Wind Turbine Diagnosis under Variable Speed Conditions Using a Single Sensor Based on the Synchrosqueezing Transform Method
The gearbox is one of the key components in wind turbines. Gearbox fault signals are usually nonstationary and highly contaminated with noise. The presence of amplitude-modulated and frequency-modulated (AM-FM) characteristics compound the difficulty of precise fault diagnosis of wind turbines, ther...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2017-05-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/17/5/1149 |
| _version_ | 1811308080453910528 |
|---|---|
| author | Yanjie Guo Xuefeng Chen Shibin Wang Ruobin Sun Zhibin Zhao |
| author_facet | Yanjie Guo Xuefeng Chen Shibin Wang Ruobin Sun Zhibin Zhao |
| author_sort | Yanjie Guo |
| collection | DOAJ |
| description | The gearbox is one of the key components in wind turbines. Gearbox fault signals are usually nonstationary and highly contaminated with noise. The presence of amplitude-modulated and frequency-modulated (AM-FM) characteristics compound the difficulty of precise fault diagnosis of wind turbines, therefore, it is crucial to develop an effective fault diagnosis method for such equipment. This paper presents an improved diagnosis method for wind turbines via the combination of synchrosqueezing transform and local mean decomposition. Compared to the conventional time-frequency analysis techniques, the improved method which is performed in non-real-time can effectively reduce the noise pollution of the signals and preserve the signal characteristics, and hence is suitable for the analysis of nonstationary signals with high noise. This method is further validated by simulated signals and practical vibration data measured from a 1.5 MW wind turbine. The results confirm that the proposed method can simultaneously control the noise and increase the accuracy of time-frequency representation. |
| first_indexed | 2024-04-13T09:15:42Z |
| format | Article |
| id | doaj.art-a0c9314d0009456bae96069281a59a1a |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T09:15:42Z |
| publishDate | 2017-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-a0c9314d0009456bae96069281a59a1a2022-12-22T02:52:44ZengMDPI AGSensors1424-82202017-05-01175114910.3390/s17051149s17051149Wind Turbine Diagnosis under Variable Speed Conditions Using a Single Sensor Based on the Synchrosqueezing Transform MethodYanjie Guo0Xuefeng Chen1Shibin Wang2Ruobin Sun3Zhibin Zhao4School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, ChinaSchool of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, ChinaSchool of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, ChinaSchool of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, ChinaSchool of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, ChinaThe gearbox is one of the key components in wind turbines. Gearbox fault signals are usually nonstationary and highly contaminated with noise. The presence of amplitude-modulated and frequency-modulated (AM-FM) characteristics compound the difficulty of precise fault diagnosis of wind turbines, therefore, it is crucial to develop an effective fault diagnosis method for such equipment. This paper presents an improved diagnosis method for wind turbines via the combination of synchrosqueezing transform and local mean decomposition. Compared to the conventional time-frequency analysis techniques, the improved method which is performed in non-real-time can effectively reduce the noise pollution of the signals and preserve the signal characteristics, and hence is suitable for the analysis of nonstationary signals with high noise. This method is further validated by simulated signals and practical vibration data measured from a 1.5 MW wind turbine. The results confirm that the proposed method can simultaneously control the noise and increase the accuracy of time-frequency representation.http://www.mdpi.com/1424-8220/17/5/1149wind turbinevibration signal under variable speed conditionsynchrosqueezing transformlocal mean decomposition (LMD) |
| spellingShingle | Yanjie Guo Xuefeng Chen Shibin Wang Ruobin Sun Zhibin Zhao Wind Turbine Diagnosis under Variable Speed Conditions Using a Single Sensor Based on the Synchrosqueezing Transform Method Sensors wind turbine vibration signal under variable speed condition synchrosqueezing transform local mean decomposition (LMD) |
| title | Wind Turbine Diagnosis under Variable Speed Conditions Using a Single Sensor Based on the Synchrosqueezing Transform Method |
| title_full | Wind Turbine Diagnosis under Variable Speed Conditions Using a Single Sensor Based on the Synchrosqueezing Transform Method |
| title_fullStr | Wind Turbine Diagnosis under Variable Speed Conditions Using a Single Sensor Based on the Synchrosqueezing Transform Method |
| title_full_unstemmed | Wind Turbine Diagnosis under Variable Speed Conditions Using a Single Sensor Based on the Synchrosqueezing Transform Method |
| title_short | Wind Turbine Diagnosis under Variable Speed Conditions Using a Single Sensor Based on the Synchrosqueezing Transform Method |
| title_sort | wind turbine diagnosis under variable speed conditions using a single sensor based on the synchrosqueezing transform method |
| topic | wind turbine vibration signal under variable speed condition synchrosqueezing transform local mean decomposition (LMD) |
| url | http://www.mdpi.com/1424-8220/17/5/1149 |
| work_keys_str_mv | AT yanjieguo windturbinediagnosisundervariablespeedconditionsusingasinglesensorbasedonthesynchrosqueezingtransformmethod AT xuefengchen windturbinediagnosisundervariablespeedconditionsusingasinglesensorbasedonthesynchrosqueezingtransformmethod AT shibinwang windturbinediagnosisundervariablespeedconditionsusingasinglesensorbasedonthesynchrosqueezingtransformmethod AT ruobinsun windturbinediagnosisundervariablespeedconditionsusingasinglesensorbasedonthesynchrosqueezingtransformmethod AT zhibinzhao windturbinediagnosisundervariablespeedconditionsusingasinglesensorbasedonthesynchrosqueezingtransformmethod |