Enabling Health Monitoring Approach Based on Vibration Data for Accurate Prognostics

By Kamran Javed, R. Gouriveau, Noureddine Zerhouni, P. Nectoux. IEEE transactions on industrial electronics (1982. Print), 2015

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A Two-Stage Data-Driven-Based Prognostic Approach for Bearing Degradation Problem (2016, background): “Its definition can be described as the length between the current inspection time and the end of the plants’ allowed useful life [13]–[17].”
Machinery health prognostics: A systematic review from data acquisition to RUL prediction (2018, methodology): “Besides the above two commonly used ANNs, there are some other ANNs [45,73,325,326] in the field of machinery RUL prediction.”
A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element Bearings (2020, methodology): “[18] proposed a summation wavelet extreme learning machine approach to perform the RUL estimation task of bearings.”
A Model-Based Method for Remaining Useful Life Prediction of Machinery (2016, background): “xk is the health state at tk , which is hard to be acquired in real applications and is generally represented by a health indicator [28], [29], [34].”
Motor Bearing Fault Detection Using Spectral Kurtosis-Based Feature Extraction Coupled With K-Nearest Neighbor Distance Analysis (2016, background): “Signals that provide efficient monitoring include vibration signals [5], [6], motor current signals [7], [8], acoustic emission signals [9], [10], and more recently, stray flux [11].”