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Statistical Modeling of Bearing Degradation Signals

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Prognostics and Health Management of Electronics
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Vibration‐based Condition Monitoring
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Stochastic modelling and analysis of degradation for highly reliable products
inferredcites →https://doi.org/10.1007/978-1-4419-1545-0openalex-snapshot
Wavelets: Theory and Applications for Manufacturing
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Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery
inferredcites →https://doi.org/10.1016/j.aei.2004.08.001openalex-snapshot
Robust performance degradation assessment methods for enhanced rolling element bearing prognostics
inferredcites →https://doi.org/10.1016/j.asoc.2011.03.026openalex-snapshot
A hybrid feature selection scheme and self-organizing map model for machine health assessment
inferredcites →https://doi.org/10.1016/j.ejor.2010.11.018openalex-snapshot
Remaining useful life estimation – A review on the statistical data driven approaches
inferredcites →https://doi.org/10.1016/j.jsv.2007.01.001openalex-snapshot
Online tracking of bearing wear using wavelet packet decomposition and probabilistic modeling: A method for bearing prognostics
inferredcites →https://doi.org/10.1016/j.ymssp.2004.09.001openalex-snapshot
The spectral kurtosis: a useful tool for characterising non-stationary signals
inferredcites →https://doi.org/10.1016/j.ymssp.2006.02.009openalex-snapshot
Approximate Entropy as a diagnostic tool for machine health monitoring
inferredcites →https://doi.org/10.1016/j.ymssp.2009.07.012openalex-snapshot
Bearing performance degradation assessment based on lifting wavelet packet decomposition and fuzzy c-means
inferredcites →https://doi.org/10.1016/j.ymssp.2012.03.011openalex-snapshot
Combining Relevance Vector Machines and exponential regression for bearing residual life estimation
inferredcites →https://doi.org/10.1016/j.ymssp.2015.04.004openalex-snapshot
Criterion fusion for spectral segmentation and its application to optimal demodulation of bearing vibration signals
inferredcites →https://doi.org/10.1023/a:1009664101413openalex-snapshot
Modelling Accelerated Degradation Data Using Wiener Diffusion With A Time Scale Transformation
inferredcites →https://doi.org/10.1080/00031305.1986.10475419openalex-snapshot
An Analytic Approximation to the Distribution of Lilliefors's Test Statistic for Normality
inferredcites →https://doi.org/10.1080/00224065.2003.11980233openalex-snapshot
The Changepoint Model for Statistical Process Control
inferredcites →https://doi.org/10.1080/07408170590929018openalex-snapshot
Residual-life distributions from component degradation signals: A Bayesian approach
inferredcites →https://doi.org/10.1080/07408170802369409openalex-snapshot
Residual-life estimation for components with non-symmetric priors
inferredcites →https://doi.org/10.1080/0740817x.2012.706376openalex-snapshot
Condition monitoring and remaining useful life prediction using degradation signals: revisited
inferredcites →https://doi.org/10.1109/79.543975openalex-snapshot
The expectation-maximization algorithm
inferredcites →https://doi.org/10.1109/tase.2007.910302openalex-snapshot
A Neural Network Degradation Model for Computing and Updating Residual Life Distributions
inferredcites →https://doi.org/10.1109/tim.2016.2601004openalex-snapshot
A New Method Based on Stochastic Process Models for Machine Remaining Useful Life Prediction
inferredcites →https://doi.org/10.1109/tr.2008.2011659openalex-snapshot
Residual Life Predictions in the Absence of Prior Degradation Knowledge
inferredcites →https://doi.org/10.1109/tr.2008.928245openalex-snapshot
Prognostic Degradation Models for Computing and Updating Residual Life Distributions in a Time-Varying Environment
inferredcites →https://doi.org/10.1109/tr.2011.2104716openalex-snapshot
Combined Probability Approach and Indirect Data-Driven Method for Bearing Degradation Prognostics
inferredcites →https://doi.org/10.1109/tr.2011.2182221openalex-snapshot
Remaining Useful Life Estimation Based on a Nonlinear Diffusion Degradation Process
inferredcites →https://doi.org/10.1109/tr.2012.2194175openalex-snapshot
Remaining Useful Life Estimation of Critical Components With Application to Bearings
inferredcites →https://doi.org/10.1109/tr.2016.2570568openalex-snapshot
A Model-Based Method for Remaining Useful Life Prediction of Machinery
inferredcites →https://doi.org/10.1115/1.1379745openalex-snapshot
Wavelet Analysis and Envelope Detection For Rolling Element Bearing Fault Diagnosis—Their Effectiveness and Flexibilities
inferredcites →https://doi.org/10.1177/1077546314547224openalex-snapshot
An equivalent cyclic energy indicator for bearing performance degradation assessment
inferredcites →https://doi.org/10.1243/09544062jmes1224openalex-snapshot
Spectral entropy: A complementary index for rolling element bearing performance degradation assessment
inferredcites →https://doi.org/10.2307/1269554openalex-snapshot
Models for Variable-Stress Accelerated Life Testing Experiments Based on Wiener Processes and the Inverse Gaussian Distribution

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Rolling Bearing Fault Detection of Rotary Machine Using a Novel Adaptive Sparse Representation
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Stochastic Degradation Modeling and Remaining Useful Lifetime Prediction Based on Long Short-Term Memory Network
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Remaining useful life prediction via a variational autoencoder and a time‐window‐based sequence neural network
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Fault Representations of Bearing Race Based on Grayscale Maps and CNN Networks
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Multifractal Characteristics on Multiple Pollution Variables in Malaysia
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Accelerated degradation tests with inspection effects
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Stochastic degradation modeling and remaining useful lifetime prediction based on long short-term memory network
