A review by discussion of condition monitoring and fault diagnosis in machine tools, Int. J. Mach. Tools Manuf, vol.34, issue.4, pp.527-551, 1994. ,

An integrated platform for diagnostics, prognostics and maintenance optimization, Proc. Intell. Maint. Syst, pp.15-27, 2004. ,

A review on machinery diagnostics and prognostics implementing condition-based maintenance, Mech. Syst. Signal Process, vol.20, issue.7, pp.1483-1510, 2006. ,

How to track rolling element bearing health with vibration signature analysis, vol.25, pp.24-35, 1991. ,

The Reliability-based maintenance strategy: a vision for improving industrial productivity, CSI Ind. Report, 1993. ,

, What is a Bearing?

Introduction to Bearings, p.1, 2018. ,

, Structure and composition, p.1, 2019.

Rolling bearing analysis: advanced concepts of bearing technology, 5thed. NewYork: TaylorandFrancisGroup, 2007. ,

, Bearing Failure: Causes and Cures

A Review of Rolling Element Bearing Vibration'Detection, Diagnosis and Prognosis, DEFENCE SCIENCE AND TECHNOLOGY ORGANIZATION, 1994. ,

A review of rolling element bearing health monitoring. III-Preliminary test results on eddy current proximity transducer technique, International Conference on Vibrations in Rotating Machinery, 3 rd, pp.119-125, 1984. ,

Condition monitoring of slow speed rolling element bearings in a mechanically noisy environment, Appita J, vol.42, issue.3, pp.206-208, 1989. ,

Rolling Element Bearing Diagnostics with Lasers, Microphones and Accelerometers, Vib. Institute(USA), pp.43-52, 1992. ,

Acoustic emission, vol.2, 1983. ,

Use of acoustic emission for machine condition monitoring, Br. J. Non-Destructive Test, vol.35, issue.2, pp.75-78, 1993. ,

Fundamentals of noise and vibration analysis for engineers, 2003. ,

Vibration-based condition monitoring: industrial, aerospace and automotive applications, 2011. ,

, Mechanical vibrations, vol.4, 2011.

Vibration based condition assessment of rolling element bearings with localized defects, Int. J. Sci. Technol. Res, vol.2, issue.4, pp.149-155, 2013. ,

Bi-spectrum based-EMD applied to the nonstationary vibration signals for bearing faults diagnosis, ISA Trans, vol.53, issue.5, pp.1650-1660, 2014. ,

Non-stationary signal processing for bearing health monitoring, Int. J. Manuf. Res, vol.1, issue.1, pp.18-40, 2006. ,

Experimental investigations on induction machine condition monitoring and fault diagnosis using digital signal processing techniques, Electr. Power Syst. Res, vol.65, issue.3, pp.197-221, 2003. ,

, The Fourier transform and its applications, vol.31999, 1986.

Short term spectral analysis, synthesis, and modification by discrete Fourier transform, IEEE Trans. Acoust, vol.25, issue.3, pp.235-238, 1977. ,

Comparison of Methods for Different Time-frequency Analysis of Vibration Signal, vol.7, pp.68-74, 2012. ,

On the quantum correction for thermodynamic equilibrium, Part I: Physical Chemistry. Part II: Solid State Physics, pp.110-120, 1997. ,

The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines, Mech. Syst. Signal Process, vol.20, issue.2, pp.308-331, 2006. ,

URL : https://hal.archives-ouvertes.fr/hal-01714436

Spectral kurtosis optimization for rolling element bearings, ISSPA, pp.839-842, 2005. ,

Application of an improved kurtogram method for fault diagnosis of rolling element bearings, Mech. Syst. Signal Process, vol.25, issue.5, pp.1738-1749, 2011. ,

The enhancement of fault detection and diagnosis in rolling element bearings using minimum entropy deconvolution combined with spectral kurtosis, Mech. Syst. Signal Process, vol.21, issue.6, pp.2616-2633, 2007. ,

An enhanced Kurtogram method for fault diagnosis of rolling element bearings, Mech. Syst. Signal Process, vol.35, issue.1-2, pp.176-199, 2013. ,

Cyclostationary modelling of rotating machine vibration signals, Mech. Syst. Signal Process, vol.18, issue.6, pp.1285-1314, 2004. ,

URL : https://hal.archives-ouvertes.fr/hal-00552018

Extracting repetitive transients for rotating machinery diagnosis using multiscale clustered grey infogram, Mech. Syst. Signal Process, vol.76, pp.157-173, 2016. ,

