In China recent accidents of sudden collapses of in-service bridges have aroused great concern about the real traffic load and bearing capacity of existing bridges. The proper management of existing bridges relies on accurate information of bridge operating load which is essential for correct assessment of operation and safety of bridges. An integrated load identification system for operating traffic which is built on characteristics of orthotropic steel deck, that is, the locality of stress influence line of orthotropic steel deck, and is based upon BWIM technique to establish functional relation between axle load and stress history, Case study of stress monitoring was carried out on two truss bridges with orthotropic steel deck under both controlled and normal traffic conditions to verify the system. In the case of controlled traffic, monitored information was used to back calculate axle load. The load information was compared with synchronous video recording of the traffic to check inversely calculated data about wheel weight and its lateral deviation between actual condition, The results show that the established identification system is accurate and valid. In the case of normal traffic, monitored stress data were used to back calculate axle load and wheel lateral distribution. From the results, axle load spectrum is abstracted and can directly help assessment of real load capacity and fatigue life of the bridge.
Abnormal Vehicle Load Identification Method Based on Genetic Algorithm and Wireless Sensor Network
