基于MSST的旋转机械故障诊断研究

黄传金1,2,陈宏3,雷文平3,李凌均3,孟雅俊1,赵静1

振动与冲击 ›› 2019, Vol. 38 ›› Issue (8) : 1-8.

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振动与冲击 ›› 2019, Vol. 38 ›› Issue (8) : 1-8.
论文

基于MSST的旋转机械故障诊断研究

  • 黄传金1,2,陈宏3,雷文平3,李凌均3,孟雅俊1,赵静1
作者信息 +

Research on fault diagnosis of rotating machinery based on MSST

  • HUANG Chuanjin1,2,CHEN Hong3,LEI Wenping3,LI Lingjun3,MENG Yajun1,ZHAO Jing1
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文章历史 +

摘要

在介绍多变量信号调制模型的基础上,提出了一种基于双变量同步挤压小波变换的旋转机械故障诊断新方法。该方法首先通过正交采样技术获取互相垂直通道的振动信号并将其组成一个双变量信号;然后用同步压缩小波变换分别获取每个变量的同步压缩值,并运用自适应频率拼接技术划分双变量带宽的时频域,以识别双变量中的单分量信号,确定在这些频带内存在的瞬时振幅和频率;最后,根据多通道联合瞬时频率概念融合双变量信号中每个通道的瞬时频率和瞬时幅值,得到双变量信号的时频表征。转子双稳态信号、转子松动不对中碰摩复合故障和齿轮减速箱振动信号分析结果证明了所提方法的可行性和有效性。

Abstract

A new time-frequency analysis method for fault diagnosis of rotating machinery was proposed based on multivariable synchrosqueezing.Firstly, the method uses the vibration signals of vertical channels through a quadrature sampling and forms a bivariate signal.Then the simultaneous squeezed wavelet transform is used to obtain the synchronous extrusion value of each variable, and the adaptive frequency splicing technique is used to divide the time-frequency domain of the bivariate bandwidth to identify the single-component signal and determine the instantaneous amplitude and frequency presenting in these frequency bandwidth.Finally, according to the multi-channel joint instantaneous frequency concept, the instantaneous frequency and instantaneous amplitude of each channel in the bivariate signal are combined to obtain the time-frequency representation of the bivariate signal.The analysis results of rotor bistable signals, rotor misalignment composite faults and gearbox vibration signals demonstrate the feasibility and effectiveness of the proposed method.

关键词

多变量信号调制 / 同步压缩小波变换 / 时频分析 / 故障诊断

Key words

Multivariate signal modulation model / Squeezed wavelet transform / Time-frequency analysis / Rotary machinery fault diagnosis

引用本文

导出引用
黄传金1,2,陈宏3,雷文平3,李凌均3,孟雅俊1,赵静1. 基于MSST的旋转机械故障诊断研究[J]. 振动与冲击, 2019, 38(8): 1-8
HUANG Chuanjin1,2,CHEN Hong3,LEI Wenping3,LI Lingjun3,MENG Yajun1,ZHAO Jing1. Research on fault diagnosis of rotating machinery based on MSST[J]. Journal of Vibration and Shock, 2019, 38(8): 1-8

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