Yang Hu
Title
Cited by
Cited by
Year
A particle filtering and kernel smoothing-based approach for new design component prognostics
Y Hu, P Baraldi, F Di Maio, E Zio
Reliability Engineering & System Safety 134, 19-31, 2015
1022015
Online Performance Assessment Method for a Model-Based Prognostic Approach
Y Hu, P Baraldi, F Di Maio, E Zio
IEEE Transactions on Reliability 65 (2), 718-735, 2016
382016
Deep diagnostics and prognostics: An integrated hierarchical learning framework in PHM applications
Y Lin, X Li, Y Hu
Applied Soft Computing 72, 555-564, 2018
282018
A Systematic Semi-Supervised Self-adaptable Fault Diagnostics approach in an evolving environment
Y Hu, P Baraldi, F Di Maio, E Zio
Mechanical Systems and Signal Processing 88, 413-427, 2017
272017
Feature learning for fault detection in high-dimensional condition monitoring signals
G Michau, Y Hu, T Palmé, O Fink
Proceedings of the Institution of Mechanical Engineers, Part O: Journal of …, 2020
262020
Predicting railway wheel wear under uncertainty of wear coefficient, using universal kriging
MA Cremona, B Liu, Y Hu, S Bruni, R Lewis
Reliability Engineering & System Safety 154, 49-59, 2016
262016
Fault detection based on signal reconstruction with auto-associative extreme learning machines
Y Hu, T Palmé, O Fink
Engineering applications of artificial intelligence 57, 105-117, 2017
242017
Fault diagnostics between different type of components: A transfer learning approach
X Li, Y Hu, M Li, J Zheng
Applied Soft Computing 86, 105950, 2020
222020
System risk evolution analysis and risk critical event identification based on event sequence diagram
P Luo, Y Hu
Reliability Engineering & System Safety 114, 36-44, 2013
132013
Deep health indicator extraction: A method based on auto-encoders and extreme learning machines
Y Hu, T Palmé, O Fink
PHM 2016, Denver, USA, 3-6 October 2016, 446-452, 2016
102016
Performance data prognostics based on relevance vector machine and particle filter
Y Hu, P Luob
Chemical Engineering 33, 349-354, 2013
62013
Online sequential extreme learning machines for fault detection
Y Hu, O Fink, T Palmé
2016 IEEE International Conference on Prognostics and Health Management …, 2016
52016
A prognostic approach based on particle filtering and optimized tuning kernel smoothing
Y Hu, P Baraldi, F Di Maio, E Zio
Proc. 2nd Eur. Conf. Prognostics Health Manage. Soc, 2014
52014
A SVM-based framework for fault detection in high-speed trains
J Liu, Y Hu, S Yang
Measurement 172, 108779, 2021
32021
A Compacted Object Sample Extraction (COMPOSE)-based method for fault diagnostics in evolving environment
Y Hu, P Baraldi, F Di Maio, E Zio
2015 Prognostics and System Health Management Conference (PHM), 1-5, 2015
32015
Neural architecture search for fault diagnosis
X Li, Y Hu, J Zheng, M Li
arXiv preprint arXiv:2002.07997, 2020
22020
Particle filtering for prognostics of a newly designed product with a new parameters initialization strategy based on reliability test data
J Liu, E Zio, Y Hu
IEEE Access 6, 62564-62573, 2018
22018
Dynamic Mode Transfer Scheduling for Degrading Standby System Considering Load-Sharing Characteristic
YH Lin, SJ Ruan, F Tao, Y Hu
IEEE Systems Journal, 2020
12020
Issues and tips: a set of integrated experiments of applying auto-encoder and convolutional neural network in feature extraction and fault diagnosis
X Li, M Li, J Zheng, Y Hu
2018 Prognostics and System Health Management Conference (PHM-Chongqing …, 2018
12018
Development of prognostics and health management methods for engineering systems operating in evolving environments
Y Hu
Italy, 2015
12015
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