Bridge vehicle load model on different grades of roads in China based on Weigh-in-Motion (WIM) data

被引:32
作者
Chen, Bin [1 ,4 ]
Ye, Ze-nan [2 ]
Chen, Zengshun [3 ]
Xie, Xu [1 ]
机构
[1] Zhejiang Univ Technol, Coll Civil Engn & Architecture, Hangzhou, Zhejiang, Peoples R China
[2] Hangzhou Normal Univ, Dept Math, Hangzhou, Zhejiang, Peoples R China
[3] Hong Kong Univ Sci & Technol, Dept Civil & Environm Engn, Kowloon, Hong Kong, Peoples R China
[4] Zhejiang Univ, Coll Civil Engn & Architecture, Hangzhou, Zhejiang, Peoples R China
关键词
Steel bridge; Vehicle load model; Field measurement; Probability distribution; Fatigue load model; DESIGN; GPS;
D O I
10.1016/j.measurement.2018.03.005
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Bridge vehicle load is an important parameter that is relevant to the construction and maintenance stages of a bridge. In recent years, a large number of orthotropic steel deck bridges have been built in China, and it is urgent to establish a fatigue load model that reflects the actual traffic conditions of the bridges. This study has investigated the variation of vehicles over time on four grades of road (expressway, first-class highway, second-class highway and urban main road) according to the weight-in-motion (WIM) data. Subsequently, the statistical model was established in terms of speed, axle weight, and gross weight of vehicle (GVW) acting on the four grades of road. Finally, a fatigue load model of vehicles on the four grades of road was established based on a two-stage method. The results show that (1) the speed of vehicle on the four grades of road obeys the unimodal distribution; (2) the GVW of two- and three-axle vehicles on the four grades of road belongs to the t-distribution and the log-normal distribution, respectively; (3) the GVW of four- and five-axle vehicles on expressways is a finite mixed distribution, whereas the GVW of four- and five-axle vehicles on the remain three grades of road obeys the log-logistic and log-normal distribution respectively; (4) the GVW of six- and above axle vehicles on expressways and second-class highways obeys a finite mixed distribution with two variables, whereas that on first-class and urban main roads obeys the log-normal distribution; (5) the axle weight of standard fatigue vehicles differs remarkably on different grades of roads, which is difficult to describe the fatigue damage in a uniform standard fatigue vehicle.
引用
收藏
页码:670 / 678
页数:9
相关论文
共 35 条
[31]   STRESS CYCLES FOR FATIGUE DESIGN OF STEEL BRIDGES [J].
SCHILLING, CG .
JOURNAL OF STRUCTURAL ENGINEERING-ASCE, 1984, 110 (06) :1222-1234
[32]   ESTIMATING DIMENSION OF A MODEL [J].
SCHWARZ, G .
ANNALS OF STATISTICS, 1978, 6 (02) :461-464
[33]   Wavelet based multi-step filtering method for bridge health monitoring using GPS and accelerometer [J].
Yi, Ting-Hua ;
Li, Hong-Nan ;
Gu, Ming .
SMART STRUCTURES AND SYSTEMS, 2013, 11 (04) :331-348
[34]   Experimental assessment of high-rate GPS receivers for deformation monitoring of bridge [J].
Yi, Ting-Hua ;
Li, Hong-Nan ;
Gu, Ming .
MEASUREMENT, 2013, 46 (01) :420-432
[35]   Damage detection in bridge structures under moving loads with phase trajectory change of multi-type vibration measurements [J].
Zhang, Weiwei ;
Li, Jun ;
Hao, Hong ;
Ma, Hongwei .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2017, 87 :410-425