吉林大学学报(工学版) ›› 2020, Vol. 50 ›› Issue (2): 557-564.doi: 10.13229/j.cnki.jdxbgxb20190082

• 交通运输工程·土木工程 • 上一篇    

基于生存分析的城市桥梁使用性能衰变模型

方宇(),孙立军()   

  1. 同济大学 道路与交通工程教育部重点实验室,上海 201804
  • 收稿日期:2019-01-18 出版日期:2020-03-01 发布日期:2020-03-08
  • 通讯作者: 孙立军 E-mail:1610049@tongji.edu.cn;ljsun@tongji.edu.cn
  • 作者简介:方宇(1992-),男,博士研究生.研究方向:交通基础设施管理.E-mail:1610049@tongji.edu.cn
  • 基金资助:
    国家自然科学基金项目(51678443);国家重点研发计划项目(2018YFB1600100)

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

摘要:

使用上海市城市桥梁的历年常规检测数据,基于生存分析理论建立了桥梁使用性能衰变的概率性预测模型。同时,利用韦伯分布的可靠性函数深入描述了不同等级内桥梁各部位的性能衰变行为,研究表明:当前上海市城市桥梁在状态等级为A级和B级时持续周期相对较短;且相比于下部结构,桥梁的桥面系和上部结构的性能衰变速率更快。最后,根据2016年~2018年网级桥梁衰变预测的实际算例,对比了生存分析与回归分析、马尔科夫链的预测效果差异,验证了生存分析模型具有较高的预测精度。

关键词: 道路工程, 桥梁性能, 预测模型, 生存分析, 韦伯分布

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

中图分类号: 

  • U418

表1

城市桥梁完好状态分级"

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

图1

上海市城市桥梁BCI等级变迁趋势"

图2

桥梁性能衰变过程的持续周期"

表2

2004年以来BMS数据库存储的检测记录"

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

表3

韦伯分布参数估计结果"

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

图3

各状态等级下韦伯分布的可靠性函数"

表4

桥梁各部位平均期望寿命 (年)"

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

表5

各状态等级城市桥梁所占比例分布 (%)"

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

表6

模型预测结果与相对误差 (%)"

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
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