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 …
Review of tool condition monitoring in machining and opportunities for deep learning
Tool condition monitoring and machine tool diagnostics are performed using advanced
sensors and computational intelligence to predict and avoid adverse conditions for cutting …
sensors and computational intelligence to predict and avoid adverse conditions for cutting …
Highly accurate machine fault diagnosis using deep transfer learning
We develop a novel deep learning framework to achieve highly accurate machine fault
diagnosis using transfer learning to enable and accelerate the training of deep neural …
diagnosis using transfer learning to enable and accelerate the training of deep neural …
Deep learning and its applications to machine health monitoring
Abstract Since 2006, deep learning (DL) has become a rapidly growing research direction,
redefining state-of-the-art performances in a wide range of areas such as object recognition …
redefining state-of-the-art performances in a wide range of areas such as object recognition …
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 …
DCNN-based multi-signal induction motor fault diagnosis
Deep learning (DL) architecture, which exploits multiple hidden layers to learn hierarchical
representations automatically from massive input data, presents a promising tool for …
representations automatically from massive input data, presents a promising tool for …
[HTML][HTML] Deep learning for manufacturing sustainability: Models, applications in Industry 4.0 and implications
Recent advancements and developments in artificial intelligence (AI) based approaches
have shifted the manufacturing practices towards the fourth industrial revolution, considered …
have shifted the manufacturing practices towards the fourth industrial revolution, considered …
Deep learning models for predictive maintenance: a survey, comparison, challenges and prospects
O Serradilla, E Zugasti, J Rodriguez, U Zurutuza - Applied Intelligence, 2022 - Springer
Given the growing amount of industrial data in the 4th industrial revolution, deep learning
solutions have become popular for predictive maintenance (PdM) tasks, which involve …
solutions have become popular for predictive maintenance (PdM) tasks, which involve …
Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach: A review of two decades of research
Industry 4.0 is an era of smart manufacturing. Manufacturing is impossible without the use of
machinery. The majority of these machines comprise rotating components and are called …
machinery. The majority of these machines comprise rotating components and are called …
Challenges and opportunities of deep learning models for machinery fault detection and diagnosis: A review
In the age of industry 4.0, deep learning has attracted increasing interest for various
research applications. In recent years, deep learning models have been extensively …
research applications. In recent years, deep learning models have been extensively …