Simultaneous use of Acoustic Emission Signals and Statistical Analysis to Distinguish between Lubrication Modes in Rolling Element Bearings
The lack of lubricant in bearing surfaces could be considered as the main cause of wear and faults in bearing surfaces. To avoid unexpected failures, special emphasis on adequate evaluation of lubrication mode (lubricated/dry) on the bearing surfaces is demanded. To that end, the proper use of relia...
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| Format: | Article |
| Language: | English |
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Islamic Azad University-Isfahan (Khorasgan) Branch
2018-12-01
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| Series: | International Journal of Advanced Design and Manufacturing Technology |
| Subjects: | |
| Online Access: | https://admt.isfahan.iau.ir/article_668321_74487c2798543081f2ac02cb249e8572.pdf |
| _version_ | 1797657307528560640 |
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| author | Seyed Ali Niknam |
| author_facet | Seyed Ali Niknam |
| author_sort | Seyed Ali Niknam |
| collection | DOAJ |
| description | The lack of lubricant in bearing surfaces could be considered as the main cause of wear and faults in bearing surfaces. To avoid unexpected failures, special emphasis on adequate evaluation of lubrication mode (lubricated/dry) on the bearing surfaces is demanded. To that end, the proper use of reliable techniques and tools, including sensory information from acoustic emission (AE) signals is among popular methods when real-time condition monitoring evolves. The current work intends to evaluate the sensitivity of AE parameters to different levels of process parameters on the basis of statistical analysis. In this context, rotational speed and radial load were used as the main experimental parameters. Following that, adequacy of a new AE signal parameter for real-time condition monitoring of rolling element bearing is presented. Experimental and statistical results confirmed the great capability of AE signals to differentiate between two types of bearing modes, in particular, dry and lubricated. Signal processing and statistical analysis conducted in this study exhibited that several time series AE parameters, in particular, Std, Max, Mean, and Variance are sensitive to the variation radial load and rotational speed. It was observed that radial load has insignificant effects on computed values of AE parameters from both bearing modes. The statistical analysis revealed that rotational speed (A) has a significant effect on all computed AE parameters from the dry bearing. |
| first_indexed | 2024-03-11T17:42:34Z |
| format | Article |
| id | doaj.art-1d10133c99d04c00b01d52bf5bdcfe64 |
| institution | Directory Open Access Journal |
| issn | 2252-0406 2383-4447 |
| language | English |
| last_indexed | 2024-03-11T17:42:34Z |
| publishDate | 2018-12-01 |
| publisher | Islamic Azad University-Isfahan (Khorasgan) Branch |
| record_format | Article |
| series | International Journal of Advanced Design and Manufacturing Technology |
| spelling | doaj.art-1d10133c99d04c00b01d52bf5bdcfe642023-10-18T09:05:28ZengIslamic Azad University-Isfahan (Khorasgan) BranchInternational Journal of Advanced Design and Manufacturing Technology2252-04062383-44472018-12-011148190668321Simultaneous use of Acoustic Emission Signals and Statistical Analysis to Distinguish between Lubrication Modes in Rolling Element BearingsSeyed Ali Niknam0School of Mechanical Engineering, Iran University of Science and Technology, IranThe lack of lubricant in bearing surfaces could be considered as the main cause of wear and faults in bearing surfaces. To avoid unexpected failures, special emphasis on adequate evaluation of lubrication mode (lubricated/dry) on the bearing surfaces is demanded. To that end, the proper use of reliable techniques and tools, including sensory information from acoustic emission (AE) signals is among popular methods when real-time condition monitoring evolves. The current work intends to evaluate the sensitivity of AE parameters to different levels of process parameters on the basis of statistical analysis. In this context, rotational speed and radial load were used as the main experimental parameters. Following that, adequacy of a new AE signal parameter for real-time condition monitoring of rolling element bearing is presented. Experimental and statistical results confirmed the great capability of AE signals to differentiate between two types of bearing modes, in particular, dry and lubricated. Signal processing and statistical analysis conducted in this study exhibited that several time series AE parameters, in particular, Std, Max, Mean, and Variance are sensitive to the variation radial load and rotational speed. It was observed that radial load has insignificant effects on computed values of AE parameters from both bearing modes. The statistical analysis revealed that rotational speed (A) has a significant effect on all computed AE parameters from the dry bearing.https://admt.isfahan.iau.ir/article_668321_74487c2798543081f2ac02cb249e8572.pdfacoustic emissionbearingcondition monitoringlubrication |
| spellingShingle | Seyed Ali Niknam Simultaneous use of Acoustic Emission Signals and Statistical Analysis to Distinguish between Lubrication Modes in Rolling Element Bearings International Journal of Advanced Design and Manufacturing Technology acoustic emission bearing condition monitoring lubrication |
| title | Simultaneous use of Acoustic Emission Signals and Statistical Analysis to Distinguish between Lubrication Modes in Rolling Element Bearings |
| title_full | Simultaneous use of Acoustic Emission Signals and Statistical Analysis to Distinguish between Lubrication Modes in Rolling Element Bearings |
| title_fullStr | Simultaneous use of Acoustic Emission Signals and Statistical Analysis to Distinguish between Lubrication Modes in Rolling Element Bearings |
| title_full_unstemmed | Simultaneous use of Acoustic Emission Signals and Statistical Analysis to Distinguish between Lubrication Modes in Rolling Element Bearings |
| title_short | Simultaneous use of Acoustic Emission Signals and Statistical Analysis to Distinguish between Lubrication Modes in Rolling Element Bearings |
| title_sort | simultaneous use of acoustic emission signals and statistical analysis to distinguish between lubrication modes in rolling element bearings |
| topic | acoustic emission bearing condition monitoring lubrication |
| url | https://admt.isfahan.iau.ir/article_668321_74487c2798543081f2ac02cb249e8572.pdf |
| work_keys_str_mv | AT seyedaliniknam simultaneoususeofacousticemissionsignalsandstatisticalanalysistodistinguishbetweenlubricationmodesinrollingelementbearings |