BP神经网络在汽车动态称重中的应用  

Application of BP Neural Network to Dynamic Weighing with Cars

作　　者：常全伟[1] 张元[1] 余章明[1] 

机构地区：[1]河南工业大学信息科学与工程学院,河南郑州450001

出　　处：《电子质量》2011年第5期37-40,共4页Electronics Quality

摘　　要：公路动态称重仪器测量精度受外界各种因素的影响较大,称重信号与各个影响因素的关系不明确,该文提出了利用神经网络的算法来处理动态称重信号的理论。利用神经网络建立的模型能够将输入的各种信息很好地进行数据融合,能够大大降低外界干扰对输入信号的影响。实验表明,利用神经网络对动态称重信号进行处理,能够满足精度要求。The measurement precision of the Highway dynamic wieghing system is influenced by a variety of factors outside,and the relationship of weighing signal and different factors is not clear,so this paper proposes the theory of handling dynamic weight signal by neural network algorithm.Neural network model can fuse a good variety of data information input,and can greatly reduce the influence of the interference signals loutside to input signals.Experiments show that the neural network for dynamic weighing signal processing,can meet the accuracy requirements.

关 键 词：神经网络 数据融合模型 

分 类 号：TH715.1[机械工程—测试计量技术及仪器]