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基于递归分析的滚珠轴承故障诊断

Ball Bearing Fault Diagnosis Using Recurrence Analysis.

作者信息

Kecik Krzysztof, Smagala Arkadiusz, Lyubitska Kateryna

机构信息

Department of Applied Mechanics, Mechanical Engineering Faculty, Lublin University of Technology, 20-618 Lublin, Poland.

Polish Bearing Factory, 23-204 Krasnik, Poland.

出版信息

Materials (Basel). 2022 Aug 27;15(17):5940. doi: 10.3390/ma15175940.

DOI:10.3390/ma15175940
PMID:36079322
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9457464/
Abstract

This paper presents the problem of rolling bearing fault diagnosis based on vibration velocity signal. For this purpose, recurrence plots and quantification methods are used for nonlinear signals. First, faults in the form of a small scratch are intentionally introduced by the electron-discharge machining method in the outer and inner rings of a bearing and a rolling ball. Then, the rolling bearings are tested on the special laboratory system, and acceleration signals are measured. Detailed time-dependent recurrence methodology shows some interesting results, and several of the recurrence indicators such as determinism, entropy, laminarity, trapping time and averaged diagonal line can be utilized for fault detection.

摘要

本文提出了基于振动速度信号的滚动轴承故障诊断问题。为此,将递归图和量化方法用于非线性信号。首先,通过电火花加工方法在轴承外圈、内圈以及滚动球上故意引入小划痕形式的故障。然后,在特殊实验室系统上对滚动轴承进行测试,并测量加速度信号。详细的与时间相关的递归方法显示了一些有趣的结果,并且诸如确定性、熵、层流性、捕获时间和平均对角线等几个递归指标可用于故障检测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4732/9457464/e60c53724744/materials-15-05940-g008a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4732/9457464/6d040c28de5d/materials-15-05940-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4732/9457464/2a0eedc4b093/materials-15-05940-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4732/9457464/fdf1ef8ee48d/materials-15-05940-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4732/9457464/58acfa8b074b/materials-15-05940-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4732/9457464/7921fd5b87f7/materials-15-05940-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4732/9457464/20593914de1e/materials-15-05940-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4732/9457464/c17543fdd6d6/materials-15-05940-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4732/9457464/e60c53724744/materials-15-05940-g008a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4732/9457464/6d040c28de5d/materials-15-05940-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4732/9457464/2a0eedc4b093/materials-15-05940-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4732/9457464/fdf1ef8ee48d/materials-15-05940-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4732/9457464/58acfa8b074b/materials-15-05940-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4732/9457464/7921fd5b87f7/materials-15-05940-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4732/9457464/20593914de1e/materials-15-05940-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4732/9457464/c17543fdd6d6/materials-15-05940-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4732/9457464/e60c53724744/materials-15-05940-g008a.jpg

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