Bearings Health Monitoring Based on Frequency-Domain Vibration Signals Analysis
Rotating machine health monitoring is critical for system safety, cost savings, and increased reliability. The need for a simple and accurate fault diagnosis method has led to the development of various monitoring techniques. They incorporate vibration, motor’s current signature, and acoustic emissi...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Unviversity of Technology- Iraq
2023-01-01
|
| Series: | Engineering and Technology Journal |
| Subjects: | |
| Online Access: | https://etj.uotechnology.edu.iq/article_175635_295f0e5dafdf2f558ebd6b8dafa6cc25.pdf |
| _version_ | 1797337657870647296 |
|---|---|
| author | Saja Jawad Alaa Jaber |
| author_facet | Saja Jawad Alaa Jaber |
| author_sort | Saja Jawad |
| collection | DOAJ |
| description | Rotating machine health monitoring is critical for system safety, cost savings, and increased reliability. The need for a simple and accurate fault diagnosis method has led to the development of various monitoring techniques. They incorporate vibration, motor’s current signature, and acoustic emission signals analysis in condition monitoring. So, based on using vibration signal analysis, a test rig was built for bearing fault identification. The test rig replicates and investigates various bearing problems, such as those found in the inner and outer races. An accelerometer, type ADXL335, was interfaced to a data acquisition device (DAQ USB-6215) for collecting vibration signals under various operating circumstances. In addition, a load cell was embedded with the test rig, interfaced with a digital panel meter, and used for recording the applied load on the bearings. The time-domain signal analysis technique was used after acquiring vibration signals at various bearing health states. Then, the time-domain signal was converted to the frequency domain using the fast Fourier transform, and the result was analyzed to investigate the generated fault frequencies. Finally, the obtained frequencies were compared with the theoretical values extracted from the theoretical equations, and the method proved its effectiveness in detecting the fault generated. |
| first_indexed | 2024-03-08T09:16:47Z |
| format | Article |
| id | doaj.art-1049fd4d30724b3e964c621b151900b9 |
| institution | Directory Open Access Journal |
| issn | 1681-6900 2412-0758 |
| language | English |
| last_indexed | 2024-03-08T09:16:47Z |
| publishDate | 2023-01-01 |
| publisher | Unviversity of Technology- Iraq |
| record_format | Article |
| series | Engineering and Technology Journal |
| spelling | doaj.art-1049fd4d30724b3e964c621b151900b92024-01-31T14:15:47ZengUnviversity of Technology- IraqEngineering and Technology Journal1681-69002412-07582023-01-01411869510.30684/etj.2022.131581.1043175635Bearings Health Monitoring Based on Frequency-Domain Vibration Signals AnalysisSaja Jawad0Alaa Jaber1mechanical DepartmentUniversity of Technology-IraqRotating machine health monitoring is critical for system safety, cost savings, and increased reliability. The need for a simple and accurate fault diagnosis method has led to the development of various monitoring techniques. They incorporate vibration, motor’s current signature, and acoustic emission signals analysis in condition monitoring. So, based on using vibration signal analysis, a test rig was built for bearing fault identification. The test rig replicates and investigates various bearing problems, such as those found in the inner and outer races. An accelerometer, type ADXL335, was interfaced to a data acquisition device (DAQ USB-6215) for collecting vibration signals under various operating circumstances. In addition, a load cell was embedded with the test rig, interfaced with a digital panel meter, and used for recording the applied load on the bearings. The time-domain signal analysis technique was used after acquiring vibration signals at various bearing health states. Then, the time-domain signal was converted to the frequency domain using the fast Fourier transform, and the result was analyzed to investigate the generated fault frequencies. Finally, the obtained frequencies were compared with the theoretical values extracted from the theoretical equations, and the method proved its effectiveness in detecting the fault generated.https://etj.uotechnology.edu.iq/article_175635_295f0e5dafdf2f558ebd6b8dafa6cc25.pdfvibration signal analysisbearing fault detectiontime-domain signal analysisfrequency-domain signal analysisfault frequencies |
| spellingShingle | Saja Jawad Alaa Jaber Bearings Health Monitoring Based on Frequency-Domain Vibration Signals Analysis Engineering and Technology Journal vibration signal analysis bearing fault detection time-domain signal analysis frequency-domain signal analysis fault frequencies |
| title | Bearings Health Monitoring Based on Frequency-Domain Vibration Signals Analysis |
| title_full | Bearings Health Monitoring Based on Frequency-Domain Vibration Signals Analysis |
| title_fullStr | Bearings Health Monitoring Based on Frequency-Domain Vibration Signals Analysis |
| title_full_unstemmed | Bearings Health Monitoring Based on Frequency-Domain Vibration Signals Analysis |
| title_short | Bearings Health Monitoring Based on Frequency-Domain Vibration Signals Analysis |
| title_sort | bearings health monitoring based on frequency domain vibration signals analysis |
| topic | vibration signal analysis bearing fault detection time-domain signal analysis frequency-domain signal analysis fault frequencies |
| url | https://etj.uotechnology.edu.iq/article_175635_295f0e5dafdf2f558ebd6b8dafa6cc25.pdf |
| work_keys_str_mv | AT sajajawad bearingshealthmonitoringbasedonfrequencydomainvibrationsignalsanalysis AT alaajaber bearingshealthmonitoringbasedonfrequencydomainvibrationsignalsanalysis |