Testing second order cyclostationarity in the squared envelope spectrum of non-white vibration signals, Mech. Syst. Signal Process, vol.40, issue.1, pp.38-55, 2013. ,

Application of the horizontal slice of cyclic bispectrum in rolling element bearings diagnosis, Mech. Syst. Signal Process, vol.26, pp.229-243, 2012. ,

Finding a frequency signature for a cyclostationary signal with applications to wheel bearing diagnostics, Mech. Syst. Signal Process, vol.38, issue.1, pp.55-64, 2013. ,

The Autogram: An effective approach for selecting the optimal demodulation band in rolling element bearings diagnosis, Mech. Syst. Signal Process, vol.105, pp.294-318, 2018. ,

Wavelet analysis and envelope detection for rolling element bearing fault diagnosis-their effectiveness and flexibilities, J. Vib. Acoust, vol.123, issue.3, pp.303-310, 2001. ,

Multi-fault diagnosis of rolling bearing elements using wavelet analysis and hidden Markov model based fault recognition, Ndt E Int, vol.38, issue.8, pp.654-664, 2005. ,

Feature extraction based on Morlet wavelet and its application for mechanical fault diagnosis, J. Sound Vib, vol.234, issue.1, pp.135-148, 2000. ,

Rolling element bearings multi-fault classification based on the wavelet denoising and support vector machine, Mech. Syst. Signal Process, vol.21, issue.7, pp.2933-2945, 2007. ,

Vibration analysis of rotating machinery using time-frequency analysis and wavelet techniques, Mech. Syst. Signal Process, vol.25, issue.6, pp.2083-2101, 2011. ,

Fault diagnosis of rotating machinery based on improved wavelet package transform and SVMs ensemble, Mech. Syst. Signal Process, vol.21, issue.2, pp.688-705, 2007. ,

Detection of bearing faults using a novel adaptive morphological update lifting wavelet, Chinese J. Mech. Eng, vol.30, issue.6, pp.1305-1313, 2017. ,

Research of the lifting wavelet arithmetic and applied in rotary mechanic fault diagnosis, Journal of physics: conference series, vol.48, p.696, 2006. ,

Microarray image enhancement by denoising using decimated and undecimated multiwavelet transforms, Signal, Image Video Process, vol.4, issue.2, pp.177-185, 2010. ,

Construction and selection of lifting-based multiwavelets for mechanical fault detection, Mech. Syst. Signal Process, vol.40, issue.2, pp.571-588, 2013. ,

Multiwavelet denoising with improved neighboring coefficients for application on rolling bearing fault diagnosis, Mech. Syst. Signal Process, vol.25, issue.1, pp.285-304, 2011. ,

Adaptive multiwavelets via two-scale similarity transforms for rotating machinery fault diagnosis, Mech. Syst. Signal Process, vol.23, issue.5, pp.1490-1508, 2009. ,

Multiwavelet construction via an adaptive symmetric lifting scheme and its applications for rotating machinery fault diagnosis, Meas. Sci. Technol, vol.20, issue.4, p.45103, 2009. ,

Construction of customized redundant multiwavelet via increasing multiplicity for fault detection of rotating machinery ,

, Syst. Signal Process, vol.42, issue.1-2, pp.206-224, 2014.

Noise suppression and signal compression using the wavelet packet transform, Chemom. Intell. Lab. Syst, vol.36, issue.2, pp.81-94, 1997. ,

Selection of wavelet packet basis for rotating machinery fault diagnosis, J. Sound Vib, vol.284, issue.3-5, pp.567-582, 2005. ,

Rolling element bearing fault diagnosis using wavelet packets, Ndt E Int, vol.35, issue.3, pp.197-205, 2002. ,

Fault diagnosis of rotating machinery based on the statistical parameters of wavelet packet paving and a generic support vector regressive classifier, Measurement, vol.46, issue.4, pp.1551-1564, 2013. ,

Rolling bearing fault diagnosis based on wavelet packet decomposition and multi-scale permutation entropy, Entropy, vol.17, issue.9, pp.6447-6461, 2015. ,

The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, Proc. R. Soc. London. Ser. A Math. Phys. Eng. Sci, vol.454, pp.903-995, 1971. ,

A roller bearing fault diagnosis method based on EMD energy entropy and ANN, J. Sound Vib, vol.294, issue.1-2, pp.269-277, 2006. ,

