Keyphrases
Electrical Machines
100%
Failure Time
100%
Degradation Data
100%
Prognostic Approach
100%
Rolling Element Bearing
100%
Failure Prognostics
100%
Degradation Characteristics
50%
Degradation Process
33%
Mahalanobis Distance
33%
Prediction Accuracy
16%
Reduction Method
16%
Statistical Features
16%
Frequency Features
16%
Degradation Model
16%
Hilbert-Huang Transform
16%
Regression-based Method
16%
Practical Case Study
16%
Local Time
16%
Energy Feature
16%
Health Management
16%
Feature Reduction
16%
Global Time
16%
Continuous Updating
16%
Health Index
16%
Feature Frequency
16%
Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN)
16%
Exponential Regression
16%
Dynamic Principal Component Analysis
16%
Remaining Lifetime
16%
Failure Experiment
16%
Bayesian Algorithm
16%
Distance Health
16%
Fault Evolution
16%
Multiple Degradations
16%
Fault Frequency
16%
Run-to-failure
16%
Failure Time Prediction
16%
Degradation Feature Extraction
16%
Empirical Bayesian
16%
Intrinsic Energy
16%
Local Degradation
16%
Transform Method
16%
Prediction Steps
16%
PRONOSTIA
16%
Engineering
Electrical Machine
100%
Rolling Element
100%
Mahalanobis Distance
33%
Principal Components
33%
Feature Extraction
16%
Accurate Prediction
16%
Degradation Model
16%
Hilbert-Huang Transform
16%
Local Time
16%
Degradation Process
16%
Process Time
16%
Component Analysis
16%
Step Prediction
16%
Statistical Feature
16%
Global Time
16%
Empirical-Mode Decomposition
16%