Traditional ways to acquire information on truck axle and gross weight are expensive and subject to bias, and this led to the development of weight-in-motion (WIM) techniques. Most of the existing WIM systems have been developed to measure only the static axle loads. However, dynamic axle loads are also important. Some systems use instrumented vehicles to measure dynamic axle loads, but are subject to bias. All of this prompted 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 axle loads from bridge responses, The four methods are interpretive method I, interpretive method II, time domain method, and frequency-time domain method. Examples and experiments in laboratory show that all the four methods are feasible and the time domain method and frequency-time domain method give very good results even when 5% noise is added to the simulated input data
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