基于变换步长的车辆压线声信号包络提取算法
发布时间：2018-10-14 10:28
【摘要】：车辆经过减速带时与其在路面正常行驶时的声信号波形明显不同,其特征参数的提取对车辆数量、速度、类型等的自动判断至关重要,声信号包络曲线对其特征参数的提取相比原始信号有诸多优势,但传统包络提取算法在此类交通领域声信号包络提取方面存在毛刺多、特征参数难以真正体现信号性质和特征的问题。为解决此问题,结合车辆经过减速带时的声信号特点,提出一种基于变换步长的车辆压线声信号包络提取算法。该算法通过设置不同步长遍历信号,以每个步长内的最大值点绘制曲线并与原信号波形对比,以轮廓清晰度和特征点提取误差值为判断依据实现声信号包络的有效提取。实验结果表明,在相同采样点数条件下,所提算法比传统包络提取算法提取的包络曲线轮廓更清晰、毛刺少,且特征参数提取误差小。
[Abstract]:When a vehicle passes through a speed reducer, it is obviously different from the sound signal waveform of a vehicle when it is running normally on the road. The extraction of its characteristic parameters is of great importance to the automatic judgment of the number, speed and type of the vehicle, etc. Compared with the original signal, the acoustic signal envelope curve has many advantages over the original signal, but the traditional envelope extraction algorithm has many burrs in this kind of traffic field. It is difficult for the characteristic parameters to reflect the nature and feature of the signal. In order to solve this problem, an envelope extraction algorithm based on the transform step size is proposed to solve the problem, considering the characteristics of the acoustic signals of vehicles passing through the reducer. By setting different step sizes to traverse signals, the algorithm draws the curve with the maximum points in each step and compares with the original signal waveforms, and realizes the effective extraction of acoustic signal envelope according to the judgment of contour clarity and feature points extraction error. The experimental results show that the proposed algorithm is clearer than the traditional envelope extraction algorithm in extracting the contour of the envelope curve with less burr and less error in feature extraction under the same sampling points.
【作者单位】： 重庆交通大学信息科学与工程学院;重庆文化职业艺术学院基础教育部;
【基金】：重庆市基础科学与前沿技术研究专项(cstc2016jcyj A0345)~~
【分类号】：TN911.7;U495
本文编号：2270179
[Abstract]:When a vehicle passes through a speed reducer, it is obviously different from the sound signal waveform of a vehicle when it is running normally on the road. The extraction of its characteristic parameters is of great importance to the automatic judgment of the number, speed and type of the vehicle, etc. Compared with the original signal, the acoustic signal envelope curve has many advantages over the original signal, but the traditional envelope extraction algorithm has many burrs in this kind of traffic field. It is difficult for the characteristic parameters to reflect the nature and feature of the signal. In order to solve this problem, an envelope extraction algorithm based on the transform step size is proposed to solve the problem, considering the characteristics of the acoustic signals of vehicles passing through the reducer. By setting different step sizes to traverse signals, the algorithm draws the curve with the maximum points in each step and compares with the original signal waveforms, and realizes the effective extraction of acoustic signal envelope according to the judgment of contour clarity and feature points extraction error. The experimental results show that the proposed algorithm is clearer than the traditional envelope extraction algorithm in extracting the contour of the envelope curve with less burr and less error in feature extraction under the same sampling points.
【作者单位】： 重庆交通大学信息科学与工程学院;重庆文化职业艺术学院基础教育部;
【基金】：重庆市基础科学与前沿技术研究专项(cstc2016jcyj A0345)~~
【分类号】：TN911.7;U495
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1 邹志云,张席洲,张本勇;武汉市机动车停放特征参数调查研究[J];武汉交通科技大学学报;1999年04期
，本文编号：2270179
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