Generative Transfer Learning for Intelligent Fault Diagnosis of the Wind Turbine Gearbox
نویسندگان
چکیده
منابع مشابه
Study of Intelligence Diagnosis System for Wind Turbine Gearbox Fault
According to the current application and maintenance situation of gearbox of wind turbine, this paper analyzed the remote fault diagnosis system used for monitoring fault occurrence and diagnosing fault, which is a combination of Expert System and Artificial Neural Networks. A practical fault instance of gearbox of wind turbine is analyzed to define the expert system’s knowledge base structure ...
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Wind power has become one of the popular renewable resources all over the world and is anticipated to occupy 12% of the total global electricity generation capacity by 2020. For the harsh environment that the wind turbine operates, fault diagnostic and condition monitoring are important for wind turbine safety and reliability. This paper employs a systematic literature review to report the most...
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Abstract: This paper studies the dynamic response of a wind turbine gearbox under different excitation conditions. The proposed 4 degree-of-freedom (DOF) dynamic model takes into account the key factors such as the time-varying mesh stiffness, bearing stiffness, damping, static transmission error and gear backlash. Both the external excitation due to wind and the internal excitation due to the ...
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Reliable and quick response fault diagnosis is crucial for the wind turbine generator system (WTGS) to avoid unplanned interruption and to reduce the maintenance cost. However, the conditional data generated from WTGS operating in a tough environment is always dynamical and high-dimensional. To address these challenges, we propose a new fault diagnosis scheme which is composed of multiple extre...
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ژورنال
عنوان ژورنال: Sensors
سال: 2020
ISSN: 1424-8220
DOI: 10.3390/s20051361