Fault diagnosis of rotating machinery based on multiple ANFIS combination with GAs, Mech. Syst. Signal Process, vol.21, issue.5, pp.2280-2294, 2007. ,

A fault diagnosis approach for roller bearing based on IMF envelope spectrum and SVM, Measurement, vol.40, issue.9, pp.943-950, 2007. ,

Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals, Appl. Acoust, vol.89, pp.16-27, 2015. ,

A new approach to intelligent fault diagnosis of rotating machinery, Expert Syst. Appl, vol.35, issue.4, pp.1593-1600, 2008. ,

Application of EMD method and Hilbert spectrum to the fault diagnosis of roller bearings, Mech. Syst. Signal Process, vol.19, issue.2, pp.259-270, 2005. ,

Ensemble empirical mode decomposition: a noise-assisted data analysis method, Adv. Adapt. Data Anal, vol.1, issue.01, pp.1-41, 2009. ,

A novel bearing fault diagnosis model integrated permutation entropy, ensemble empirical mode decomposition and optimized SVM, Measurement, vol.69, pp.164-179, 2015. ,

Multi-fault diagnosis for rolling element bearings based on ensemble empirical mode decomposition and optimized support vector machines, Mech. Syst. Signal Process, vol.41, issue.1-2, pp.127-140, 2013. ,

Early damage detection of roller bearings using wavelet packet decomposition, ensemble empirical mode decomposition and support vector machine, Meccanica, vol.50, issue.3, pp.865-874, 2015. ,

A hybrid fault diagnosis method using morphological filter-translation invariant wavelet and improved ensemble empirical mode decomposition, Mech. Syst. Signal Process, vol.50, pp.101-115, 2015. ,

Fault diagnosis of rolling bearing based on second generation wavelet denoising and morphological filter, J. Mech. Sci. Technol, vol.29, issue.8, pp.3121-3129, 2015. ,

Rolling element bearing fault detection using PPCA and spectral kurtosis, Measurement, vol.75, pp.180-191, 2015. ,

A hybrid fault diagnosis method based on second generation wavelet de-noising and local mean decomposition for rotating machinery, ISA Trans, vol.61, pp.211-220, 2016. ,

Enabling health monitoring approach based on vibration data for accurate prognostics, IEEE Trans. Ind. Electron, vol.62, issue.1, pp.647-656, 2015. ,

URL : https://hal.archives-ouvertes.fr/hal-01032080

Dominant feature selection for the fault diagnosis of rotary machines using modified genetic algorithm and empirical mode decomposition, J. Sound Vib, vol.344, pp.464-483, 2015. ,

Application of higher order spectral features and support vector machines for bearing faults classification, ISA Trans, vol.54, pp.193-206, 2015. ,

Multi-fault diagnosis for rotating machinery based on orthogonal supervised linear local tangent space alignment and least square support vector machine, Neurocomputing, vol.157, pp.208-222, 2015. ,

Linear feature selection and classification using PNN and SFAM neural networks for a nearly online diagnosis of bearing naturally progressing degradations, Eng. Appl. Artif. Intell, vol.42, pp.67-81, 2015. ,

URL : https://hal.archives-ouvertes.fr/hal-01304000

Bearing fault diagnosis based on statistical locally linear embedding, Sensors, vol.15, issue.7, pp.16225-16247, 2015. ,

Weak fault diagnosis of rotating machinery based on feature reduction with Supervised Orthogonal Local Fisher Discriminant Analysis, Neurocomputing, vol.168, pp.505-519, 2015. ,

Bearing fault recognition method based on neighbourhood component analysis and coupled hidden Markov model ,

, Syst. Signal Process, vol.66, pp.568-581, 2016.

A novel method for mechanical fault diagnosis based on variational mode decomposition and multikernel support vector machine, Shock Vib, vol.2016, 2016. ,

, Bearing rating life

, Bearing Life, p.1, 2019.

An improved exponential model for predicting remaining useful life of rolling element bearings, IEEE Trans. Ind. Electron, vol.62, issue.12, pp.7762-7773, 2015. ,

, Log-Normal distribution, p.1, 2019.

