A probabilistic Bayesian recurrent neural network for remaining useful life prognostics considering epistemic and aleatory uncertainties

Digital modeling on the nonlinear mapping between multi‐source monitoring data of in‐service bridges

(2020) Hanwei Zhao et al.   Structural Control & Health Monitoring

An acoustic emission based structural health monitoring approach to damage development in solid railway axles

(2020) Michele Carboni et al.   INTERNATIONAL JOURNAL OF FATIGUE

An approach to decision‐making analysis for implementation of structural health monitoring in bridges

(2019) Ana C. Neves et al.   Structural Control & Health Monitoring

Deep semi-supervised generative adversarial fault diagnostics of rolling element bearings

(2019) David Benjamin Verstraete et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Data-driven remaining useful life prediction via multiple sensor signals and deep long short-term memory neural network

(2019) Jun Wu et al.   ISA TRANSACTIONS

Bayesian Deep-Learning-Based Health Prognostics Toward Prognostics Uncertainty

(2019) Weiwen Peng et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Assessment of Deep Learning techniques for Prognosis of solar thermal systems

(2019) Camila Correa-Jullian et al.   RENEWABLE ENERGY

Gear pitting severity level identification using binary segmentation methodology

(2019) Pradeep Kundu et al.   Structural Control & Health Monitoring

Long short-term memory recurrent neural network for remaining useful life prediction of lithium-ion batteries

(2018) Yongzhi Zhang et al.   IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY

Machinery health prognostics: A systematic review from data acquisition to RUL prediction

(2018) Yaguo Lei et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Remaining useful life estimation in prognostics using deep convolution neural networks

(2018) Xiang Li et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Convolutional neural networks for automated damage recognition and damage type identification

(2018) Ceena Modarres et al.   Structural Control & Health Monitoring

Deep learning and its applications to machine health monitoring

(2018) Rui Zhao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Statistical Modeling of Bearing Degradation Signals

(2017) Dong Wang et al.   IEEE TRANSACTIONS ON RELIABILITY

Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data

(2016) Feng Jia et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

The Emerging Internet of Things Marketplace From an Industrial Perspective: A Survey

(2015) Charith Perera et al.   IEEE Transactions on Emerging Topics in Computing

Condition monitoring and fault diagnosis of planetary gearboxes: A review

(2013) Yaguo Lei et al.   MEASUREMENT

A review on prognostics and health monitoring of Li-ion battery

(2011) Jingliang Zhang et al.   JOURNAL OF POWER SOURCES

Bayesian methodology for diagnosis uncertainty quantification and health monitoring

(2011) Shankar Sankararaman et al.   Structural Control & Health Monitoring

Rolling element bearing diagnostics—A tutorial

(2010) Robert B. Randall et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Bayesian neural networks for bridge integrity assessment

(2010) S. Arangio et al.   Structural Control & Health Monitoring

Prognostics in Battery Health Management

(2008) Kai Goebel et al.   IEEE INSTRUMENTATION & MEASUREMENT MAGAZINE

Incorporating organizational factors into Probabilistic Risk Assessment (PRA) of complex socio-technical systems: A hybrid technique formalization

(2008) Zahra Mohaghegh et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Bayesian Methodology for Model Uncertainty Using Model Performance Data

(2008) Enrique López Droguett et al.   RISK ANALYSIS

Aleatory or epistemic? Does it matter?

(2008) Armen Der Kiureghian et al.   STRUCTURAL SAFETY