Damage propagation modeling for aircraft engine run-to-failure simulation A Saxena, K Goebel, D Simon, N Eklund 2008 international conference on prognostics and health management, 1-9, 2008 | 1712 | 2008 |
Prognostics in battery health management K Goebel, B Saha, A Saxena, JR Celaya, JP Christophersen IEEE instrumentation & measurement magazine 11 (4), 33-40, 2008 | 653 | 2008 |
Metrics for evaluating performance of prognostic techniques A Saxena, J Celaya, E Balaban, K Goebel, B Saha, S Saha, ... 2008 international conference on prognostics and health management, 1-17, 2008 | 643 | 2008 |
Metrics for offline evaluation of prognostic performance A Saxena, J Celaya, B Saha, S Saha, K Goebel International Journal of Prognostics and Health Management 1 (1), 20, 2010 | 549 | 2010 |
Turbofan engine degradation simulation data set A Saxena, K Goebel NASA ames prognostics data repository 18, 878-887, 2008 | 435 | 2008 |
An adaptive recurrent neural network for remaining useful life prediction of lithium-ion batteries J Liu, A Saxena, K Goebel, B Saha, W Wang Annual Conference of the PHM Society 2 (1), 2010 | 291 | 2010 |
Evolving an artificial neural network classifier for condition monitoring of rotating mechanical systems A Saxena, A Saad Applied Soft Computing 7 (1), 441-454, 2007 | 270 | 2007 |
Modeling, detection, and disambiguation of sensor faults for aerospace applications E Balaban, A Saxena, P Bansal, KF Goebel, S Curran IEEE Sensors Journal 9 (12), 1907-1917, 2009 | 232 | 2009 |
A comparison of three data-driven techniques for prognostics K Goebel, B Saha, A Saxena 62nd Meeting of the Society For Machinery Failure Prevention Technology …, 2008 | 232 | 2008 |
A diagnostic approach for electro-mechanical actuators in aerospace systems E Balaban, P Bansal, P Stoelting, A Saxena, KF Goebel, S Curran 2009 IEEE Aerospace conference, 1-13, 2009 | 225 | 2009 |
On applying the prognostic performance metrics A Saxena, J Celaya, B Saha, S Saha, K Goebel Annual Conference of the PHM Society 1 (1), 2009 | 222 | 2009 |
Performance Benchmarking and Analysis of Prognostic Methods for CMAPSS Datasets E Ramasso, A Saxena International Journal of Prognostics and Health Management 5 (2), 15, 2014 | 203 | 2014 |
Evaluating algorithm performance metrics tailored for prognostics A Saxena, J Celaya, B Saha, S Saha, K Goebel 2009 IEEE Aerospace conference, 1-13, 2009 | 163 | 2009 |
In-situ fatigue life prognosis for composite laminates based on stiffness degradation T Peng, Y Liu, A Saxena, K Goebel Composite Structures 132, 155-165, 2015 | 130 | 2015 |
Prognostics of power MOSFETs under thermal stress accelerated aging using data-driven and model-based methodologies JR Celaya, A Saxena, S Saha, KF Goebel Annual Conference of the PHM Society 3 (1), 2011 | 130 | 2011 |
Prognostics approach for power MOSFET under thermal-stress aging JR Celaya, A Saxena, CS Kulkarni, S Saha, K Goebel 2012 Proceedings Annual Reliability and Maintainability Symposium, 1-6, 2012 | 115 | 2012 |
Prognostics: The science of making predictions K Goebel, MJ Daigle, A Saxena, I Roychoudhury, S Sankararaman, ... | 114 | 2017 |
Phm08 challenge data set A Saxena, K Goebel NASA Ames Prognostics Data Repository, 2008 | 113 | 2008 |
Towards prognostics of power MOSFETs: Accelerated aging and precursors of failure JR Celaya, A Saxena, P Wysocki, S Saha, K Goebel Annual Conference of the PHM Society 2 (1), 2010 | 109 | 2010 |
A multi-feature integration method for fatigue crack detection and crack length estimation in riveted lap joints using Lamb waves J He, X Guan, T Peng, Y Liu, A Saxena, J Celaya, K Goebel Smart Materials and Structures 22 (10), 105007, 2013 | 106 | 2013 |