Rotating machinery prognostics: State of the art, challenges and opportunities, Mech. Syst. Signal Process, vol.23, issue.3, pp.724-739, 2009. ,

Adaptive prognostics for rolling element bearing condition, Mech. Syst. Signal Process, vol.13, issue.1, pp.103-113, 1999. ,

A multi-time scale approach to remaining useful life prediction in rolling bearing, Mech. Syst. Signal Process, vol.83, pp.549-567, 2017. ,

An integrated wind turbine failures prognostic approach implementing Kalman smoother with confidence bounds, Appl. Acoust, vol.138, pp.199-208, 2018. ,

Physically based diagnosis and prognosis of cracked rotor shafts, Component and Systems Diagnostics, Prognostics, and Health Management II, vol.4733, pp.122-133, 2002. ,

Prognostics/diagnostics for gas turbine engine bearings, 2003 IEEE Aerospace Conference Proceedings (Cat. No. 03TH8652), vol.7, pp.3095-3103, 2003. ,

Remaining useful life estimation-a review on the statistical data driven approaches, Eur. J. Oper. Res, vol.213, issue.1, pp.1-14, 2011. ,

Stochastic modelling and analysis of degradation for highly reliable products, Appl. Stoch. Model. Bus. Ind, vol.31, issue.1, pp.16-32, 2015. ,

Stochastic Modeling of Wear in Bearing in Motor Pump in Two-Tank System, 2018 15th International Multi-Conference on Systems, Signals & Devices (SSD), pp.611-618, 2018. ,

The inverse Gaussian process as a degradation model, Technometrics, vol.56, issue.3, pp.302-311, 2014. ,

A prognostic model for degrading systems with randomly arriving shocks, 2016 Prognostics and System Health Management Conference, pp.1-4, 2016. ,

A degradation-modeling based prognostic approach for systems with switching operating process, 2016 Prognostics and System Health Management Conference, pp.1-6, 2016. ,

Lifetime prognostics for deteriorating systems with time-varying random jumps, Reliab. Eng. Syst. Saf, vol.167, pp.338-350, 2017. ,

Remaining useful life based maintenance policy for deteriorating systems subject to continuous degradation and shock, Procedia CIRP, vol.72, pp.1311-1315, 2018. ,

Estimating remaining useful life for degrading systems with large fluctuations, J. Control Sci. Eng, vol.2018, 2018. ,

A prediction method for the real-time remaining useful life of wind turbine bearings based on the Wiener process, Renew. energy, vol.127, pp.452-460, 2018. ,

Bearing remaining useful life prediction based on a nonlinear wiener process model, Shock Vib, vol.2018, 2018. ,

A two-stage data-driven-based prognostic approach for bearing degradation problem, IEEE Trans. Ind. Informatics, vol.12, issue.3, pp.924-932, 2016. ,

Hybrid Degradation Equipment Remaining Useful Life Prediction Oriented Parallel Simulation considering Model Soft Switch, Comput. Intell. Neurosci, vol.2019, 2019. ,

Multi-Mode Particle Filter for Bearing Remaining Life Prediction, ASME 2018 13th International Manufacturing Science and Engineering Conference, pp.3-5, 2018. ,

Condition monitoring and remaining useful life prediction using degradation signals: Revisited, IIE Trans, vol.45, issue.9, pp.939-952, 2013. ,

Switching Kalman filter for failure prognostic, Mech. Syst. Signal Process, vol.52, pp.426-435, 2015. ,

Real-time remaining useful life prediction for a nonlinear degrading system in service: Application to bearing data, IEEE/ASME Trans ,

, , vol.23, pp.211-222, 2017.

Degradation data-driven timeto-failure prognostics approach for rolling element bearings in electrical machines, IEEE Trans. Ind. Electron, vol.66, issue.1, pp.529-539, 2018. ,

Remaining Useful Life Prediction Using a Novel Two-Stage Wiener Process With Stage Correlation, IEEE Access, vol.6, pp.65227-65238, 2018. ,

A data-driven failure prognostics method based on mixture of Gaussians hidden Markov models, IEEE Trans. Reliab, vol.61, issue.2, pp.491-503, 2012. ,

URL : https://hal.archives-ouvertes.fr/hal-00737585

Remaining useful life estimation of critical components with application to bearings, IEEE Trans. Reliab, vol.61, issue.2, pp.292-302, 2012. ,

URL : https://hal.archives-ouvertes.fr/hal-00737596

An integrated approach to bearing fault diagnostics and prognostics, Proceedings of the 2005, pp.2750-2755, 2005. ,

Multi-branch hidden semi-markov modeling for rul prognosis, 2015 Annual Reliability and Maintainability Symposium (RAMS), pp.1-6, 2015. ,

URL : https://hal.archives-ouvertes.fr/hal-01084379

Extended Kalman filtering for remaining-useful-life estimation of bearings, IEEE Trans. Ind. Electron, vol.62, issue.3, pp.1781-1790, 2014. ,

