A Study on TPMS Pre-warning Threshold Algorithm Based on Multi-sensor Data Fusion
Abstract
In order to improve the precision of the tire pressure monitoring system, the Bayes method is applied to establish its mathematical model of multi-sensor information fusion. The temperature and pressure in the tire, which are the complementary information, are integrated in the model through analyzing the mechanism of tire burst generated by temperature and pressure. Through the temperature compensation of tire burst pressure threshold value, the false alarm and false negative are avoided to the hilt. The experimental results show that compared with the traditional TPMS, the accuracy of the measuring results of this model is improved and thus the system’s monitoring ability is improved so that the traffic safety is guaranteed.
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