The embodiment of the invention provides a tire wear degree identification method and device. The method comprises the steps that the circumferential acceleration sequence and the radial accelerationsequence of a tire in the driving process are acquired, and the sequences are normalized according to the vehicle speed square of the same moment; the normalized circumferential acceleration sequenceand radial acceleration sequence form a sample to be predicted in the form of a two-dimensional matrix; and the sample to be predicted is inputted to a preset convolutional neural network model, and the wear degree of the tire is determined according to the output result of the convolutional neural network model. According to the method, modeling of the complex mechanism of tire wear can be avoided, and wear degree identification can be realized by analyzing the circumferential and radial acceleration response of the tire so that the method is simpler and more convenient and higher in precision and online real-time prediction can be realized. End-to-end wear degree prediction is performed on the recombined acceleration signal matrix by using the powerful feature extraction function of theconvolutional neural network without too much early pretreatment so as to have robustness for the change of the driving condition.
本发明实施例提供一种轮胎磨损程度辨识方法及装置,该方法包括:获取行驶过程中轮胎的周向加速度序列和径向加速度序列,并根据同时刻的车速平方,对序列进行归一化;将归一化后的周向加速度序列和径向加速度序列,组成二维矩阵形式的待预测样本;将所述待预测样本输入至预设的卷积神经网络模型,根据所述卷积神经网络模型的输出结果,确定轮胎的磨损程度。该方法避免了对轮胎磨损复杂机理的建模,通过对轮胎周向、径向加速度响应进行分析实现磨损程度辨识,更加简便且精度更高,能实现在线的实时预测。利用卷积神经网络强大的特征提取功能对重组的加速度信号矩阵进行端到端的磨损程度预测,不需要太多前期预处理,对行车工况的变化具有鲁棒性。
Tire wear degree identification method and device
轮胎磨损程度辨识方法及装置
2020-11-24
Patent
Electronic Resource
Chinese
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