A Comparative Study of Moving Force Identification

Traditional ways to acquire truck axle and gross weight information are expensive and subject to bias, and this has led to the development of Weigh-¬in-Motion (WIM) techniques. Most of the existing WIM systems have been developed to measure only the static axle loads. However dynamic axle loads arc also important. Some systems use instrumented vehicles to measure dynamic axle loads, but are subject to bias. These all prompt the need to develop a system to measure the dynamic axle loads using an unbiased. random sample of vehicles. This paper aims to introduce four methods in determining such dynamic forces from bridge responses. The four methods are compared with one another based on maximum number of forces to be identified, minimum number of sensors, sensitivity towards noise and the computation time. It is concluded that acceptable estimates could be obtained by all the four methods. Further work includes merging the four methods into a Moving Force Identification System (MFIS).