传感技术学报2025，Vol.38Issue(3)：458-467,10.DOI:10.3969/j.issn.1004-1699.2025.03.012
基于轮胎垂向加速度的路面不平度等级识别研究
Research on Pavement Unevenness Grade Identification Based on Tire Vertical Acceleration
摘要
Abstract
Targeting at the problem of road surface unevenness grade recognition,a BP neural network recognition method based on the optimal characteristics of tire vertical acceleration is proposed.Firstly,the road surface unevenness model and the two-degree-of-freedom vehicle harshness model are constructed,and the tire vertical acceleration and road surface unevenness level are obtained through simu-lation.Then,based on the vertical acceleration of tires,40 feature extraction schemes are constructed successively,and a random forest model is introduced to evaluate the importance of each feature and preliminarily determine the optimal feature.Finally,40 features are used as input to the BP neural network,and the road surface unevenness level is used as the output,a three-layer BP neural network is constructed,and evaluation criteria such as accuracy are introduced to verify the optimal features.The results show that in the road sur-face unevenness grade recognition task based on the vertical acceleration feature of tires,the optimal feature is the sum of the absolute values of the second-order difference of the signal,and the BP neural network constructed with this feature as input not only has a recog-nition accuracy of 99%,but also has low complexity and good speed robustness.关键词
路面不平度识别/BP神经网络/特征提取/随机森林/轮胎垂向加速度Key words
pavement unevenness recognition/BP neural networks/feature extraction/random forest/tire vertical acceleration分类
交通运输引用本文复制引用
卢俊辰,崔凯特,钟妤馨,胡梦宜,董林玺..基于轮胎垂向加速度的路面不平度等级识别研究[J].传感技术学报,2025,38(3):458-467,10.基金项目
浙江省级人才项目(2021R52009) （2021R52009）
