Vehicle Load Analysis using Bridge-Weigh-in-Motion System in a Cable Stayed Bridge

This paper describes the procedures developing the algorithm for analyzing signals acquired from the Bridge Weigh-in-Motion (BWIM) system installed in Seohae Bridge as a part of the bridge monitoring system. Through the analysis procedure, information about heavy traffics such as weight, speed, and number of axles are attempted to be extracted from time domain strain data of the BWIM system. One of numerous pattern recognition techniques, artificial neural network (ANN) is employed since it can effectively include dynamic effects, bridge-vehicle interaction, etc. A number of vehicle running experiments with sufficient load cases are executed to acquire training and/or test set of ANN. Extracted traffic information can be utilized for developing quantitative database of loading effect. Also, it can contribute to estimate fatigue lift or current health condition, and design truck can be revised based on the database reflecting recent trend of traffic.

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