy daysbased on pavement surface fractal friction theory [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(3): 757-765.
[13] Jing WANG,Xiang LYU,Xiao⁃long QU,Chun⁃ling ZHONG,Yun⁃long ZHANG. Analysis of relationship between subgrade soil shear strength and chemical and minerals component [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(3): 766-772.
[14] LI Yi,LIU Li-ping,SUN Li-jun. Prediction model on rutting equivalent temperature for asphalt pavement at different depth [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1703-1711.
[15] NIAN Teng-fei, LI Ping, LIN Mei. Micro-morphology and gray entropy analysis of asphalt characteristics functional groups and rheological parameters under freeze-thaw cycles [J]. 吉林大学学报(工学版), 2018, 48(4): 1045-1054.
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