公路车载动态称重系统的设计与开发 2

公路车载动态称重系统的设计与开发

摘要

公路车载动态称重系统的设计对于保护公路的正常使用有着重要的经济意义和社

会价值。随着公路运输工业生产和商业贸易的不断发展，产生了对公路车辆进行动态称

重越来越严格的要求，动态称重是路政部门加强正常运输、强制超载超限、提高管理工

作效率，实现路政系统管理现代化、科学化的一项关键技术。

就公路车载动态称重系统而言，称重的精度是最重要的性能指标，它标志着公路车

载动态称重系统的技术水平的高低。目前公路车载动态称重系统由于对采集的信号只能

简单的处理，加上建立的数学模型不适合非线性对象的特殊性，同时缺乏对干扰因素以

及各种干扰因素之间的关系做深层次的研究和处理，所以系统的精度难以得到很大的提高。

鉴于影响动态称重的干扰因素很多，而且这些因素之间不存在确切的函数关系，用

传统的数学模型方法很难分析清楚这些干扰因素之间的关系，所以本文从理论基础方面

入手，从提高称重精度的思想出发，介绍了应用于车载动态称重系统的各种智能算法模型，比较分析发现对于非线性对象没有解决误差精度问题，最终提出善于非线性建模的BP 神经网络技术，包括网络的基本思想、计算过程、执行步骤、存在的问题，以及针

对动态称重对象的非线性特征以及称重过程中存在的精度不准确问题采取了BP 算法

的改进方法，进一步满足了现场环境的称重要求。

通过分析公路车载动态称重对象，建立了BP 神经网络动态称重系统模型，根据现

场采集的动态称重数据进行了网络模型的分析与数据训练，训练结果表明精度完全符合

现场要求和国家标准。对于系统硬件方面，系统采用单片机进行数据采集与传送，对单

片机的选择进行了介绍；用于数据处理的动态称重软件系统除了实现重量数据的处理、

显示和查询等基本功能以外，它还实现了将采集的数据保存于数据库中并能以报表的形

式打印出来的功能，以便于统计和查阅。本文中主要用到的单片机开发工具是 C 语言，工控机里的数据处理系统软件采用Visual C++ 6.0 编程语言，主要利用RS-232 串行接口来提供串口通信，使用BP 神经网络对称重采集的数据建模仿真的环境是MA TLAB

R2007。

关键词：动态称重系统，单片机，数学模型，BP 神经网络

DESIGNATION AND EMPOLDER OF HIGHW AY

CAR-LOADING WEIGH-IN-MOTION SYSTEM

ABSTRACT

The Highway Car-loading Weigh-in-Motion system（WIMS）has undoubtedly played an antive electronic role and social value in the protection of highway trancport. Along with the development of the Highway Transportation,Industrial production and Business Trade, it is required that the Highway WIMS needs to saticfy more qualification of modernization and scientization for the rapid automatically and the enforcement of the overloading rule.

As to the Highway Car-loading WIMS, the weighing precision of the vehicle moving is

the most important standard specification. It indicates the technical level of the Highway

Car-loading WIMS. While the weighing signal processing of the actual Weigh-in-Motion is simple digital filter and the model is not fit well with non-leneared object. Even further signal processing technique of kinds of disturbing factors. So the WIM system’s precision is hardly improved.

Because there are so many factors affect the WIMS’accuracy, and there are not exact function relations among these factors, this paper introduces some new arithmetic models to settle these factors compared with other models.In theory of improving the WIM system’s precision, final chance is choosing BP neural network. It mostly introduces the basic idea, calculated process, executes steps and existed problems of BP Neural Network, and Finally puts forward the improved method to satisfy weigh-in-motion requirement.

Through analyzing Highway WIMS’cars,this paper bases BP Neural Nerwork model.

The weigh-in-motion datas, which gathered in scene and trained by the BP Neural Network model, indicate that the precision accords with practical requirement and international standard. In hardware, the system use single-chip microcomputer and introduced the choosing condition of the single-ship microcomputer. The WIM system of the paper described can implement not only the basic function of gathering data, processing data, display data, and query data,but preserved the gathering data into the database and print in form. The system mainly use C language to write in the single-chip microcomputer, and use Visual C++ 6.0 to write in the computer for processing data. The RS-232 is used to communicate the

serial.Otherwise, the paper use MATLAB R2007 language to model weighing system, simulink and train the weighing datas.

Key Words: Weigh-in-Motion System, Single-Chip Microcomputer, System Math Modeling, BP Neural Network