基于分布式振动传感的车辆轴载感知方法

Vehicle Axle Load Sensing Based on Distributed Vibration Fiber Technology

摘要:

提出了基于分布式振动传感的车辆轴载感知方法。采用分布式光纤感知路面振动，建立光纤信号与路面振动位移映射关系及车辆轴载反演解析模型。利用足尺试验对所提车辆轴载反演解析模型进行拟合优度验证，并通过自然车辆称重试验验证所提车辆轴载感知算法有效性。结果表明：车辆轴载感知系统对单轴最大估计误差为0.98%，对车辆总重预估精度达到0.34%，且系统精度受车辆速度影响小，符合国家对于单轴2%、总重5%的精度标准。

Abstract:

This paper presents a method for sensing vehicle axle loads using distributed vibration fiber sensors to detect pavement vibrations. A mapping relationship between fiber optic signals and pavement vibration displacements is established， and analytical models for vehicle axle load inversion are proposed. Full-scale experiments are conducted to validate the accuracy of the proposed vehicle axle load inversion analytical models， while natural vehicle weighing tests are performed to verify the effectiveness of the vehicle axle load perception algorithm. The results demonstrate that the vehicle axle load sensing system， based on the inversion analytical models， achieves a maximum estimation error of 0.98% for individual axle loads and a total weight prediction accuracy of 0.34%. These accuracies meet the national standards of 2% for single axle loads and 5% for total weight. Furthermore， the system accuracy remains unaffected by variations in vehicle speed.