自相关结合灰色关联度的轴承早期故障诊断方法

方能炜; 刘兰徽; 邢镔; 胡小林; 董绍江; 裴雪武

doi:10.13433/j.cnki.1003-8728.20220165

自相关结合灰色关联度的轴承早期故障诊断方法

doi: 10.13433/j.cnki.1003-8728.20220165

1.
重庆工业大数据创新中心有限公司，重庆　400707
2.
重庆交通大学机电与车辆工程学院，重庆　400074）0

基金项目: 重庆市北碚区科学技术局技术创新与应用示范项目(2020−5)

详细信息

作者简介:
方能炜（1980−），硕士，研究方向为数据采集和计算机软硬件开发，342451687@qq.com

通讯作者:
胡小林，高级工程师，huxl0918@163.com

中图分类号: TP206
计量
- 文章访问数: 732
- HTML全文浏览量: 24
- PDF下载量: 27
- 被引次数: 0
出版历程
- 收稿日期: 2021-09-27
- 刊出日期: 2023-12-25

Early Fault Diagnosis of Bearing Coupling Autocorrelation and Grey Relational Degree

1.
Chongqing Industrial Big Data Innovation Center Co., Ltd., Chongqing 400707, China
2.
School of Mechantronics and Vehicle Engineering, Chongqing Jiaotong University, Chongqing 400074, China

摘要

摘要: 针对滚动轴承性能衰退指标敏感度低且退化起始点难以检测的问题，本文提出了自相关函数结合灰色关联度(Autocorrelation function and gray relational degree，AF-GRD)的轴承早期故障诊断方法。首先，基于希尔伯特变换和自相关函数处理轴承全寿命数据样本组获得自相关系列函数。然后，提取轴承运行初期的第一组数据作为参考样本，计算其余样本和参考样本的灰色关联度并构建轴承性能衰退指标。最后，根据该指标的变化趋势和健康阈值确定轴承早期故障发生的时间段，截取该时段的数据样本进行希尔伯特包络谱分析实现轴承早期故障诊断。利用实验室数据库完成对轴承早期故障诊断，结果表明：所提方法敏感度高而且可以完成轴承早期退化检测。
- 轴承 /
- 自相关函数 /
- 灰色关联度 /
- 早期故障诊断
Abstract: Aiming at the low sensitivity of rolling bearing performance degradation index and difficulty in determining the starting point of degradation, an early fault diagnosis method of bearing coupling autocorrelation function and gray relational degree (AF-GRD) is proposed. Firstly, the autocorrelation series function is obtained based on the Hilbert transform and the AF by processing the life data sample group of bearing. Then, the first set of data in the early stage of bearing operation was extracted as a reference sample, the GRD between the remaining samples and the reference sample was calculated and the bearing performance degradation index was constructed. Finally, the time period of the early fault of bearing is determined according to the change in index and health threshold, the data sample of this period are intercepted for Hilbert envelope spectrum analysis to realize early fault diagnosis. Using the laboratory database to complete early fault diagnosis of the bearing, the results show that AF-GRD has high sensitivity and can detect the early degradation of bearings.
- bearing /
- autocorrelation function /
- grey relational degree /
- early fault diagnosis

HTML全文

图 1 基于 AF-GRD 的轴承早期故障诊断方法流程图

Figure 1. Flow chart of a bearing's early faut diagnosis method based on AF-GRD

下载: 全尺寸图片幻灯片

图 2 轴承全寿命测试台

Figure 2. Bearing's life cycle test bench

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图 3 基于 AF-GRD 的轴承 2-1 性能退化曲线图

Figure 3. Performance degradation curve of bearing 2-1 based on AF-GRD

下载: 全尺寸图片幻灯片

图 4 基于AF-GRD的轴承2-1性能退化曲线局部分析图

Figure 4. Local analysis of bearing 2-1 performance degradation curve based on AF-GRD

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图 5 4类状态样本的包络谱图

Figure 5. Envelope spectra of four types of state samples

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图 6 基于 GRD 的轴承 2-1 性能退化曲线图

Figure 6. Performance degradation curve of bearing 2-1 based on GRD

下载: 全尺寸图片幻灯片

表 1 7种方法的早期故障诊断结果对比

Table 1. Comparison of early fault diagnosis results of seven methods

指标方法	轴承早期故障起始点	误报警情况
AF-GRD	第533组状态样本	无
DSHDD和模糊评价	第533组状态样本	多个误报警
t-SNE和核马氏距离	第535组状态样本	无
FEEMD-EHNR	第535组状态样本	无
AVMD-EHNR	第536组状态样本	无
EHNR	第544组状态样本	无
Kurtosis	第646组状态样本	1个误报警

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