Probabilistic Bridge Weigh-in-Motion

OBrien, Eugene J. and Zhang, Longwei and Zhao, Hua and Hajializadeh, Donya (2018) Probabilistic Bridge Weigh-in-Motion. Canadian Journal of Civil Engineering, 45 (8). pp. 667-675. ISSN 1208-6029

Accepted Version
Available under the following license: Creative Commons Attribution Non-commercial No Derivatives.

Download (484kB) | Preview
Official URL:


Conventional bridge weigh-in-motion (BWIM) uses a bridge influence line to find the axle weights of passing vehicles that minimize the sum of squares of differences between theoretical and measured responses. An alternative approach, probabilistic bridge weigh-in-motion (pBWIM), is proposed here. The pBWIM approach uses a probabilistic influence line and seeks to find the most probable axle weights, given the measurements. The inferred axle weights are those with the greatest probability amongst all possible combinations of values. The measurement sensors used in pBWIM are similar to BWIM, containing free-of-axle detector (FAD) sensors to calculate axle spacings and vehicle speed and weighing sensors to record deformations of the bridge. The pBWIM concept is tested here using a numerical model and a bridge in Slovenia. In a simulation, two hundred randomly generated 2-axle trucks pass over a 6 m long simply supported beam. The bending moment at mid-span is used to find the axle weights. In the field tests, seventy-seven pre-weighed trucks traveled over an integral slab bridge and the strain response in the soffit at mid-span was recorded. Results show that pBWIM has good potential to improve the accuracy of BWIM.

Item Type: Journal Article
Keywords: Bridge WIM, Probabilistic Load modelling, pWIM
Faculty: ARCHIVED Faculty of Science & Technology (until September 2018)
Depositing User: Donya Hajializadeh
Date Deposited: 07 Feb 2018 14:09
Last Modified: 09 Sep 2021 18:56

Actions (login required)

Edit Item Edit Item