Bearing fault detection and diagnosis using case western reserve university dataset with deep learning approaches: A review
A smart factory is a highly digitized and connected production facility that relies on smart
manufacturing. Additionally, artificial intelligence is the core technology of smart factories …
manufacturing. Additionally, artificial intelligence is the core technology of smart factories …
[HTML][HTML] Adoptable approaches to predictive maintenance in mining industry: An overview
The mining industry contributes to the expansion of the global economy by generating vital
commodities. For continuous production, the industry relies significantly on machinery and …
commodities. For continuous production, the industry relies significantly on machinery and …
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 …
[HTML][HTML] Relation between prognostics predictor evaluation metrics and local interpretability SHAP values
Maintenance decisions in domains such as aeronautics are becoming increasingly
dependent on being able to predict the failure of components and systems. When data …
dependent on being able to predict the failure of components and systems. When data …
A new dynamic predictive maintenance framework using deep learning for failure prognostics
KTP Nguyen, K Medjaher - Reliability Engineering & System Safety, 2019 - Elsevier
Abstract In Prognostic Health and Management (PHM) literature, the predictive maintenance
studies can be classified into two groups. The first group focuses on the prognostics step but …
studies can be classified into two groups. The first group focuses on the prognostics step but …
Artificial intelligence in prognostics and health management of engineering systems
S Ochella, M Shafiee, F Dinmohammadi - Engineering Applications of …, 2022 - Elsevier
Prognostics and health management (PHM) has become a crucial aspect of the
management of engineering systems and structures, where sensor hardware and decision …
management of engineering systems and structures, where sensor hardware and decision …
Data-driven prognostic method based on Bayesian approaches for direct remaining useful life prediction
Reliability of prognostics and health management systems relies upon accurate
understanding of critical components' degradation process to predict the remaining useful …
understanding of critical components' degradation process to predict the remaining useful …
[HTML][HTML] Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences
M Kraus, S Feuerriegel - Decision Support Systems, 2019 - Elsevier
Predicting the remaining useful life of machinery, infrastructure, or other equipment can
facilitate preemptive maintenance decisions, whereby a failure is prevented through timely …
facilitate preemptive maintenance decisions, whereby a failure is prevented through timely …
[图书][B] From prognostics and health systems management to predictive maintenance 1: Monitoring and prognostics
This book addresses the steps needed to monitor health assessment systems and the
anticipation of their failures: choice and location of sensors, data acquisition and processing …
anticipation of their failures: choice and location of sensors, data acquisition and processing …
Predicting remaining useful life of rolling bearings based on deep feature representation and long short-term memory neural network
For bearing remaining useful life prediction problem, the traditional machine-learning-based
methods are generally short of feature representation ability and incapable of adaptive …
methods are generally short of feature representation ability and incapable of adaptive …