摘要
智能轮胎监控系统装备在汽车轮胎中,为汽车提供轮胎运行过程中的实时底层信息。为了使车载系统能够得到更多的轮胎底层信息,提出了一种基于BP神经网络的轮胎磨损程度检测算法。通过安装在轮胎内壁中的温度胎压传感器与加速度传感器,在不同磨损程度的轮胎运行条件下,采集轮胎底层的温度和胎压数据,与加速度传感器测得的基于传感器的三轴加速度,进行数据整理与数据挖掘。算法构建了一个八层的神经网络对训练集进行学习,并用测试集进行测试,误差均在0.4 mm以内,能够准确预测运行过程中的轮胎磨损程度,加强了汽车底层信息的监控系统,提高了安全性。
The intelligent tire monitoring system is equipped in the car tires to provide the car with real-time bottom-level information during the operation of the tire.In order to enable the vehicle-mounted system to obtain more information about the tire bottom layer,a tire wear detection algorithm based on BP neural network was proposed.When using this algorithm,through the tire temperature&pressure sensors and acceleration sensors installed in the inner wall of the tire,the temperature and tire pressure data of the bottom layers of tires were collected under different tire operating conditions with different degrees of wear,in combination of the triaxial acceleration measured by the acceleration sensors based on the sensor for data sorting and data mining.The algorithm built an eight-layer neural network to learn from the training set and tested it with the test set.The errors are all within 0.4 mm.This algorithm can accurately predict the degree of tire wear during operation,thus strengthening the monitoring system of vehicle bottom information and improving safety.
作者
张越
张峰
张峰瑞
储昊昀
张士文
Zhang Yue;Zhang Feng;Zhang Fengrui;Chu Haoyun;Zhang Shiwen(National Experimental Teaching Demonstration Center of Electrical Engineering and Electronics,Shanghai Jiao Tong University,Shanghai 200240,China)
出处
《电气自动化》
2023年第1期109-112,共4页
Electrical Automation
关键词
智能轮胎
监控系统
磨损检测
数据挖掘
BP神经网络
intelligent tire
monitoring system
tire wear detection
data mining
BP neural network
