基于声音信号的车辆识别算法研究

Xiaobo Shen, Jonathan M. Caballero, Ronaldo Juanatas
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引用次数: 0

摘要

随着信息技术的快速发展,交通信息的采集在交通智能管理中起着举足轻重的作用。交通信息采集系统的核心是车辆检测、速度判断和车型识别。作为智能交通的重要组成部分,它被广泛应用于收费系统、交通数据统计等相关工作中,特别是在高速公路自动收费系统中,车辆类型的自动识别起着极其重要的作用。本文以车辆行驶过程中产生的发动机声信号为研究对象。经过信号预处理、小波去噪、AR特征提取后,送入BP神经网络算法进行分类识别。仿真结果表明,该系统具有较高的识别率和较强的稳定性,能够满足实际应用的需要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Vehicle Identification Algorithm Based on Sound Signal
With the fast development of information technology, the collection of traffic information plays a pivotal role in the intelligent management of traffic. The core of traffic information collection system is confirmed in vehicle detection, speed judgment and vehicle type identification. As an important part of intelligent transportation, it is widely used in toll collection system, traffic data statistics and other related work, especially in Expressway Automatic Toll Collection System, The automatic identification of vehicle type plays an extremely important role. The sound signal of engine generated by the driving vehicle is used as the research object in this paper. After signal preprocessing, wavelet denoising and AR feature extraction, it is sent to the BP neural network algorithm for classification and recognition. The simulation results show that the system has high recognition rate and strong stability, and can meet the needs of practical application.
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