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基于声发射多参数融合的滚动轴承典型故障损伤程度识别方法

栾孝驰 沙云东 李壮 郭小鹏 赵宇 柳贡民

栾孝驰, 沙云东, 李壮, 等. 基于声发射多参数融合的滚动轴承典型故障损伤程度识别方法[J]. 航空动力学报, 2024, 39(8):20220512 doi: 10.13224/j.cnki.jasp.20220512
引用本文: 栾孝驰, 沙云东, 李壮, 等. 基于声发射多参数融合的滚动轴承典型故障损伤程度识别方法[J]. 航空动力学报, 2024, 39(8):20220512 doi: 10.13224/j.cnki.jasp.20220512
LUAN Xiaochi, SHA Yundong, LI Zhuang, et al. Damage extent identification method of typical rolling bearing faults based on acoustic emission multi-parameter fusion[J]. Journal of Aerospace Power, 2024, 39(8):20220512 doi: 10.13224/j.cnki.jasp.20220512
Citation: LUAN Xiaochi, SHA Yundong, LI Zhuang, et al. Damage extent identification method of typical rolling bearing faults based on acoustic emission multi-parameter fusion[J]. Journal of Aerospace Power, 2024, 39(8):20220512 doi: 10.13224/j.cnki.jasp.20220512

基于声发射多参数融合的滚动轴承典型故障损伤程度识别方法

doi: 10.13224/j.cnki.jasp.20220512
基金项目: 辽宁省教育厅系列项目(JYT2020010); 中国航发产学研合作项目(HFZL2018CXY017)
详细信息
    作者简介:

    栾孝驰(1987-),男,副教授、硕士生导师,博士,主要从事航空发动机传动系统状态监测与轴承故障诊断技术研究。E-mail:luanxiaochi27@163.com

  • 中图分类号: V235.13

Damage extent identification method of typical rolling bearing faults based on acoustic emission multi-parameter fusion

  • 摘要:

    针对滚动轴承典型故障损伤程度难识别的问题,以声发射参数分析和波形流分析方法为基础,结合时间到达特征指数(TAFI)、计数、撞击数、能量以及引入故障特征频率功率峰值与其相邻倍频间频带内平均功率比值的无量纲参数故障因子,提出了一种基于声发射多参数融合的滚动轴承典型故障损伤程度识别方法。为验证该方法对滚动轴承典型故障损伤程度的识别效果,搭建了滚动轴承典型故障模拟试验台,开展试验并采集了线切割严重损伤和点蚀微弱损伤两种缺陷的滚动轴承声发射信号,对相同转速工况下测得的典型故障轴承与健康轴承的声发射信号应用本文提出的方法进行识别。结果表明:声发射特征参数TAFI可以初步判定轴承是否存在故障,计数和撞击数可有效识别滚动轴承的故障类型;特征参数能量可有效识别外圈故障和滚动体故障滚动轴承的不同损伤程度,引入故障因子参量来表征不同缺陷滚动轴承的损伤程度,通过线切割和点蚀缺陷1~5倍频故障因子数值上的差异,有效识别了典型故障滚动轴承的不同损伤程度,弥补了特征参数能量对内圈故障损伤程度识别的不足。该方法可有效识别滚动轴承典型故障的不同损伤程度。

     

  • 图 1  声发射信号特征参数定义图

    Figure 1.  Characteristic parameter definition of acoustic emission signal

    图 2  滚动轴承几何参数图

    Figure 2.  Geometric parameters of rolling bearings

    图 3  故障因子的定义

    Figure 3.  Definition of fault factor

    图 4  滚动轴承典型故障损伤程度识别流程

    Figure 4.  Identification process of damage extent of typical rolling bearing faults

    图 5  滚动轴承典型故障模拟试验台

    Figure 5.  Test bench for fault simulation of rolling bearing

    图 6  AE传感器布置图

    Figure 6.  AE sensor layout

    图 7  线切割缺陷的典型故障轴承

    Figure 7.  Wire cutting defect of typical faulty bearings

    图 8  点蚀缺陷的典型故障轴承

    Figure 8.  Pitting defect of typical faulty bearings

    图 9  断铅试验信号

    Figure 9.  Signal of lead-break test

    图 10  健康轴承TAFI对时间经历图

    Figure 10.  TAFI-time chart for healthy bearings

    图 11  典型故障轴承TAFI对时间经历图

    Figure 11.  TAFI-time chart for typical faulty bearings

    图 12  典型故障及健康轴承计数对时间经历图

    Figure 12.  Counting-time history graph of different faulty bearings

    图 13  典型故障及健康轴承撞击数对幅值分布图

    Figure 13.  Hit number-amplitude distribution map of different faulty bearings

    图 14  典型故障及健康轴承能量对时间经历图

    Figure 14.  Energy-time history graph of different faulty bearings

    图 15  不同损伤状态典型故障轴承平均计数

    Figure 15.  Average count of typical fault bearings under different damage states