An integrated Bayesian approach to prognositics of the remaining useful life and its application on bearing degradation problem, 2015 IEEE 13th International Conference on Industrial Informatics (INDIN), pp.1090-1095, 2015. ,

Equipment remaining useful life prediction oriented symbiotic simulation driven by real-time degradation data, Int. J. Model. Simulation, Sci. Comput, vol.9, issue.02, p.1850009, 2018. ,

Anomaly detection and fault prognosis for bearings, IEEE Trans. Instrum. Meas, vol.65, issue.9, pp.2046-2054, 2016. ,

Diagnostics and prognostics using switching Kalman filters, Struct. Heal. Monit, vol.13, issue.3, pp.296-306, 2014. ,

A novel switching unscented Kalman filter method for remaining useful life prediction of rolling bearing, Measurement, vol.135, pp.678-684, 2019. ,

Remaining useful life prediction of rolling bearings using an enhanced particle filter, IEEE Trans. Instrum. Meas, vol.64, issue.10, pp.2696-2707, 2015. ,

Remaining useful life prediction of hybrid ceramic bearings using an integrated deep learning and particle filter approach, Appl. Sci, vol.7, issue.7, p.649, 2017. ,

New Particle Filter Based on GA for Equipment Remaining Useful Life Prediction, Sensors, vol.17, issue.4, p.696, 2017. ,

Identifying new prognostic features for remaining useful life prediction using particle filtering and neuro-fuzzy system predictor, 2015 IEEE 15th ,

, International Conference on Environment and Electrical Engineering (EEEIC), pp.1533-1538, 2015.

Prognostics and health management of bearings based on logarithmic linear recursive least-squares and recursive maximum likelihood estimation, IEEE Trans. Ind. Electron, vol.65, issue.2, pp.1549-1558, 2017. ,

1551. Remaining useful life prediction of rolling bearings by the particle filter method based on degradation rate tracking, J. Vibroengineering, vol.17, issue.2, 2015. ,

Remaining useful life estimation in rolling bearings utilizing data-driven probabilistic e-support vectors regression, IEEE Trans. Reliab, vol.62, issue.4, pp.821-832, 2013. ,

Bearing health monitoring based on Hilbert-Huang transform, support vector machine, and regression, IEEE Trans. Instrum. Meas, vol.64, issue.1, pp.52-62, 2014. ,

URL : https://hal.archives-ouvertes.fr/hal-01026491

Remaining useful life estimation based on nonlinear feature reduction and support vector regression ,

, Appl. Artif. Intell, vol.26, issue.7, pp.1751-1760, 2013.

Condition based maintenance in railway transportation systems based on big data streaming analysis, Procedia Comput. Sci, vol.53, pp.437-446, 2015. ,

Remaining useful life prediction of rolling element bearings based on health state assessment, Proc. Inst. Mech. Eng. Part C J. Mech. Eng. Sci, vol.230, issue.2, pp.314-330, 2016. ,

A hybrid LSSVR/HMM-based prognostic approach, Sensors, vol.13, issue.5, pp.5542-5560, 2013. ,

Intelligent bearing performance degradation assessment and remaining useful life prediction based on self-organising map and support vector regression, Proc. Inst. Mech. Eng. Part C J. Mech. Eng. Sci, vol.232, issue.6, pp.1118-1132, 2018. ,

An integrated approach to bearing prognostics based on EEMD-multi feature extraction, Gaussian mixture models and Jensen-Rényi divergence, Appl. Soft Comput, vol.71, pp.36-50, 2018. ,

Remaining Useful Life Prediction of Wind Turbine Generator Bearing Based on EMD with an Indicator, 2018 Prognostics and System Health Management Conference (PHM-Chongqing), pp.375-379, 2018. ,

The nature of statistical learning theory, 1995. ,

Neural networks: a comprehensive foundation, 1994. ,

Residual life predictions for ball bearings based on self-organizing map and back propagation neural network methods, Mech. Syst. Signal Process, vol.21, issue.1, pp.193-207, 2007. ,

A recurrent neural network based health indicator for remaining useful life prediction of bearings, Neurocomputing, vol.240, pp.98-109, 2017. ,

An artificial neural network method for remaining useful life prediction of equipment subject to condition monitoring, J. Intell. Manuf, vol.23, issue.2, pp.227-237, 2012. ,

Predicting remaining useful life of rotating machinery based artificial neural network, Comput. Math. with Appl, vol.60, issue.4, pp.1078-1087, 2010. ,