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Remaining Useful Life Prediction Using a Novel Two-Stage Wiener Process With Stage Correlation
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Deep Decoupling Convolutional Neural Network for Intelligent Compound Fault Diagnosis
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Flexible Kurtogram for Extracting Repetitive Transients for Prognostics and Health Management of Rotating Components
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Remaining Useful Life Prediction of Rolling Bearings Based on RMS-MAVE and Dynamic Exponential Regression Model
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Estimation of Bearing Remaining Useful Life Based on Multiscale Convolutional Neural Network
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Health Indicator Construction Method of Bearings Based on Wasserstein Dual-Domain Adversarial Networks Under Normal Data Only
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Manifold Sensing-Based Convolution Sparse Self-Learning for Defective Bearing Morphological Feature Extraction
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Performance Degradation Assessment for Coaxial Bearings Using Kernel JADE and Two-Class Model
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An Adaptive Weighted Adjacent Difference Sparse Representation for Bearing Fault Diagnosis
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Adaptive Sparse Representation-Based Minimum Entropy Deconvolution for Bearing Fault Detection
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Continuous Health Monitoring of Rolling Element Bearing Based on Nonlinear Oscillatory Sample Entropy
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MMFNet: Multisensor Data and Multiscale Feature Fusion Model for Intelligent Cross-Domain Machinery Fault Diagnosis
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DLVR-NWP: A Novel Data-Driven Bearing Degradation Model for RUL Estimation
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CGASNet: A Generalized Zero-Shot Learning Compound Fault Diagnosis Approach for Bearings
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A Novel Nonlinear Dynamic Measure for Early Detection of Bearing Fault Using Weighted Squared Envelope-Based Symbolic Lempel-Ziv Complexity
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Dynamic Model-Assisted Bearing Remaining Useful Life Prediction Using the Cross-Domain Transformer Network
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Entropy Based Fault Classification Using the Case Western Reserve University Data: A Benchmark Study
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Failure Prognosis and Applications—A Survey of Recent Literature
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Oscillatory Lempel–Ziv Complexity Calculation as a Nonlinear Measure for Continuous Monitoring of Bearing Health
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Bayesian Dual-Input-Channel LSTM-Based Prognostics: Toward Uncertainty Quantification Under Varying Future Operations
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Reliability Modeling and Parameter Estimation for High-Speed Train Wheels Subject to Multi-Dimensional Degradation Processes Considering Mutual Dependency
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Condition-Adaptive Permutation Entropy: A Novel Dynamic Complexity-Based Health Indicator for Bearing Health Monitoring
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Independent Competing Risks in Common Shape-Parameter Weibull Systems, With Application to Rolling Bearing Service Life
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Remaining Useful Life Prediction of Bearings Using Ensemble Learning: The Impact of Diversity in Base Learners and Features
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Degradation-Aware Ensemble of Diverse Predictors for Remaining Useful Life Prediction
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Remaining Useful Life Prediction of Rolling Bearings Using Electrostatic Monitoring Based on Two-Stage Information Fusion Stochastic Filtering
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Prediction of performance deterioration of rolling bearing based on JADE and PSO-SVM
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Data preprocessing-based bearing fault diagnosis in PHM: A systematic review
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Degradation assessment of bearing based on machine learning classification matrix
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A Frequency-Adaptive Feature Extraction Framework for Bearing Remaining Useful Life Prediction
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Equipment Health State Assessment Based on MIC-XGBoost
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Accelerated Life Test of Bearing Under Electrical Stress
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Intelligent Diagnosis of Bearing Faults Using Feature Selection Based on Minimum Redundancy Maximum Relevance and Neural Network Optimization with Particle Swarm Method
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Related Entropy Theories Application in Condition Monitoring of Rotating Machineries
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Remaining Useful Life Prediction of MOSFETs via the Takagi–Sugeno Framework
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Research on the Performance Degradation Rules of Rolling Bearings Under Discrete Constant Conditions
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Intelligent Workshop Bearing Fault Diagnosis Method Based on Improved Convolutional Neural Network
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Intelligent Fault Diagnosis of Rolling Bearings Based on a Complete Frequency Range Feature Extraction and Combined Feature Selection Methodology
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RMS Based Health Indicators for Remaining Useful Lifetime Estimation of Bearings
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