基于随机共振及图谱理论的齿轮故障特征提取  

Fault Feature Extraction Method of Gear Root Crack Based on Stochastic Resonance and Graph Fourier Transform Theory

作　　者：刘新厂 孙琦 LIU Xinchang;SUN Qi(School of Automobile and Transportation,Chengdu Technological University,Chengdu 611730,China;School of Mechanical Engineering,Southwest Jiaotong University,Chengdu 611730,Cahina)

机构地区：[1]成都工业学院汽车与交通学院,成都611730 [2]西南交通大学机械学院,成都611730

出　　处：《噪声与振动控制》2022年第2期108-113,共6页Noise and Vibration Control

基　　金：轨道交通运维技术与装备四川省重点实验室开放课题基金资助项目(2020YW003);成都工业学院引进人才科研启动项目(2021RC003);四川省大学生创新创业项目(S202111116048)。

摘　　要：机车齿轮箱齿轮工作环境恶劣且极易出现齿轮损伤。齿轮箱齿根裂纹损伤检测是保证列车安全运行的有效措施。本文提出了一种基于随机共振以及图谱理论相结合的齿根裂纹故障提取方法。基于随机共振以及图谱理论的故障提取方法具体过程如下:首先,运用复Morlet小波梳状滤波器对原始信号进行解调处理;然后,运用图谱理论方法对仿真信号进行处理提取信号中含有的冲击信号成分;最后利用随机共振方法对提取的冲击信号进行处理,达到消除信号中噪声干扰增强信号中冲击成分的目的。运用文中所提出方法对仿真数据进行处理,结果证明了所提出方法的有效性。Locomotive gearbox is always operating in very harsh environment and the gear may be damaged easily.Gear root crack damage detection is an effective way to ensure the safe operation of the train. In this paper, a fault extraction method based on stochastic resonance and graph spectrum theory is proposed. Firstly, the complex Morlet wavelet comb filter is used to demodulate the original signal. Then, the spectrum theory is used to process the simulation signal and extract the impact signal components in the signal. Finally, the stochastic resonance method is used to process the extracted impulse signal to eliminate the noise interference and enhance the impulse component in the signal. The simulation data are processed using the proposed method, and the effectiveness of the proposed method is proved.

关 键 词：故障诊断 机车齿轮箱 齿根裂纹 随机共振 图谱理论 

分 类 号：U260.143[机械工程—车辆工程] TH113.1[交通运输工程—载运工具运用工程]