State-of-the-Art Detection and Diagnosis Methods for Rolling Bearing Defects: A Comprehensive Review
Rolling bearings are essential transmission and support components in aircraft engines, playing a critical role in ensuring their safe and stable operation. Rolling bearing faults have a significant impact and should not be ignored. The effective diagnosis of bearing faults has always been a critica...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/2/1001 |
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| author | Bojun Sun Zixin Sheng Peng Song Huilin Sun Fei Wang Xiaogang Sun Junyan Liu |
| author_facet | Bojun Sun Zixin Sheng Peng Song Huilin Sun Fei Wang Xiaogang Sun Junyan Liu |
| author_sort | Bojun Sun |
| collection | DOAJ |
| description | Rolling bearings are essential transmission and support components in aircraft engines, playing a critical role in ensuring their safe and stable operation. Rolling bearing faults have a significant impact and should not be ignored. The effective diagnosis of bearing faults has always been a critical requirement for ensuring reliable operation. With the increasing demands of modern manufacturing to reduce costs and improve quality, the development of advanced bearing fault detection methods has become indispensable. This paper presents the brief review of recent trends in research on bearing failure modes, bearing fault detection and diagnosis methods, and development trends and prospects. This article provides a comprehensive review of the existing fault diagnosis methods for rolling bearings in four aspects: the integration of advanced sensor technology and advanced data processing technology, multimodal fusion, intelligent detection, and real-time monitoring. It discusses methods based on vibration analysis, acoustic methods, current-based methods, electromagnetic methods, infrared methods, radiographic methods, visual methods, and intelligent detection methods. This study reveals that the application of intelligent detection technology, multimodal fusion detection technology, and real-time online monitoring technology has achieved favorable results. In the future, bearing fault detection will develop in a more intelligent, integrated, and real-time direction. |
| format | Article |
| id | doaj-art-556475af886244fbadfc492ea640abd5 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-556475af886244fbadfc492ea640abd52025-01-24T13:21:38ZengMDPI AGApplied Sciences2076-34172025-01-01152100110.3390/app15021001State-of-the-Art Detection and Diagnosis Methods for Rolling Bearing Defects: A Comprehensive ReviewBojun Sun0Zixin Sheng1Peng Song2Huilin Sun3Fei Wang4Xiaogang Sun5Junyan Liu6Aero Engine Corporation of China Harbin Bearing Company, Ltd., Harbin 150500, ChinaSchool of Instrument Science and Engineering, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, ChinaAero Engine Corporation of China Harbin Bearing Company, Ltd., Harbin 150500, ChinaSchool of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Instrument Science and Engineering, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, ChinaRolling bearings are essential transmission and support components in aircraft engines, playing a critical role in ensuring their safe and stable operation. Rolling bearing faults have a significant impact and should not be ignored. The effective diagnosis of bearing faults has always been a critical requirement for ensuring reliable operation. With the increasing demands of modern manufacturing to reduce costs and improve quality, the development of advanced bearing fault detection methods has become indispensable. This paper presents the brief review of recent trends in research on bearing failure modes, bearing fault detection and diagnosis methods, and development trends and prospects. This article provides a comprehensive review of the existing fault diagnosis methods for rolling bearings in four aspects: the integration of advanced sensor technology and advanced data processing technology, multimodal fusion, intelligent detection, and real-time monitoring. It discusses methods based on vibration analysis, acoustic methods, current-based methods, electromagnetic methods, infrared methods, radiographic methods, visual methods, and intelligent detection methods. This study reveals that the application of intelligent detection technology, multimodal fusion detection technology, and real-time online monitoring technology has achieved favorable results. In the future, bearing fault detection will develop in a more intelligent, integrated, and real-time direction.https://www.mdpi.com/2076-3417/15/2/1001bearing failure modesbearing defectdetection and diagnosis methodsmultimodal measurement |
| spellingShingle | Bojun Sun Zixin Sheng Peng Song Huilin Sun Fei Wang Xiaogang Sun Junyan Liu State-of-the-Art Detection and Diagnosis Methods for Rolling Bearing Defects: A Comprehensive Review Applied Sciences bearing failure modes bearing defect detection and diagnosis methods multimodal measurement |
| title | State-of-the-Art Detection and Diagnosis Methods for Rolling Bearing Defects: A Comprehensive Review |
| title_full | State-of-the-Art Detection and Diagnosis Methods for Rolling Bearing Defects: A Comprehensive Review |
| title_fullStr | State-of-the-Art Detection and Diagnosis Methods for Rolling Bearing Defects: A Comprehensive Review |
| title_full_unstemmed | State-of-the-Art Detection and Diagnosis Methods for Rolling Bearing Defects: A Comprehensive Review |
| title_short | State-of-the-Art Detection and Diagnosis Methods for Rolling Bearing Defects: A Comprehensive Review |
| title_sort | state of the art detection and diagnosis methods for rolling bearing defects a comprehensive review |
| topic | bearing failure modes bearing defect detection and diagnosis methods multimodal measurement |
| url | https://www.mdpi.com/2076-3417/15/2/1001 |
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