A semi-supervised GAN method for RUL prediction using failure and suspension histories

Potential, challenges and future directions for deep learning in prognostics and health management applications

(2020) Olga Fink et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Generalizing semi-supervised generative adversarial networks to regression using feature contrasting

(2019) Greg Olmschenk et al.   COMPUTER VISION AND IMAGE UNDERSTANDING

A Comprehensive Survey of Prognostics and Health Management Based on Deep Learning for Autonomous Ships

(2019) Andre Listou Ellefsen et al.   IEEE TRANSACTIONS ON RELIABILITY

Prediction of remaining useful life by data augmentation technique based on dynamic time warping

(2019) Seokgoo Kim et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Semi-supervised regression: A recent review

(2018) Georgios Kostopoulos et al.   JOURNAL OF INTELLIGENT & FUZZY SYSTEMS

A review on the application of deep learning in system health management

(2018) Samir Khan et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

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

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

Deep learning and its applications to machine health monitoring

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

Remaining useful life predictions for turbofan engine degradation using semi-supervised deep architecture

(2018) André Listou Ellefsen et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element Bearings

(2018) Biao Wang et al.   IEEE TRANSACTIONS ON RELIABILITY

Multistream sensor fusion-based prognostics model for systems with single failure modes

(2017) Xiaolei Fang et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

A novel approach for bearing remaining useful life estimation under neither failure nor suspension histories condition

(2015) Lei Xiao et al.   JOURNAL OF INTELLIGENT MANUFACTURING

A co-training-based approach for prediction of remaining useful life utilizing both failure and suspension data

(2015) Chao Hu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Significance, interpretation, and quantification of uncertainty in prognostics and remaining useful life prediction

(2015) Shankar Sankararaman   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A Framework of Similarity-Based Residual Life Prediction Approaches Using Degradation Histories With Failure, Preventive Maintenance, and Suspension Events

(2013) Ming-Yi You et al.   IEEE TRANSACTIONS ON RELIABILITY

An intelligent approach to machine component health prognostics by utilizing only truncated histories

(2013) Chen Lu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Modified Weibull model: A Bayes study using MCMC approach based on progressive censoring data

(2012) Ahmed A. Soliman et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

A case study for quantifying system reliability and uncertainty

(2011) Alyson G. Wilson et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

A neural network approach for remaining useful life prediction utilizing both failure and suspension histories

(2009) Zhigang Tian et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Rotating machinery prognostics: State of the art, challenges and opportunities

(2008) Aiwina Heng et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING