A review of the application of deep learning in intelligent fault diagnosis of rotating machinery
Z Zhu, Y Lei, G Qi, Y Chai, N Mazur, Y An, X Huang - Measurement, 2023 - Elsevier
With the rapid development of industry, fault diagnosis plays a more and more important role
in maintaining the health of equipment and ensuring the safe operation of equipment. Due to …
in maintaining the health of equipment and ensuring the safe operation of equipment. Due to …
A review of wind speed and wind power forecasting with deep neural networks
The use of wind power, a pollution-free and renewable form of energy, to generate electricity
has attracted increasing attention. However, intermittent electricity generation resulting from …
has attracted increasing attention. However, intermittent electricity generation resulting from …
Dual-threshold attention-guided GAN and limited infrared thermal images for rotating machinery fault diagnosis under speed fluctuation
End-to-end intelligent diagnosis of rotating machinery under speed fluctuation and limited
samples is challenging in industrial practice. The existing limited samples methods usually …
samples is challenging in industrial practice. The existing limited samples methods usually …
Intelligent fault diagnosis of machines with small & imbalanced data: A state-of-the-art review and possible extensions
The research on intelligent fault diagnosis has yielded remarkable achievements based on
artificial intelligence-related technologies. In engineering scenarios, machines usually work …
artificial intelligence-related technologies. In engineering scenarios, machines usually work …
Intelligent fault diagnosis of rotor-bearing system under varying working conditions with modified transfer convolutional neural network and thermal images
The existing intelligent fault diagnosis methods of rotor-bearing system mainly focus on
vibration analysis under steady operation, which has low adaptability to new scenes. In this …
vibration analysis under steady operation, which has low adaptability to new scenes. In this …
A highly sensitive triboelectric vibration sensor for machinery condition monitoring
Vibration sensors are involved extensively in a variety of applications. Especially in the era
of the Internet of Things, developing self‐powered vibration sensors has become a very …
of the Internet of Things, developing self‐powered vibration sensors has become a very …
A survey of transfer learning for machinery diagnostics and prognostics
In industrial manufacturing systems, failures of machines caused by faults in their key
components greatly influence operational safety and system reliability. Many data-driven …
components greatly influence operational safety and system reliability. Many data-driven …
Intelligent mechanical fault diagnosis using multisensor fusion and convolution neural network
Diagnosis of mechanical faults in manufacturing systems is critical for ensuring safety and
saving costs. With the development of data transmission and sensor technologies …
saving costs. With the development of data transmission and sensor technologies …
Fault diagnosis for small samples based on attention mechanism
Aiming at the application of deep learning in fault diagnosis, mechanical rotating equipment
components are prone to failure under complex working environment, and the industrial big …
components are prone to failure under complex working environment, and the industrial big …
Wind turbine gearbox anomaly detection based on adaptive threshold and twin support vector machines
Data-driven condition monitoring reduces downtime of wind turbines and increases
reliability. Wind turbine operation and maintenance (O&M) cost is a significant factor that …
reliability. Wind turbine operation and maintenance (O&M) cost is a significant factor that …