Transfer learning algorithms for bearing remaining useful life prediction: A comprehensive review from an industrial application perspective
Accurate remaining useful life (RUL) prediction for rolling bearings encounters many
challenges such as complex degradation processes, varying working conditions, and …
challenges such as complex degradation processes, varying working conditions, and …
Challenges in predictive maintenance–A review
Predictive maintenance (PdM) aims the reduction of costs to increase the competitive
strength of the enterprises. It uses sensor data together with analytics techniques to optimize …
strength of the enterprises. It uses sensor data together with analytics techniques to optimize …
[HTML][HTML] CNN parameter design based on fault signal analysis and its application in bearing fault diagnosis
As a representative deep learning network, Convolutional Neural Network (CNN) has been
extensively used in bearing fault diagnosis and many good results have been reported. In …
extensively used in bearing fault diagnosis and many good results have been reported. In …
Using deep learning-based approach to predict remaining useful life of rotating components
J Deutsch, D He - IEEE Transactions on Systems, Man, and …, 2017 - ieeexplore.ieee.org
In the age of Internet of Things and Industrial 4.0, prognostic and health management (PHM)
systems are used to collect massive real-time data from mechanical equipment. PHM big …
systems are used to collect massive real-time data from mechanical equipment. PHM big …
A systematic review of data-driven approaches to fault diagnosis and early warning
As an important stage of life cycle management, machinery PHM (prognostics and health
management), an emerging subject in mechanical engineering, has seen a huge amount of …
management), an emerging subject in mechanical engineering, has seen a huge amount of …