A comprehensive review on signal-based and model-based condition monitoring of wind turbines: Fault diagnosis and lifetime prognosis

H Badihi, Y Zhang, B Jiang, P Pillay… - Proceedings of the …, 2022 - ieeexplore.ieee.org
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 …

Gearbox condition monitoring in wind turbines: A review

JP Salameh, S Cauet, E Etien, A Sakout… - Mechanical Systems and …, 2018 - Elsevier
Wind turbine technology is experiencing rapid growth with respect to size, market share, and
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

M Azamfar, J Singh, I Bravo-Imaz, J Lee - Mechanical Systems and Signal …, 2020 - Elsevier
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 …

Variable speed induction motors' fault detection based on transient motor current signatures analysis: A review

MF Yakhni, S Cauet, A Sakout, H Assoum… - … Systems and Signal …, 2023 - Elsevier
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 …

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 …

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 …

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 …

Deep learning-based cross-domain adaptation for gearbox fault diagnosis under variable speed conditions

J Singh, M Azamfar, A Ainapure… - … Science and Technology, 2020 - iopscience.iop.org
Existing intelligent gearbox fault diagnosis approaches have two shortcomings:(a) their
performance is mostly confined to manual handcrafted features, and (b) they follow a …

[HTML][HTML] Fault diagnosis and fault frequency determination of permanent magnet synchronous motor based on deep learning

CS Wang, IH Kao, JW Perng - Sensors, 2021 - mdpi.com
The early diagnosis of a motor is important. Many researchers have used deep learning to
diagnose motor applications. This paper proposes a one-dimensional convolutional neural …

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 …