基于变换步长的车辆压线声信号包络提取算法

doi:10.11772/j.issn.1001-9081.2017.12.3625

计算机应用 ›› 2017, Vol. 37 ›› Issue (12): 3625-3630.DOI: 10.11772/j.issn.1001-9081.2017.12.3625

• 应用前沿、交叉与综合 • 上一篇

基于变换步长的车辆压线声信号包络提取算法

蓝章礼¹, 黄芬^1,2

1. 重庆交通大学信息科学与工程学院, 重庆 400074;
2. 重庆文化职业艺术学院基础教育部, 重庆 400067

收稿日期:2017-05-22 修回日期:2017-07-27 发布日期:2017-12-18 出版日期:2017-12-10
通讯作者: 黄芬
作者简介:蓝章礼(1973-),男,重庆人,教授,博士,CCF会员,主要研究方向:算法设计、信号处理、交通信息化、桥梁健康监测、模式识别;黄芬(1990-),女,河南商丘人,硕士研究生,主要研究方向:算法设计、信号处理、交通信息化。
基金资助:
重庆市基础科学与前沿技术研究专项（cstc2016jcyjA0345）。

Envelope extraction algorithm for acoustic signal of vehicle pressing line based on variable step size

LAN Zhangli¹, HUANG Fen^1,2

1. School of Information Science and Engineering, Chongqing Jiaotong University, Chongqing 400074, China;
2. Department of Basic Education, Chongqing Vocational College of Culture and Arts, Chongqing 400067, China

Received:2017-05-22 Revised:2017-07-27 Online:2017-12-18 Published:2017-12-10
Supported by:
This work is partially supported by the Chongqing Research Program of Basic Research and Frontier Technology (cstc2016jcyjA0345).

摘要/Abstract

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。

关键词: 交通智能检测, 包络提取, 特征参数, 变换步长

Abstract: The acoustic signal waveform of vehicle through the deceleration zone is different from that of the normal running on the road, the extraction of its feature parameters is crucial to the automatic judgment of number, speed and type of vehicles, and the acoustic signal envelope curve has many advantages in extracting its feature parameters compared with the original signal. However, the traditional envelope extraction algorithm has the problems that there are many burrs and it is difficult for the feature parameters to truly reflect the signal properties and features in the envelope extraction of acoustic signals in such traffic domain. In order to solve the problems, combined with the characteristics of acoustic signals of vehicles through the deceleration zone, a new envelope extraction algorithm for acoustic signal of vehicle pressing line based on variable step size was proposed. Different step sizes were set to traverse the signal. The curve was plotted by using the maximum point in each step and compared with the original signal waveform. The sharp definition and error of feature point extraction were taken as the judgment basis to realize the effective extraction of the acoustic signal envelope. The experimental results show that, under the same number of sampling points, the extracted envelope curve by the proposed algorithm is more clear and has less burrs than that by the traditional envelope extraction algorithm, and the extraction error of feature parameters is smaller.

Key words: traffic intelligent detection, envelope extraction, feature parameter, variable step size

中图分类号:

蓝章礼, 黄芬. 基于变换步长的车辆压线声信号包络提取算法[J]. 计算机应用, 2017, 37(12): 3625-3630.

LAN Zhangli, HUANG Fen. Envelope extraction algorithm for acoustic signal of vehicle pressing line based on variable step size[J]. Journal of Computer Applications, 2017, 37(12): 3625-3630.

参考文献

[1] 焦琴琴,牛力瑶,孙壮文.基于车辆声音及震动信号相融合的车型识别[J].微型机与应用,2015,34(11):79-82.(JIAO Q Q, NIU L Y, SUN Z W. Vehicle recognition based on fusion of acoustic and seismic signals[J]. Microcomputer & its Applications, 2015, 34(11):79-82.)
[2] 靳舜.基于声音和震动信号特征融合的车型识别研究[D].西安:长安大学,2014:3-5.(JIN S. Vehicle identification research based on feature fusion of acoustic and seismic signals[D]. Xi'an:Chang'an University, 2014:3-5.)
[3] 李云焕.基于声音识别的交通信息检测技术研究[D].西安:长安大学,2014:11-14.(LI Y H. Research of traffic information detection technology based on voice recognition[D]. Xi'an:Chang'an University, 2014:11-14.)
[4] 周酥,朱蒂,吴效明,等.基于小波变换的心音包络提取算法及应用[J].中国组织工程研究与临床康复,2011,15(30):5615-5619.(ZHOU S, ZHU D, WU X M, et al. Envelope extraction algorithm and phonocardiogram signal application based on wavelet transform[J]. Journal of Clinical Rehabilitative Tissue Engineering Research, 2011, 15(30):5615-5619.)
[5] HUANG D. A wavelet-based algorithm for the hilbert transform[J]. Mechanical Systems & Signal Processing, 1996, 10(2):125-134.
[6] 张绪省,朱贻盛,成晓雄,等.信号包络提取方法——从希尔伯特变换到小波变换[J].电子科学学刊,1997,19(1):120-123.(ZHANG X S, ZHU Y S, CHENG X X, et al. The method of extracting signal envelope-from Hilbert transform to wavelet transform[J]. Journal of Electronics, 1997, 19(1):120-123.)
[7] 王光荣.基于Hilbert变换的信号包络提取方法研究[J].中国科技信息,2012(1):87-88.(WANG G R. The research of envelope demosulation analysis methods on noise and vibration[J]. China Science and Technology Information, 2012(1):87-88.)
[8] 张盈盈,潘宏侠,郑茂远.基于小波包和Hilbert包络分析的滚动轴承故障诊断方法[J].电子测试,2010(6):20-23.(ZHANG Y Y, PAN H X, ZHENG M Y. Rolling bearings fault diagnosis based on wavelet packet and Hilbert envelope analysis[J]. Electronic Test, 2010(6):20-23.)
[9] 侯铁双.基于复解析小波变换的信号包络检测[J].西安邮电大学学报,2011,16(3):18-21.(HOU T S. Detection of signal envelope based on the complex analytical wavelet transform[J]. Journal of Xi'an University of Posts and Telecommunications, 2011, 16(3):18-21.)
[10] 刘彬,戴桂平,林洪彬.一种改进的基于小波变换的包络提取算法研究[J].仪器仪表学报,2006,27(1):34-37.(LIU B, DAI G P, LIN H B. Study on an improved envelope extraction algorithm based on wavelet transform[J]. Chinese Journal of Scientific Instrument, 2006, 27(1):34-37.)
[11] 蔡国娟.基于包络分析的轴承故障诊断[J].石油化工设备技术,2014,35(2):41-43.(CAI G J. Bearing fault diagnosis based on envelope analysis[J]. Petrochemical Equipment Technology, 2014, 35(2):41-43.)

基于变换步长的车辆压线声信号包络提取算法

Envelope extraction algorithm for acoustic signal of vehicle pressing line based on variable step size

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