基于BP神经网络的四轮胎压监测算法研究

Study on the algorithm of four-wheel tire pressure monitoring based on BP neural network

4个车轮同时缺气时,传统滚动半径法很难监测出轮胎压力值,导致误报率较高。为解决该问题,提出了一种基于BP神经网络的间接式四轮胎压缺气监测方法,通过采集轮速脉冲数对BP神经网络进行训练,实现对4个车轮同时缺气时的胎压识别。实验结果表明:训练后的BP神经网络可以有效识别4个车轮同时缺气时的压力值,误报基本消除,该方法为4个车轮同时缺气时的胎压监测研究提供了新的方向。

When four wheels are short of air at the same time,the traditional rolling radius method is difficult to detect the tire pressure value and has a high false alarm rate.In order to solve this problem,it proposed an indirect four-wheel tire pressure and lack of air monitoring method based on BP neural network,by collecting the number of wheel speed pulses,the BP neural network was trained to realize tire pressure identification when four wheels were short of air at the same time.Experimental results showed that the trained BP neural network can effectively identify the pressure value when four wheels were short of air at the same time,and the false alarm was basically eliminated,this method provided a new direction for tire pressure monitoring research when four wheels were short of air at the same time.