Multi-bearing remaining useful life collaborative prediction: A deep learning approach, J. Manuf. Syst, vol.43, pp.248-256, 2017. ,

Prediction of bearing remaining useful life with deep convolution neural network, IEEE Access, vol.6, pp.13041-13049, 2018. ,

The use of MD-CUMSUM and NARX neural network for anticipating the remaining useful life of bearings, Measurement, vol.111, pp.397-410, 2017. ,

Bearing performance degradation assessment using long short-term memory recurrent network, Comput. Ind, vol.106, pp.14-29, 2019. ,

Rolling element bearing remaining useful life estimation based on a convolutional long-short-term memory network, Procedia Comput. Sci, vol.127, pp.123-132, 2018. ,

Estimation of bearing remaining useful life based on multiscale convolutional neural network, IEEE Trans. Ind. Electron, vol.66, issue.4, pp.3208-3216, 2018. ,

Estimating the remaining useful life of bearings using a neuro-local linear estimator-based method, J. Acoust. Soc. Am, vol.141, issue.5, pp.452-457, 2017. ,

An artificial neural network approach for remaining useful life prediction of equipments subject to condition monitoring, 2009 8th International Conference on Reliability, Maintainability and Safety, pp.143-148, 2009. ,

A novel approach for bearing remaining useful life estimation under neither failure nor suspension histories condition, J. Intell. Manuf, vol.28, issue.8, pp.1893-1914, 2017. ,

Pairwise comparison learning based bearing health quantitative modeling and its application in service life prediction, Futur. Gener. Comput. Syst, 2019. ,

Predicting remaining useful life of rolling bearings based on deep feature representation and long short-term memory neural network, Adv. Mech. Eng, vol.10, issue.12, p.1687814018817184, 2018. ,

Towards bearing health prognosis using generative adversarial networks: Modeling bearing degradation, 2018 International Conference on Advancements in Computational Sciences (ICACS), pp.1-6, 2018. ,

Autoencoders and Recurrent Neural Networks Based Algorithm for Prognosis of Bearing Life, 2018 21st International Conference on Electrical Machines and Systems (ICEMS), pp.537-542, 2018. ,

A neural network approach for prediction of bearing performance degradation tendency, 2017 9th International Conference on Modelling, Identification and Control (ICMIC, pp.204-208, 2017. ,

Condition monitoring and fault diagnosis of electrical motors-A review, IEEE Trans. energy Convers, vol.20, issue.4, pp.719-729, 2005. ,

Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network, Mech. Syst. Signal Process, vol.56, pp.150-172, 2015. ,

URL : https://hal.archives-ouvertes.fr/hal-01566122

A fuzzy BP approach for diagnosis and prognosis of bearing faults in induction motors, IEEE Power Engineering Society General Meeting, pp.2291-2294, 2005. ,

Predicting the remaining useful life of rolling element bearings using locally linear fusion regression, J. Intell. Fuzzy Syst, pp.1-12, 2018. ,

Remaining Useful Life Prediction of Bearings Using Fuzzy Multimodal Extreme Learning Regression, 2017 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC, pp.499-503, 2017. ,

Distributed neuro-fuzzy feature forecasting approach for condition monitoring, Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA), pp.1-8, 2014. ,

, Methods of multivariate analysis, vol.492, 2003.

Segmenting time series: A survey and novel approach, Data mining in time series databases, pp.1-21, 2004. ,

Research on condition monitoring of bearing health using vibration data, Applied Mechanics and Materials, 2012, vol.226, pp.340-344 ,

Constructing fuzzy models by product space clustering, Fuzzy model identification, pp.53-90, 1997. ,

An introductory survey of fuzzy control, Inf. Sci. (Ny), vol.36, issue.1-2, pp.59-83, 1985. ,

Remaining Useful Life Estimation for Bearings Based on Segmented Projection Error and Fuzzy Inference System, The 6th International Conference on Mechanical Engineering & Mechanics, 2017. ,

Bearings Degradation Monitoring Indicator Based on Segmented Hotelling T Square and Piecewise Linear Representation, 2018 IEEE International Conference on Mechatronics and Automation (ICMA), pp.1389-1394, 2018. ,

Data Piecewise Linear Approximation for Bearings Degradation Monitoring, The 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, pp.60-64, 2019. ,

Ensemble-index: A new approach to indexing large databases, Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, pp.117-125, 2001. ,

