Lubrication State Recognition Based on Energy Characteristics of Friction Vibration with EEMD and SVM
In order to identify different lubrication states, lubrication experiments were carried out on a Bruker UMT-3 tester. The experimental results show that the frequency band energy characteristics of friction vibration signals are different under different lubrication states. Based on this, a lubricat...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2021/9972119 |
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| author | Hai-jie Yu Hai-jun Wei Jing-ming Li Da‐ping Zhou Li‐dui Wei Hong Liu |
| author_facet | Hai-jie Yu Hai-jun Wei Jing-ming Li Da‐ping Zhou Li‐dui Wei Hong Liu |
| author_sort | Hai-jie Yu |
| collection | DOAJ |
| description | In order to identify different lubrication states, lubrication experiments were carried out on a Bruker UMT-3 tester. The experimental results show that the frequency band energy characteristics of friction vibration signals are different under different lubrication states. Based on this, a lubrication state recognition method with ensemble empirical mode decomposition (EEMD) and support vector machine (SVM) was proposed. The vibration signals were decomposed into a finite number of stationary intrinsic mode functions (IMFs) with the EEMD method. The first six IMF components containing the main friction information were retained to calculate the energy ratio and construct the feature vector. The experimental results show that the mixed lubrication state can be identified by hundred percent, and there is a slight confusion between boundary lubrication and dry friction. The results show that frequency band energy of friction vibration signals is an effective feature to identify different lubrication states, and the proposed method can be used to identify different lubrication states. |
| format | Article |
| id | doaj-art-ddcf86d7c49342b2a8f2ed56830bf35e |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-ddcf86d7c49342b2a8f2ed56830bf35e2025-02-03T01:31:22ZengWileyShock and Vibration1070-96221875-92032021-01-01202110.1155/2021/99721199972119Lubrication State Recognition Based on Energy Characteristics of Friction Vibration with EEMD and SVMHai-jie Yu0Hai-jun Wei1Jing-ming Li2Da‐ping Zhou3Li‐dui Wei4Hong Liu5Merchant Marine College, Shanghai Maritime University, Shanghai 201306, ChinaMerchant Marine College, Shanghai Maritime University, Shanghai 201306, ChinaMerchant Marine College, Shanghai Maritime University, Shanghai 201306, ChinaMerchant Marine College, Shanghai Maritime University, Shanghai 201306, ChinaMerchant Marine College, Shanghai Maritime University, Shanghai 201306, ChinaMerchant Marine College, Shanghai Maritime University, Shanghai 201306, ChinaIn order to identify different lubrication states, lubrication experiments were carried out on a Bruker UMT-3 tester. The experimental results show that the frequency band energy characteristics of friction vibration signals are different under different lubrication states. Based on this, a lubrication state recognition method with ensemble empirical mode decomposition (EEMD) and support vector machine (SVM) was proposed. The vibration signals were decomposed into a finite number of stationary intrinsic mode functions (IMFs) with the EEMD method. The first six IMF components containing the main friction information were retained to calculate the energy ratio and construct the feature vector. The experimental results show that the mixed lubrication state can be identified by hundred percent, and there is a slight confusion between boundary lubrication and dry friction. The results show that frequency band energy of friction vibration signals is an effective feature to identify different lubrication states, and the proposed method can be used to identify different lubrication states.http://dx.doi.org/10.1155/2021/9972119 |
| spellingShingle | Hai-jie Yu Hai-jun Wei Jing-ming Li Da‐ping Zhou Li‐dui Wei Hong Liu Lubrication State Recognition Based on Energy Characteristics of Friction Vibration with EEMD and SVM Shock and Vibration |
| title | Lubrication State Recognition Based on Energy Characteristics of Friction Vibration with EEMD and SVM |
| title_full | Lubrication State Recognition Based on Energy Characteristics of Friction Vibration with EEMD and SVM |
| title_fullStr | Lubrication State Recognition Based on Energy Characteristics of Friction Vibration with EEMD and SVM |
| title_full_unstemmed | Lubrication State Recognition Based on Energy Characteristics of Friction Vibration with EEMD and SVM |
| title_short | Lubrication State Recognition Based on Energy Characteristics of Friction Vibration with EEMD and SVM |
| title_sort | lubrication state recognition based on energy characteristics of friction vibration with eemd and svm |
| url | http://dx.doi.org/10.1155/2021/9972119 |
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