Related references
Note: Only part of the references are listed.Deep Learning for HDD Health Assessment: An Application Based on LSTM
Aniello De Santo et al.
IEEE TRANSACTIONS ON COMPUTERS (2022)
An automated health indicator construction methodology for prognostics based on multi-criteria optimization
Khanh T. P. Nguyen et al.
ISA TRANSACTIONS (2021)
A flexible alarm prediction system for smart manufacturing scenarios following a forecaster-analyzer approach
Kevin Villalobos et al.
JOURNAL OF INTELLIGENT MANUFACTURING (2021)
A generalized remaining useful life prediction method for complex systems based on composite health indicator
Pengfei Wen et al.
RELIABILITY ENGINEERING & SYSTEM SAFETY (2021)
Multi-sensor edge computing architecture for identification of failures short-circuits in wind turbine generators
Yongzhao Xu et al.
APPLIED SOFT COMPUTING (2021)
Predictive Maintenance and Intelligent Sensors in Smart Factory: Review
Martin Pech et al.
SENSORS (2021)
Automatic Feature Extraction and Construction Using Genetic Programming for Rotating Machinery Fault Diagnosis
Bo Peng et al.
IEEE TRANSACTIONS ON CYBERNETICS (2021)
Incremental novelty detection and fault identification scheme applied to a kinematic chain under non-stationary operation
J. A. Carino et al.
ISA TRANSACTIONS (2020)
Stakeholder-oriented systematic design methodology for prognostic and health management system: Stakeholder expectation definition
Rui Li et al.
ADVANCED ENGINEERING INFORMATICS (2020)
A systematic methodology for Prognostic and Health Management system architecture definition
Rui Li et al.
RELIABILITY ENGINEERING & SYSTEM SAFETY (2020)
Anomaly monitoring improves remaining useful life estimation of industrial machinery
Gurkan Aydemir et al.
JOURNAL OF MANUFACTURING SYSTEMS (2020)
Pattern recognition method of fault diagnostics based on a new health indicator for smart manufacturing
Moncef Soualhi et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2020)
Complex engineered system health indexes extraction using low frequency raw time-series data based on deep learning methods
Cui Liu et al.
MEASUREMENT (2020)
Machine Learning in Predictive Maintenance towards Sustainable Smart Manufacturing in Industry 4.0
Zeki Murat Cinar et al.
SUSTAINABILITY (2020)
A Methodology and Experimental Implementation for Industrial Robot Health Assessment via Torque Signature Analysis
Unai Izagirre et al.
APPLIED SCIENCES-BASEL (2020)
Edge Computing: A Promising Framework for Real-Time Fault Diagnosis and Dynamic Control of Rotating Machines Using Multi-Sensor Data
Gang Qian et al.
IEEE SENSORS JOURNAL (2019)
A deep belief network based health indicator construction and remaining useful life prediction using improved particle filter
Kaixiang Peng et al.
NEUROCOMPUTING (2019)
Machine learning for multi-criteria inventory classification applied to intermittent demand
F. Lolli et al.
PRODUCTION PLANNING & CONTROL (2019)
An integrated wind turbine failures prognostic approach implementing Kalman smoother with confidence bounds
Lotfi Saidi et al.
APPLIED ACOUSTICS (2018)
Evolving model identification for process monitoring and prediction of non-linear systems
Goran Andonovski et al.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2018)
A method for autonomous data partitioning
Xiaowei Gu et al.
INFORMATION SCIENCES (2018)
Cloud-Based Parallel Machine Learning for Tool Wear Prediction
Dazhong Wu et al.
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME (2018)
Machine health management in smart factory: A review
Gil-Yong Lee et al.
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY (2018)
Artificial intelligence for fault diagnosis of rotating machinery: A review
Ruonan Liu et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2018)
A review on the application of deep learning in system health management
Samir Khan et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2018)
Machinery health prognostics: A systematic review from data acquisition to RUL prediction
Yaguo Lei et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2018)
Prognostics and Health Management: A Review of Vibration Based Bearing and Gear Health Indicators
Dong Wang et al.
IEEE ACCESS (2018)
Fault Detection and Identification Methodology Under an Incremental Learning Framework Applied to Industrial Machinery
Jesus A. Carino et al.
IEEE ACCESS (2018)
A Survey of Machine Learning Techniques Applied to Self-Organizing Cellular Networks
Paulo Valente Klaine et al.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS (2017)
A novel intelligent method for bearing fault diagnosis based on affinity propagation clustering and adaptive feature selection
Zexian Wei et al.
KNOWLEDGE-BASED SYSTEMS (2017)
Unsupervised real-time anomaly detection for streaming data
Subutai Ahmad et al.
