2002Unpublished venueRequires access

Theoretical testing of a multiple-sensor bridge weigh-in-motion algorithm

Arturo González, M F Green, E J O'Brien, Hong Xie

Open publisher page 2 citations

Abstract

A Bridge Weigh-In-Motion (B-WIM) system is based on the measurement oftheflexure in a bridge and the use of measurements to estimate the attributes of passing traffic loads. The information provided by strain sensors and axle detectors is converted into axle weights through the application of an algorithm. Because the dynamic interaction between bridge and vehicle has many parameters for which estimation is very difficult from raw bridge strains, the traditional B- WIM algorithm consists of static equations of equilibrium. Hence, dynamics can be a significant source of inaccuracy in B-WIM systems depending on the bridge and vehicle characteristics. In this papel~ the influence of dynamics on B- WIM accuracy is assessed numerically by simulating the passage of a number of vehicles over a bridge. Then, the theoretical bridge response is used to test a new B- WIM algorithm based on multiple longitudinal sensor locations and the traditional algorithm based on one single location. In smooth road conditions, the multiple sensor B-WIM achieved better results, while the traditional B- WIM failed to predict individual axle weights accurately. In rough conditions, results were much poorer due to high dynamic excitation and only gross vehicle weight was predicted accurately.

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What this paper is about

A Bridge Weigh-In-Motion (B-WIM) system is based on the measurement oftheflexure in a bridge and the use of measurements to estimate the attributes of passing traffic loads. The information provided by strain sensors and axle detectors is converted into axle weights through the application of an algorithm. Because the dynamic interaction between bridge and vehicle has many parameters for which estimation is very difficult from raw bridge strains, the traditional B- WIM algorithm consists of static equations of equilibrium. Hence, dynamics can be a significant source of inaccuracy in B-WIM systems depending on the bridge and vehicle characteristics. In this papel~ the influence of dynamics on B- WIM accuracy is assessed numerically by simulating the passage of a number of vehicles over a bridge. Then, the theoretical bridge response is used to test a new B- WIM algorithm based on multiple longitudinal sensor locations and the traditional algorithm based on one single location. In smooth road conditions, the multiple sensor B-WIM achieved better results, while the traditional B- WIM failed to predict individual axle weights accurately. In rough conditions, results were much poorer due to high dynamic excitation and only gross vehicle weight was predicted accurately.

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Available abstract

A Bridge Weigh-In-Motion (B-WIM) system is based on the measurement oftheflexure in a bridge and the use of measurements to estimate the attributes of passing traffic loads. The information provided by strain sensors and axle detectors is converted into axle weights through the application of an algorithm. Because the dynamic interaction between bridge and vehicle has many parameters for which estimation is very difficult from raw bridge strains, the traditional B- WIM algorithm consists of static equations of equilibrium. Hence, dynamics can be a significant source of inaccuracy in B-WIM systems depending on the bridge and vehicle characteristics. In this papel~ the influence of dynamics on B- WIM accuracy is assessed numerically by simulating the passage of a number of vehicles over a bridge. Then, the theoretical bridge response is used to test a new B- WIM algorithm based on multiple longitudinal sensor locations and the traditional algorithm based on one single location. In smooth road conditions, the multiple sensor B-WIM achieved better results, while the traditional B- WIM failed to predict individual axle weights accurately. In rough conditions, results were much poorer due to high dynamic excitation and only gross vehicle weight was predicted accurately.

Key concepts: Weigh in motion, Bridge (graph theory), Axle, Algorithm, Structural engineering, Computation, Engineering, Computer science

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