东北大学学报（自然科学版）

东北大学学报:自然科学版 ›› 2014, Vol. 35 ›› Issue (11): 1607-1611.DOI: 10.12068/j.issn.1005-3026.2014.11.020

• 资源与土木工程 • 上一篇    下一篇

一种基于同步性的听觉滤波信号关联度分析方法

李允公1，于良会2，叶利丽1，戴丽1   

  1. (1东北大学 机械工程与自动化学院， 辽宁 沈阳110819; 2潍柴动力股份有限公司 技术中心， 山东 潍坊261001)
  • 收稿日期:2013-10-08 修回日期:2013-10-08 出版日期:2014-11-15 发布日期:2014-07-03
  • 通讯作者: 李允公
  • 作者简介:李允公(1976-)，男，辽宁抚顺人，东北大学副教授，博士.
  • 基金资助:
    国家自然科学基金资助项目(51275080).

A Method for Estimating the Degree of Association Between Auditory Filter Signals Based on Synchronism Cue

LI Yungong1， YU Lianghui2， YE Lili1， DAI Li1   

  1. 1. School of Mechanical Engineering & Automation， Northeastern University， Shengyang 110819， China; 2. Technology Center， Weichai Power Co.， Ltd.， Weifang 261001， China.
  • Received:2013-10-08 Revised:2013-10-08 Online:2014-11-15 Published:2014-07-03
  • Contact: LI Yungong
  • About author:-
  • Supported by:
    -

RichHTML

0

PDF (PC)

523

摘要： 受听觉系统运行机制的启发，提出一种以同步性为线索的信号分量间关联度的分析方法.首先对信号进行带通滤波、逆序滤波和半波整流，继而提取一次、二次和三次极值点，并生成三种单位序列.基于单位序列分别计算相邻滤波通道同步性和一、二次极值点同步性，这两种同步性可描述信号分量间的波形吻合程度和波动关联性.分析了带有侧隙的齿轮振动信号，结果表明所提方法可发现具有较高关联性的信号分量，有助于缩减数据量和揭示被测对象的动力行为特性.

关键词: 带通滤波, 时频分解, 听觉模型, 故障诊断, 包络

Abstract: Inspired by the signal processing model of the human auditory system， a method of the degree of association between signal components was proposed. Firstly， the signal was successively processed with Gammatone bandpass filter， inversed order filter and halfwave rectification. Then， the once， twice and thrice extremums were picked out in the waveform after halfwave rectification to generate three kinds of units sequences. By using these units sequences， two synchronisms between adjacent filter channels signals and the once and twice extremums points in different filter channels were calculated respectively. The former synchronism may present the correlation， and the other reflects the degree of fluctuation association. A vibration signal measured from a gear system with tooth backlash is analyzed by the method. The results show the proposed method can discover those signal components with high degree of association， and it is favorable for reducing data size and revealing the dynamic characteristics of the measured system.

Key words: bandpass filter, timefrequency decomposition, auditory model, faults diagnosis, envelope

中图分类号: