橡胶油管式车辆行驶称重技术的研究

Weigh-in-motion technology for vehicles using rubber oil pipe

提出了一种橡胶油管的车辆行驶称重技术,并研制了一种便携式车辆行驶称重系统。针对多种因素会对行驶称重系统的输出值产生影响,提出一种与BP神经网络相结合的计算模型,进行数据处理,同时结合信息融合技术建立了车型识别模型及专家系统。经一系列试验证明,该行驶称重系统可实现不同路面的超载检查的要求,为车辆超载检测及交通数据统计提供了一种经济有效的手段。

In this paper, a new Weigh-in-motion (WIM) technology for vehicles using rubber oil pipe is put forward, and a portable WIM system is developed. Because there are several factors that affect the output values of the WIM system, the calculation model using BP Neural Network is set up, and used to carry out data processing. Based on the information fusion technique, recognition model for vehicle classification and expert system were set up. The results of series of tests show that the accuracy of this WIM system meets the requirement of overload detection on most roads. Therefore, this WIM system is an economical and effective tool for vehicle overload detection and traffic data statistics.