NEUROCOMPUTING (2017)
An unsupervised artificial neural network versus a rule-based approach for fault detection and identification in an automated assembly machine
Heshan Fernando et al.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING (2017)
Intelligent Diagnosis Method for Rotating Machinery Using Dictionary Learning and Singular Value Decomposition
Te Han et al.
SENSORS (2017)
Remaining Useful Life Prediction for Rotating Machinery Based on Optimal Degradation Indicator
Aisong Qin et al.
SHOCK AND VIBRATION (2017)
A novel fault diagnosis scheme applying fuzzy clustering algorithms
A. Rodriguez Ramos et al.
APPLIED SOFT COMPUTING (2017)
An evolving approach to unsupervised and Real-Time fault detection in industrial processes
Clauber Gomes Bezerra et al.
EXPERT SYSTEMS WITH APPLICATIONS (2016)
An Intelligent Fault Diagnosis Method Using Unsupervised Feature Learning Towards Mechanical Big Data
Yaguo Lei et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2016)
Prognostics: a literature review
Hatem M. Elattar et al.
COMPLEX & INTELLIGENT SYSTEMS (2016)
Bearing Fault Diagnosis Using Feature Ranking Methods and Fault Identification Algorithms
V. Vakharia et al.
INTERNATIONAL CONFERENCE ON VIBRATION PROBLEMS 2015 (2016)
Comparison between Artificial Neural Network and Support Vector Method for a Fault Diagnostics in Rolling Element Bearings
J. P. Patel et al.
INTERNATIONAL CONFERENCE ON VIBRATION PROBLEMS 2015 (2016)
Bearing Health Monitoring Based on Hilbert-Huang Transform, Support Vector Machine, and Regression
Abdenour Soualhi et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2015)
Fault Diagnosis with Evolving Fuzzy Classifier Based on Clustering Algorithm and Drift Detection
Maurilio Inacio et al.
MATHEMATICAL PROBLEMS IN ENGINEERING (2015)
Rolling bearing fault diagnosis using an optimization deep belief network
Haidong Shao et al.
MEASUREMENT SCIENCE AND TECHNOLOGY (2015)
Fully unsupervised fault detection and identification based on recursive density estimation and self-evolving cloud-based classifier
Bruno Sielly Jales Costa et al.
NEUROCOMPUTING (2015)
Multimodal deep support vector classification with homologous features and its application to gearbox fault diagnosis
Chuan Li et al.
NEUROCOMPUTING (2015)
Practical options for selecting data-driven or physics-based prognostics algorithms with reviews
Dawn An et al.
RELIABILITY ENGINEERING & SYSTEM SAFETY (2015)
Stochastic modelling and analysis of degradation for highly reliable products
Zhi-Sheng Ye et al.
APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY (2015)
Online data-driven anomaly detection in autonomous robots
Eliahu Khalastchi et al.
KNOWLEDGE AND INFORMATION SYSTEMS (2015)
A Feature Extraction Method for Fault Classification of Rolling Bearing based on PCA
Fengtao Wang et al.
11TH INTERNATIONAL CONFERENCE ON DAMAGE ASSESSMENT OF STRUCTURES (DAMAS 2015) (2015)
Review of Hybrid Prognostics Approaches for Remaining Useful Life Prediction of Engineered Systems, and an Application to Battery Life Prediction
Linxia Liao et al.
IEEE TRANSACTIONS ON RELIABILITY (2014)
COMPOSE: A Semisupervised Learning Framework for Initially Labeled Nonstationary Streaming Data
Karl B. Dyer et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2014)
Degradation Data Analysis Using Wiener Processes With Measurement Errors
Zhi-Sheng Ye et al.
IEEE TRANSACTIONS ON RELIABILITY (2013)
A Data-Driven Failure Prognostics Method Based on Mixture of Gaussians Hidden Markov Models
Diego Alejandro Tobon-Mejia et al.
IEEE TRANSACTIONS ON RELIABILITY (2012)
Remaining useful life estimation - A review on the statistical data driven approaches
Xiao-Sheng Si et al.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2011)
Adaptive feature extraction using sparse coding for machinery fault diagnosis
Haining Liu et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2011)
Prognostic modelling options for remaining useful life estimation by industry
J. Z. Sikorska et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2011)
Feature selection using Decision Tree and classification through Proximal Support Vector Machine for fault diagnostics of roller bearing
V. Sugumaran et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2007)
A review on machinery diagnostics and prognostics implementing condition-based maintenance
Andrew K. S. Jardine et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2006)
Artificial neural network based fault diagnostics of rolling element bearings using time-domain features
B Samanta et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2003)
Linking maintenance strategies to performance
L Swanson
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2001)