Similarity-based queries for time series data, ACM SIGMOD Record, vol.26, pp.13-25, 1997. ,

Similarity search over time-series data using wavelets, Proceedings 18th international conference on data engineering, pp.212-221, 2002. ,

Tsa-tree: A wavelet-based approach to improve the efficiency of multi-level surprise and trend queries on time-series data, Proceedings. 12th International Conference on Scientific and Statistica Database Management, pp.55-68, 2000. ,

A similarity search method of time series data with combination of fourier and wavelet transforms, Proceedings Ninth International Symposium on Temporal Representation and Reasoning, pp.86-92, 2002. ,

On the choice of sampling rates in parametric identification of time series, Inf. Sci. (Ny), vol.1, issue.3, pp.273-278, 1969. ,

Fast time sequence indexing for arbitrary Lp norms, VLDB, vol.385, p.99, 2000. ,

Dimensionality reduction for fast similarity search in large time series databases, Knowl. Inf. Syst, vol.3, issue.3, pp.263-286, 2001. ,

Dimensionality reduction for indexing time series based on the minimum distance, J. Inf. Sci. Eng, vol.19, issue.4, pp.697-711, 2003. ,

Locally adaptive dimensionality reduction for indexing large time series databases, ACM Sigmod Rec, vol.30, issue.2, pp.151-162, 2001. ,

Approximate queries and representations for large data sequences, Proceedings of the Twelfth International Conference on Data Engineering, pp.536-545, 1996. ,

An Enhanced Representation of Time Series Which Allows Fast and Accurate Classification, Clustering and Relevance Feedback, Kdd, vol.98, pp.239-243, 1998. ,

Fast retrieval of similar subsequences in long sequence databases, Proceedings 1999 Workshop on Knowledge and Data Engineering Exchange (KDEX'99)(Cat. No. PR00453), pp.60-67, 1999. ,

Knowledge-based event detection in complex time series data, Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making, pp.271-280, 1999. ,

A probabilistic approach to fast pattern matching in time series databases, Kdd, vol.1997, pp.24-30, 1997. ,

Scan-along polygonal approximation for data compression of electrocardiograms, IEEE Trans. Biomed. Eng, issue.11, pp.723-729, 1983. ,

ECG segmentation using time-warping, International Symposium on Intelligent Data Analysis, pp.275-285, 1997. ,

Event detection from time series data, Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, pp.33-42, 1999. ,

Multivariate SPC charts for monitoring batch processes, Technometrics, vol.37, issue.1, pp.41-59, 1995. ,

Nonlinear principal component analysis using autoassociative neural networks, AIChE J, vol.37, issue.2, pp.233-243, 1991. ,

On-line batch process monitoring using dynamic PCA and dynamic PLS models, Chem. Eng. Sci, vol.57, issue.1, pp.63-75, 2002. ,

Adaptive batch monitoring using hierarchical PCA, Chemom. Intell. Lab. Syst, vol.41, issue.1, pp.73-81, 1998. ,

Selection of the number of principal components: the variance of the reconstruction error criterion with a comparison to other methods ,

, Chem. Res, vol.38, issue.11, pp.4389-4401, 1999.

Analysis of a complex of statistical variables into principal components, J. Educ. Psychol, vol.24, issue.6, p.417, 1933. ,

The mahalanobis distance, Chemom. Intell. Lab. Syst, vol.50, issue.1, pp.1-18, 2000. ,

An online algorithm for segmenting time series, ICDM 2001, Proceedings IEEE International Conference on Data Mining, pp.289-296, 2001. ,

Algorithm AS 89: the upper tail probabilities of Spearman's rho, J. R. Stat. Soc. Ser. C (Applied Stat, vol.24, issue.3, pp.377-379, 1975. ,

Membership functions and probability measures of fuzzy sets, J. Am. Stat. Assoc, vol.99, issue.467, pp.867-877, 2004. ,

Fuzzy sets, Inf. Control, vol.8, issue.3, pp.338-353, 1965. ,

Designing fuzzy inference systems from data: An interpretabilityoriented review, IEEE Trans. fuzzy Syst, vol.9, issue.3, pp.426-443, 2001. ,

URL : https://hal.archives-ouvertes.fr/hal-01320328

An experiment in linguistic synthesis with a fuzzy logic controller, Int. J. Man. Mach. Stud, vol.7, issue.1, pp.1-13, 1975. ,

Multiple model approaches to nonlinear modelling and control, 1997. ,

Fuzzy identification of systems and its applications to modeling and control, IEEE Trans. Syst. Man. Cybern, issue.1, pp.116-132, 1985. ,

