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A comprehensive review on signal-based and model-based condition monitoring of wind turbines: Fault diagnosis and lifetime prognosis
Wind turbines play an increasingly important role in renewable power generation. To ensure
the efficient production and financial viability of wind power, it is crucial to maintain wind …
the efficient production and financial viability of wind power, it is crucial to maintain wind …
Gearbox condition monitoring in wind turbines: A review
Wind turbine technology is experiencing rapid growth with respect to size, market share, and
technological design. Operational and maintenance cost directly determine whether the …
technological design. Operational and maintenance cost directly determine whether the …
Multisensor data fusion for gearbox fault diagnosis using 2-D convolutional neural network and motor current signature analysis
Gearboxes are widely used in rotating machinery and various industrial applications for
transmission of power and torque. They operate for prolong hours and under different …
transmission of power and torque. They operate for prolong hours and under different …
Variable speed induction motors' fault detection based on transient motor current signatures analysis: A review
Induction motor is a major component in the industrial sector. It is experiencing great
development concerning size, market share, and technological design. Any sudden failure …
development concerning size, market share, and technological design. Any sudden failure …
Detection of gear fault severity based on parameter-optimized deep belief network using sparrow search algorithm
J Gai, K Zhong, X Du, K Yan, J Shen - Measurement, 2021 - Elsevier
In gear fault diagnosis, most current intelligent fault diagnosis methods show good
classification performance for fault pattern recognition. However, when detecting fault …
classification performance for fault pattern recognition. However, when detecting fault …
A discrimination model in waste plastics sorting using NIR hyperspectral imaging system
Y Zheng, J Bai, J Xu, X Li, Y Zhang - Waste Management, 2018 - Elsevier
Classification of plastics is important in the recycling industry. A plastic identification model
in the near infrared spectroscopy wavelength range 1000–2500 nm is proposed for the …
in the near infrared spectroscopy wavelength range 1000–2500 nm is proposed for the …
Condition monitoring of wind turbine gearbox bearing based on deep learning model
J Fu, J Chu, P Guo, Z Chen - Ieee Access, 2019 - ieeexplore.ieee.org
Wind turbines condition monitoring and fault warning have important practical value for wind
farms to reduce maintenance costs and improve operation levels. Due to the increase in the …
farms to reduce maintenance costs and improve operation levels. Due to the increase in the …
Mixed eccentricity fault detection for induction motors based on time synchronous averaging of vibration signals
This article presents a method based on vibration signals to diagnose rotor mixed
eccentricity faults in three-phase squirrel cage induction motors (SCIMs). Rotor eccentricity …
eccentricity faults in three-phase squirrel cage induction motors (SCIMs). Rotor eccentricity …
Investigation of electromechanical coupling vibration characteristics of an electric drive multistage gear system
Y Yi, D Qin, C Liu - Mechanism and machine theory, 2018 - Elsevier
In order to investigate the electromechanical interaction mechanism, a dynamic model of an
electric drive multistage gear system is established, wherein the electromagnetic …
electric drive multistage gear system is established, wherein the electromagnetic …
Deep learning-based cross-domain adaptation for gearbox fault diagnosis under variable speed conditions
Existing intelligent gearbox fault diagnosis approaches have two shortcomings:(a) their
performance is mostly confined to manual handcrafted features, and (b) they follow a …
performance is mostly confined to manual handcrafted features, and (b) they follow a …