Abstract
In order to improve the dynamical respond of the weighing sensor and to meet the demand of rapid weigh-in-motion(WIM), a new adaptive weighing system is introduced. The system consists of sensors, data processing module, control module and interface circuit. For restraining the influence of vehicle speed and vehicle liberation, the system adopts self-adaptive variable step size LMS algorithm based on neural network to filter out the noise of WIM signal. Based on this method of signal processing, a vehicle WIM system based on neural network self adaptive filtering was designed. The experimental results proved that the neural network based method can be used to reduce the weighing time and increase the accuracy simultaneously.
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