Weigh-in-Motion (WIM) systems have provided an effective means of data collection for pavement research and facility design, traffic monitoring, and weight enforcement. In weight enforcement, WIM systems have been increasingly used to screen potentially overweight vehicles. The use of WIM for screening purposes reduces queuing at weigh stations, resulting in considerable savings for both truckers and enforcement agencies. Many of the vehicle characteristics affecting variation in measured dynamic loads increase exponentially with speed, making it very difficult to infer static weight with appropriate precision at highway speeds. Some methods improved the weigh precision is presented in this paper. As weighing signal is a transient signal mixed with noises, a signal processing method based on wavelet transform was suggested.The wavelet transform has the characteristic of multi-analysis and the ability to analyze partial characteristic both in the time domain and the frequency range. The high frequency signal was de-noised, and the low frequency weighing signal was acquired. At the same time, the ARMA model of WIM is establishment, the problem of Weigh-In-Motion turn into a calculation of estimated parameters. Results show the methods of signal process are effective.

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