Envelope extraction algorithm for acoustic signal of vehicle pressing line based on variable step size
LAN Zhangli1, HUANG Fen1,2
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
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.
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. Journal of Computer Applications, 2017, 37(12): 3625-3630.
[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.)
2017, Vol. 37 
