Applications of machine learning to machine fault diagnosis: A review and roadmap
Intelligent fault diagnosis (IFD) refers to applications of machine learning theories to
machine fault diagnosis. This is a promising way to release the contribution from human …
machine fault diagnosis. This is a promising way to release the contribution from human …
A review on the application of blind deconvolution in machinery fault diagnosis
Fault diagnosis is of significance for ensuring the safe and reliable operation of machinery
equipment. Due to the heavy noise and interference, it is difficult to detect the fault directly …
equipment. Due to the heavy noise and interference, it is difficult to detect the fault directly …
Autoencoder-based representation learning and its application in intelligent fault diagnosis: A review
Z Yang, B Xu, W Luo, F Chen - Measurement, 2022 - Elsevier
With the increase of the scale and complexity of mechanical equipment, traditional intelligent
fault diagnosis (IFD) based on shallow machine learning methods is unable to meet the …
fault diagnosis (IFD) based on shallow machine learning methods is unable to meet the …
Vibration based condition monitoring and fault diagnosis of wind turbine planetary gearbox: A review
As one of the most immensely growing renewable energies, the wind power industry also
experiences a high failure rate and operation & maintenance cost. Therefore, the condition …
experiences a high failure rate and operation & maintenance cost. Therefore, the condition …
A multi-stage semi-supervised learning approach for intelligent fault diagnosis of rolling bearing using data augmentation and metric learning
Limited condition monitoring data are recorded with label information in practice, which
make the fault identification task more challenging. A semi-supervised learning (SSL) …
make the fault identification task more challenging. A semi-supervised learning (SSL) …
Damage detection techniques for wind turbine blades: A review
Blades play a vital role in wind turbine system performances. However, they are susceptible
to damage arising from complex and irregular loading or even cause catastrophic collapse …
to damage arising from complex and irregular loading or even cause catastrophic collapse …
Development of intelligent fault-tolerant control systems with machine learning, deep learning, and transfer learning algorithms: a review
Abstract Intelligent Fault-Tolerant Control (IFTC) refers to the applications of machine
learning algorithms for fault diagnosis and design of Fault-Tolerant Control (FTC). The …
learning algorithms for fault diagnosis and design of Fault-Tolerant Control (FTC). The …
Deep learning for prognostics and health management: State of the art, challenges, and opportunities
B Rezaeianjouybari, Y Shang - Measurement, 2020 - Elsevier
Improving the reliability of engineered systems is a crucial problem in many applications in
various engineering fields, such as aerospace, nuclear energy, and water declination …
various engineering fields, such as aerospace, nuclear energy, and water declination …
A physics-informed deep learning approach for bearing fault detection
In recent years, advances in computer technology and the emergence of big data have
enabled deep learning to achieve impressive successes in bearing condition monitoring …
enabled deep learning to achieve impressive successes in bearing condition monitoring …
Fault diagnosis based on extremely randomized trees in wireless sensor networks
Abstract Wireless Sensor Network (WSN) being highly diversified cyber–physical system
makes it vulnerable to numerous failures, which can cause devastation towards safety …
makes it vulnerable to numerous failures, which can cause devastation towards safety …