Deep learning algorithms for bearing fault diagnostics—A comprehensive review
In this survey paper, we systematically summarize existing literature on bearing fault
diagnostics with deep learning (DL) algorithms. While conventional machine learning (ML) …
diagnostics with deep learning (DL) algorithms. While conventional machine learning (ML) …
A review of failure modes, condition monitoring and fault diagnosis methods for large-scale wind turbine bearings
Large-scale wind turbine bearings including main bearings, gearbox bearings, generator
bearings, blade bearings and yaw bearings, are critical components for wind turbines to …
bearings, blade bearings and yaw bearings, are critical components for wind turbines to …
A hybrid prognostics approach for estimating remaining useful life of rolling element bearings
Remaining useful life (RUL) prediction of rolling element bearings plays a pivotal role in
reducing costly unplanned maintenance and increasing the reliability, availability, and safety …
reducing costly unplanned maintenance and increasing the reliability, availability, and safety …
Interpretable convolutional neural network with multilayer wavelet for Noise-Robust Machinery fault diagnosis
Convolutional neural networks (CNNs) are being utilized for mechanical fault diagnosis, due
to its excellent automatic discriminative feature learning ability. However, the poor …
to its excellent automatic discriminative feature learning ability. However, the poor …
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 …
Intelligent fault diagnosis of rolling bearings based on normalized CNN considering data imbalance and variable working conditions
Intelligent fault detection and diagnosis, as an important approach, play a crucial role in
ensuring the stable, reliable and safe operation of rolling bearings, which is one of the most …
ensuring the stable, reliable and safe operation of rolling bearings, which is one of the most …
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 …
A review of artificial intelligence methods for condition monitoring and fault diagnosis of rolling element bearings for induction motor
The fault detection and diagnosis (FDD) along with condition monitoring (CM) and of rotating
machinery (RM) have critical importance for early diagnosis to prevent severe damage of …
machinery (RM) have critical importance for early diagnosis to prevent severe damage of …
Deep transfer network with joint distribution adaptation: A new intelligent fault diagnosis framework for industry application
In recent years, an increasing popularity of deep learning model for intelligent condition
monitoring and diagnosis as well as prognostics used for mechanical systems and …
monitoring and diagnosis as well as prognostics used for mechanical systems and …
Deep transfer learning with limited data for machinery fault diagnosis
Investigation of deep transfer learning on machinery fault diagnosis is helpful to overcome
the limitations of a large volume of training data, and accelerate the practical applications of …
the limitations of a large volume of training data, and accelerate the practical applications of …