北京航空航天大学学报 ›› 2007, Vol. 33 ›› Issue (09): 1041-1045.

• 论文 • 上一篇    下一篇

汽车动态称重中的一种信号处理方法

吴杰, 费玉华, 于劲松, 万九卿   

  1. 北京航空航天大学 自动化科学与电气工程学院, 北京 100083
  • 收稿日期:2006-09-20 出版日期:2007-09-30 发布日期:2010-09-17
  • 作者简介:吴 杰(1981-),男,河南信阳人,硕士生,maverickwj@gmail.com.

Method of signal processing in weigh-in-motion of vehicles

Wu Jie, Fei Yuhua, Yu Jinsong, Wan Jiuqing   

  1. School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
  • Received:2006-09-20 Online:2007-09-30 Published:2010-09-17

摘要: 为了提高汽车动态称重(WIM, Weigh-In-Motion)系统的称重精度,基于"逆模型"的思想,使用了自适应逆滤波器来充分抑制混叠在重量信号频带内的噪声信号.在有限长冲激响应滤波器的框架下,通过最小均方自适应算法,离线构建了WIM系统的逆系统,并用此逆系统作为一个新型的滤波器使用.而且,为了进一步提高称重精度,同时又采用了低通滤波器,来滤除分布在重量信号频带以外的噪声干扰.经过由自适应逆滤波器和低通滤波器构成的复合滤波器处理后, 称重结果较经参数估计方法处理后得到的结果,在称重精度上有了很大提高.

Abstract: Based on the concept of inverse model, an adaptive inverse filter (AIF) was employed which could suppress noise within the bandwidth of the desired signal. Within the framework of the finite impulse response (FIR) filter, the inverse system of weigh-in-motion (WIM) system was constructed by using least mean square (LMS) adaptive algorithm as an innovative filter. Moreover, for the sake of best improving measurement accuracy, as a noise filter, a low-pass (LP) filter dedicated to restrain noise out of the bandwidth of useful signal was adopted. After processed by cascaded filter combination, namely, AIF filter and LP filter, obtained results, compared with those processed by the approach of parameter estimation, show a significant improvement in estimation of static weight of moving vehicles.

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