Data clustering: a review, ACM Comput. Surv, vol.31, issue.3, pp.264-323, 1999. ,

A Comparison Study between Various Fuzzy Clustering Algorithms, Jordan J. Mech. Ind. Eng, vol.5, issue.4, 2011. ,

A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters, 1973. ,

Pattern recognition with fuzzy objective function algorithms, 2013. ,

Generation of fuzzy rules by mountain clustering, J. Intell. Fuzzy Syst, vol.2, issue.3, pp.209-219, 1994. ,

Fuzzy model identification based on cluster estimation, J. Intell. fuzzy Syst, vol.2, issue.3, pp.267-278, 1994. ,

Pattern clustering by multivariate mixture analysis, Multivariate Behav. Res, vol.5, issue.3, pp.329-350, 1970. ,

ANFIS: adaptive-network-based fuzzy inference system, IEEE Trans. Syst. Man. Cybern, vol.23, issue.3, pp.665-685, 1993. ,

The Moore-Penrose Inverse and Least Squares, pp.1-10, 2014. ,

Effects of sample size on the performance of species distribution models, Divers. Distrib, vol.14, issue.5, pp.763-773, 2008. ,

Approximate solution of systems of linear equations, Int. J. Control, vol.57, issue.6, pp.1269-1271, 1993. ,

Cluster validity measurement techniques, 6th International symposium of hungarian researchers on computational intelligence, p.35, 2005. ,

Well-separated clusters and optimal fuzzy partitions, J. Cybern, vol.4, issue.1, pp.95-104, 1974. ,

Application of fuzzy ISODATA algorithms to star tracker pointing systems, IFAC Proc, vol.11, issue.1, pp.1319-1323, 1978. ,

Cluster validity for fuzzy clustering algorithms, Fuzzy Sets Syst, vol.5, issue.2, pp.177-185, 1981. ,

Numerical taxonomy with fuzzy sets, J. Math. Biol, vol.1, issue.1, pp.57-71, 1974. ,

A validity measure for fuzzy clustering, IEEE Trans. Pattern Anal. Mach. Intell, issue.8, pp.841-847, 1991. ,

Unsupervised optimal fuzzy clustering, IEEE Trans. Pattern Anal. Mach. Intell, issue.7, pp.773-780, 1989. ,

Validity-guided (re)clustering with applications to image segmentation, IEEE Trans. Fuzzy Syst, vol.4, issue.2, pp.112-123, 2002. ,

A New Fuzzy Set Merging Technique Using Inclusion-Based Fuzzy Clustering, IEEE Trans. Fuzzy Syst, vol.16, issue.1, pp.145-161, 2008. ,

eFSLab: Developing evolving fuzzy systems from data in a friendly environment, European Control Conference, pp.922-927, 2009. ,

Advanced statistical methods in biometric research, 1952. ,

Accelerated projection methods for computing pseudoinverse solutions of systems of linear equations, BIT Numer. Math, vol.57, issue.6, pp.1269-1271, 1979. ,

PRONOSTIA: An experimental platform for bearings accelerated degradation tests, IEEE International Conference on Prognostics and Health Management, PHM'12, pp.1-8, 2012. ,

URL : https://hal.archives-ouvertes.fr/hal-00719503

Fuzzy model identification: selected approaches, 2012. ,

Genetic algorithms in search, Optim. Mach, 1989. ,

Optimization by simulated annealing, vol.220, pp.671-680, 1983. ,

Spectral entropy: a complementary index for rolling element bearing performance degradation assessment, Proc. Inst. Mech. Eng. Part C J. Mech. Eng. Sci, vol.223, issue.5, pp.1223-1231, 2009. ,

Approximate entropy as a diagnostic tool for machine health monitoring, Mech. Syst. Signal Process, vol.21, issue.2, pp.824-839, 2007. ,

Application of the largest Lyapunov exponent algorithm for feature extraction in low speed slew bearing condition monitoring, Mech. Syst. Signal Process, vol.50, pp.116-138, 2015. ,

Using the correlation dimension for vibration fault diagnosis of rolling element bearings-I. Basic concepts, Mech. Syst. Signal Process, vol.10, issue.3, pp.241-250, 1996. ,

A review of feature extraction methods in vibration-based condition monitoring and its application for degradation trend estimation of low-speed slew bearing, Machines, vol.5, issue.4, p.21, 2017. ,