Modeling and Characteristic Analysis of Variable Reluctance Signal Variation of Rolling Bearing Outer Ring Fault
The bearing fault diagnosis based on instantaneous angular speed (IAS) has been developed rapidly. However, it is difficult to identify the weak fault of bearings by using the variable reluctance sensor (VRS) as an encoder because of the lack of the high-frequency information in the modulation frequ...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9762934/ |
| _version_ | 1811256383403720704 |
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| author | Zexing Ni Xiufeng Wang Renqiong Wu Leilei Du |
| author_facet | Zexing Ni Xiufeng Wang Renqiong Wu Leilei Du |
| author_sort | Zexing Ni |
| collection | DOAJ |
| description | The bearing fault diagnosis based on instantaneous angular speed (IAS) has been developed rapidly. However, it is difficult to identify the weak fault of bearings by using the variable reluctance sensor (VRS) as an encoder because of the lack of the high-frequency information in the modulation frequency of IAS. To overcome this shortcoming, a novel method based on the raw signal of the VRS is proposed for bearing diagnosis in this paper. The mechanism of bearing local fault signal response is analyzed by establishing the bearing outer ring fault model and the sensor signal response model, which are explored and verified by the fault simulation experiments. The results show that the gearwheel tooth-pass frequency is modulated by the outer ring fault characteristic frequency, and the defect size can be estimated by the double peaks in the high-frequency band. Moreover, compared with the acceleration signals, the defect size estimations based on the VRS are closer to the actual defect size, which verifies the effectiveness of the proposed method. |
| first_indexed | 2024-04-12T17:39:26Z |
| format | Article |
| id | doaj.art-3ac082d447414d928c28cefaf012fc3a |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-12T17:39:26Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-3ac082d447414d928c28cefaf012fc3a2022-12-22T03:22:50ZengIEEEIEEE Access2169-35362022-01-0110495424955010.1109/ACCESS.2022.31704269762934Modeling and Characteristic Analysis of Variable Reluctance Signal Variation of Rolling Bearing Outer Ring FaultZexing Ni0Xiufeng Wang1https://orcid.org/0000-0002-9611-4306Renqiong Wu2Leilei Du3College of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, ChinaCollege of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, ChinaCollege of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, ChinaCollege of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, ChinaThe bearing fault diagnosis based on instantaneous angular speed (IAS) has been developed rapidly. However, it is difficult to identify the weak fault of bearings by using the variable reluctance sensor (VRS) as an encoder because of the lack of the high-frequency information in the modulation frequency of IAS. To overcome this shortcoming, a novel method based on the raw signal of the VRS is proposed for bearing diagnosis in this paper. The mechanism of bearing local fault signal response is analyzed by establishing the bearing outer ring fault model and the sensor signal response model, which are explored and verified by the fault simulation experiments. The results show that the gearwheel tooth-pass frequency is modulated by the outer ring fault characteristic frequency, and the defect size can be estimated by the double peaks in the high-frequency band. Moreover, compared with the acceleration signals, the defect size estimations based on the VRS are closer to the actual defect size, which verifies the effectiveness of the proposed method.https://ieeexplore.ieee.org/document/9762934/Bearing fault diagnosisdynamic modelingfault characteristicsvariable reluctance sensor |
| spellingShingle | Zexing Ni Xiufeng Wang Renqiong Wu Leilei Du Modeling and Characteristic Analysis of Variable Reluctance Signal Variation of Rolling Bearing Outer Ring Fault IEEE Access Bearing fault diagnosis dynamic modeling fault characteristics variable reluctance sensor |
| title | Modeling and Characteristic Analysis of Variable Reluctance Signal Variation of Rolling Bearing Outer Ring Fault |
| title_full | Modeling and Characteristic Analysis of Variable Reluctance Signal Variation of Rolling Bearing Outer Ring Fault |
| title_fullStr | Modeling and Characteristic Analysis of Variable Reluctance Signal Variation of Rolling Bearing Outer Ring Fault |
| title_full_unstemmed | Modeling and Characteristic Analysis of Variable Reluctance Signal Variation of Rolling Bearing Outer Ring Fault |
| title_short | Modeling and Characteristic Analysis of Variable Reluctance Signal Variation of Rolling Bearing Outer Ring Fault |
| title_sort | modeling and characteristic analysis of variable reluctance signal variation of rolling bearing outer ring fault |
| topic | Bearing fault diagnosis dynamic modeling fault characteristics variable reluctance sensor |
| url | https://ieeexplore.ieee.org/document/9762934/ |
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