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.
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