Bearing Fault Diagnosis under Time-Varying Speed and Load Conditions via Observer-Based Load Torque Analysis
Bearing fault is the most common failure in rotating machines, and bearing fault diagnosis (BFD) has been investigated using vibration, current, or acoustic signals. However, there are still challenges in some existing approaches. This study proposes a novel BFD method based on natural observer. Bas...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/10/3532 |
| _version_ | 1797500233111830528 |
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| author | Ming Ye Jian Zhang Jiaqiang Yang |
| author_facet | Ming Ye Jian Zhang Jiaqiang Yang |
| author_sort | Ming Ye |
| collection | DOAJ |
| description | Bearing fault is the most common failure in rotating machines, and bearing fault diagnosis (BFD) has been investigated using vibration, current, or acoustic signals. However, there are still challenges in some existing approaches. This study proposes a novel BFD method based on natural observer. Based on the analysis of the effects on the load torque signal caused by bearing faults in the permanent magnetic synchronous machine (PMSM), a modified natural observer was designed to reconstruct the load torque signal from electrical signals, acquiring a novel indicator without the additional sensor installed. Angular resampling was implemented to convert the non-stationary load torque signal into a stationary one to reduce the computational complexity. For full-auto diagnosis without human involvement, a threshold determination algorithm was also modified. Experimental validations were carried out under speed-varying and torque-varying conditions and were compared with phase current and q-axis current signals. The average signal-to-noise ratio (SNR) of the estimated load torque is about 8.65 times compared with the SNR of the traditional q-axis current. The effectiveness of the proposed method prior to the traditional PMSM bearing fault indicators is demonstrated by the order spectrum results. |
| first_indexed | 2024-03-10T03:58:58Z |
| format | Article |
| id | doaj.art-603edc10ea11411ebe96db834250a1a0 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T03:58:58Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-603edc10ea11411ebe96db834250a1a02023-11-23T10:49:26ZengMDPI AGEnergies1996-10732022-05-011510353210.3390/en15103532Bearing Fault Diagnosis under Time-Varying Speed and Load Conditions via Observer-Based Load Torque AnalysisMing Ye0Jian Zhang1Jiaqiang Yang2College of Electrical Engineering, Zhejiang University, Hangzhou 310027, ChinaCollege of Electrical Engineering, Zhejiang University, Hangzhou 310027, ChinaCollege of Electrical Engineering, Zhejiang University, Hangzhou 310027, ChinaBearing fault is the most common failure in rotating machines, and bearing fault diagnosis (BFD) has been investigated using vibration, current, or acoustic signals. However, there are still challenges in some existing approaches. This study proposes a novel BFD method based on natural observer. Based on the analysis of the effects on the load torque signal caused by bearing faults in the permanent magnetic synchronous machine (PMSM), a modified natural observer was designed to reconstruct the load torque signal from electrical signals, acquiring a novel indicator without the additional sensor installed. Angular resampling was implemented to convert the non-stationary load torque signal into a stationary one to reduce the computational complexity. For full-auto diagnosis without human involvement, a threshold determination algorithm was also modified. Experimental validations were carried out under speed-varying and torque-varying conditions and were compared with phase current and q-axis current signals. The average signal-to-noise ratio (SNR) of the estimated load torque is about 8.65 times compared with the SNR of the traditional q-axis current. The effectiveness of the proposed method prior to the traditional PMSM bearing fault indicators is demonstrated by the order spectrum results.https://www.mdpi.com/1996-1073/15/10/3532bearing fault diagnosis (BFD)natural observerpermanent magnet synchronous machine (PMSM)angular resample (AR) |
| spellingShingle | Ming Ye Jian Zhang Jiaqiang Yang Bearing Fault Diagnosis under Time-Varying Speed and Load Conditions via Observer-Based Load Torque Analysis Energies bearing fault diagnosis (BFD) natural observer permanent magnet synchronous machine (PMSM) angular resample (AR) |
| title | Bearing Fault Diagnosis under Time-Varying Speed and Load Conditions via Observer-Based Load Torque Analysis |
| title_full | Bearing Fault Diagnosis under Time-Varying Speed and Load Conditions via Observer-Based Load Torque Analysis |
| title_fullStr | Bearing Fault Diagnosis under Time-Varying Speed and Load Conditions via Observer-Based Load Torque Analysis |
| title_full_unstemmed | Bearing Fault Diagnosis under Time-Varying Speed and Load Conditions via Observer-Based Load Torque Analysis |
| title_short | Bearing Fault Diagnosis under Time-Varying Speed and Load Conditions via Observer-Based Load Torque Analysis |
| title_sort | bearing fault diagnosis under time varying speed and load conditions via observer based load torque analysis |
| topic | bearing fault diagnosis (BFD) natural observer permanent magnet synchronous machine (PMSM) angular resample (AR) |
| url | https://www.mdpi.com/1996-1073/15/10/3532 |
| work_keys_str_mv | AT mingye bearingfaultdiagnosisundertimevaryingspeedandloadconditionsviaobserverbasedloadtorqueanalysis AT jianzhang bearingfaultdiagnosisundertimevaryingspeedandloadconditionsviaobserverbasedloadtorqueanalysis AT jiaqiangyang bearingfaultdiagnosisundertimevaryingspeedandloadconditionsviaobserverbasedloadtorqueanalysis |