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A Review on Vibration-Based Fault Diagnosis Techniques for Wind Turbine Gearboxes Operating Under Nonstationary Conditions
https://orcid.org/http://orcid.org/0000-0003-1422-5473
Numerous studies on vibration-based techniques for fault diagnosis of wind turbine gearboxes operating under nonstationary conditions have been reported. In spite, a review on vibration-based condition monitoring and fault diagnosis techniques for gearboxes of wind turbines operating under nonstationary conditions is unavailable. Thus, the objective of this review is to discuss filtering, decomposition, entropy, and cyclostationary analysis techniques, as well as summarizing the remaining issues. This review will discuss various vibration-based diagnostic approaches developed for wind turbine gearboxes under nonstationary conditions, including both simulation and experimental approaches. Studies on dynamic models of gear systems and advanced signal-processing techniques developed for nonstationary conditions are reviewed. Additionally, the importance of multi-sensor and cointegration based approaches is discussed, and intelligent classification methods that have been used to distinguish healthy and faulty gear systems are also reviewed. Finally, the remaining research challenges are outlined.
A Review on Vibration-Based Fault Diagnosis Techniques for Wind Turbine Gearboxes Operating Under Nonstationary Conditions
https://orcid.org/http://orcid.org/0000-0003-1422-5473
Numerous studies on vibration-based techniques for fault diagnosis of wind turbine gearboxes operating under nonstationary conditions have been reported. In spite, a review on vibration-based condition monitoring and fault diagnosis techniques for gearboxes of wind turbines operating under nonstationary conditions is unavailable. Thus, the objective of this review is to discuss filtering, decomposition, entropy, and cyclostationary analysis techniques, as well as summarizing the remaining issues. This review will discuss various vibration-based diagnostic approaches developed for wind turbine gearboxes under nonstationary conditions, including both simulation and experimental approaches. Studies on dynamic models of gear systems and advanced signal-processing techniques developed for nonstationary conditions are reviewed. Additionally, the importance of multi-sensor and cointegration based approaches is discussed, and intelligent classification methods that have been used to distinguish healthy and faulty gear systems are also reviewed. Finally, the remaining research challenges are outlined.
A Review on Vibration-Based Fault Diagnosis Techniques for Wind Turbine Gearboxes Operating Under Nonstationary Conditions
https://orcid.org/http://orcid.org/0000-0003-1422-5473
Numerous studies on vibration-based techniques for fault diagnosis of wind turbine gearboxes operating under nonstationary conditions have been reported. In spite, a review on vibration-based condition monitoring and fault diagnosis techniques for gearboxes of wind turbines operating under nonstationary conditions is unavailable. Thus, the objective of this review is to discuss filtering, decomposition, entropy, and cyclostationary analysis techniques, as well as summarizing the remaining issues. This review will discuss various vibration-based diagnostic approaches developed for wind turbine gearboxes under nonstationary conditions, including both simulation and experimental approaches. Studies on dynamic models of gear systems and advanced signal-processing techniques developed for nonstationary conditions are reviewed. Additionally, the importance of multi-sensor and cointegration based approaches is discussed, and intelligent classification methods that have been used to distinguish healthy and faulty gear systems are also reviewed. Finally, the remaining research challenges are outlined.
A Review on Vibration-Based Fault Diagnosis Techniques for Wind Turbine Gearboxes Operating Under Nonstationary Conditions
J. Inst. Eng. India Ser. C
Sharma, Vikas (Autor:in)
Journal of The Institution of Engineers (India): Series C ; 102 ; 507-523
01.04.2021
17 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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