    图 16  不同损伤状态典型故障轴承平均能量

    Figure 16.  Average energy of typical fault bearings under different damage states

    图 17  不同损伤状态典型故障轴承撞击总数

    Figure 17.  Total number of impacts of typical fault bearings under different damage states

    图 18  线切割缺陷外圈故障包络谱

    Figure 18.  Outer ring fault envelope spectrum of wire-cut defects

    图 19  点蚀缺陷外圈故障包络谱

    Figure 19.  Outer ring fault envelope spectrum of pitting defects

    图 20  线切割缺陷滚动体故障包络谱

    Figure 20.  Rolling fault envelope spectrum of wire-cut defects

    图 21  点蚀缺陷滚动体故障包络谱

    Figure 21.  Rolling fault envelope spectrum of pitting defects

    图 22  线切割缺陷内圈故障包络谱

    Figure 22.  Inner ring fault envelope spectrum of wire-cut defects

    图 23  点蚀缺陷内圈故障包络谱

    Figure 23.  Inner ring fault envelope spectrum of pitting defects

    图 24  轴承故障不同损伤状态的故障因子

    Figure 24.  Fault factors of bearing fault in different damage states

    表  1  试验轴承的几何参数

    Table  1.   Geometric parameters of the test bearing

    参数数值及说明
    轴承型号NJ204EM
    节径/mm33.5
    接触角/(°)0
    滚动体个数12
    滚动体直径/mm6
    下载: 导出CSV

    表  2  不同损伤状态典型故障轴承的声发射参数统计

    Table  2.   Acoustic emission parameter statistics of typical fault bearings under different damage states

    损伤
    状态
    故障
    类型
    计数
    平均值
    能量平均值/
    (mV·µs)
    撞击
    总数
    健康 无故障 2.10 0.42 20
    线切割
    缺陷
    内圈 71.30 2.27 234
    滚动体 169.67 466.03 841
    外圈 281.90 825.03 625
    点蚀缺陷 内圈 15.58 0.97 53
    滚动体 51.35 30.94 721
    外圈 186.48 48.29 236
    下载: 导出CSV

    表  3  840 r/min转速下轴承线切割与点蚀损伤故障特征频率理论值

    Table  3.   Theoretical value of fault characteristic frequency of bearing linear cutting and pitting damage at 840 r/min speed

    故障类型 故障特征频率理论值/Hz
    外圈 ${f_{\text{o}}} = 60.91$
    滚动体 ${f_{\text{b}}} = 30.25$
    内圈 ${f_{\text{i}}} = 99.04$
    下载: 导出CSV

    表  4  故障特征频率及倍频对应峰值和附近平均峰值

    Table  4.   Fault characteristic frequency and frequency doubling corresponding peak and nearby average peak 10−3 W

    特征
    频率
    变量值 外圈 滚动体 内圈
    线切割故障 点蚀故障 线切割故障 点蚀故障 线切割故障 点蚀故障
    1倍频 D2 4.22 1.78 59.7 1.65 0.0189 0.176
    D 0.78 0.81 9.0 0.58 0.0070 0.120
    2倍频 D2 3.71 1.24 62.7 1.66 0.0185 0.123
    D 0.78 0.65 10.1 0.49 0.0069 0.079
    3倍频 D2 2.38 1.18 47.3 1.20 0.0148 0.098
    D 0.76 0.57 9.2 0.48 0.0055 0.069
    4倍频 D2 2.78 1.03 43.3 1.23 0.0153 0.089
    D 0.77 0.47 9.1 0.48 0.0056 0.059
    5倍频 D2 2.29 0.72 28.4 0.0128 0.090
    D 0.75 0.38 9.0 0.47 0.0053 0.063
    下载: 导出CSV

    表  5  不同损伤状态典型故障轴承的故障因子

    Table  5.   Fault factors of typical fault bearings under different damage states

    故障类型 损伤状态 $ {\lambda _1} $ $ {\lambda _2} $ $ {\lambda _3} $ $ {\lambda _4} $ $ {\lambda _5} $
    外圈 线切割 5.38 4.75 3.13 3.63 3.05
    点蚀 2.19 1.92 2.08 2.22 1.88
    滚动体 线切割 6.67 6.21 5.16 4.74 3.16
    点蚀 2.84 3.40 2.51 2.55 1.00
    内圈 线切割 2.71 2.69 2.67 2.75 2.41
    点蚀 1.46 1.56 1.43 1.50 1.43
    下载: 导出CSV
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  • 收稿日期:  2022-07-17
  • 网络出版日期:  2023-11-27

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