基于神经网络的车辆动态称重系统设计和应用

Design and Application of Vehicle Dynamic Weighing System Based on Neural Network

基于动态化车辆承重特点,设计了一种基于神经网络的车辆动态称重系统,能够基于神经网络自适应滤波变步长LMS算法,过滤不同频段称重信号产生的噪声。处于不同环境下针对不同车型,达到了较好的技术适应度且速度较快,精准度较高。可以对高速公路经过车辆重量动态计划实现精准测量,满足测量精准度需求,存在理论及实践参考价值。该系统选择高性能TMS32C2812芯片,设计较高软硬件系统,可以对高速公路上的经过车辆重量动态计划精准测量。

Based on the characteristics of dynamic vehicle load-bearing,this research proposes a vehicle dynamic weighing system based on neural network.The system can adaptively complete the filter LMS algorithm with variable step size based on neural network,and filter the noise generated by weighing signals in different frequency bands.In different environments for different models,it has achieved better technical adaptability,faster speed and higher accuracy.It can realize accurate measurement for the dynamic plan of vehicle weight of expressway,meet the demand of measurement accuracy,and have theoretical and practical reference value.Through the application of the system,the high-performance TMS32c2812 chip is selected and the high-performance software and hardware systems are adopted to accurately measure the dynamic plan of the passing vehicle weight on the highway.