摘要
针对双秤台汽车衡的车辆动态称重进行了算法研究,提出了先使用小波变换对称重信号滤波预处理,使用专家系统识别车辆轴型,用车轴的速度计算加速度,最后依据双秤台传感器称重信号、速度信号、加速度信号、以及车辆轴型组建BP网络模型,利用BP网络算法良好的自我学习能力,对大量实测数据进行训练,达到了一定的动态称重测量精度,取得了较好的效果。
An algorithm is presented,aiming at vehicle dynamic weighing based on double weighing platform truck scale. Firstly,it uses wavelet transformation to filter weighing signal,use expert system to identify type of vehicle,and uses speed of axle to calculate its acceleration,according to weighing signal,signal of speed,signal of acceleration and the axle type of vehicle to build BP network,use good self-learning ability of BP network algorithm,train a large amount of data and achieves certain dynamic weighing precision. Inshort,it achieves better results.
出处
《传感器与微系统》
CSCD
2015年第6期133-136,共4页
Transducer and Microsystem Technologies
关键词
双秤台汽车衡
动态称重
BP网络
小波变换
专家系统
double weighing platform truck scale
dynamic weighing
BP network
wavelet transform
expert system
作者简介
张晓东（1990-），男，山西忻州人，硕士研究生，研究方向为动态称重与智能仪器。
