| 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 | 1968 | 2008 |
| Prognostics methods for battery health monitoring using a Bayesian framework B Saha, K Goebel, S Poll, J Christophersen IEEE Transactions on instrumentation and measurement 58 (2), 291-296, 2008 | 952 | 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 | 700 | 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 | 675 | 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 | 572 | 2010 |
| Comparison of prognostic algorithms for estimating remaining useful life of batteries B Saha, K Goebel, J Christophersen Transactions of the Institute of Measurement and Control 31 (3-4), 293-308, 2009 | 530 | 2009 |
| Turbofan engine degradation simulation data set A Saxena, K Goebel NASA ames prognostics data repository 18, 878-887, 2008 | 480 | 2008 |
| Modeling Li-ion battery capacity depletion in a particle filtering framework B Saha, K Goebel Annual Conference of the PHM Society 1 (1), 2009 | 471 | 2009 |
| A Survey of Artificial Intelligence for Prognostics. M Schwabacher, K Goebel AAAI fall symposium: artificial intelligence for prognostics, 108-115, 2007 | 396 | 2007 |
| Fusing physics-based and deep learning models for prognostics MA Chao, C Kulkarni, K Goebel, O Fink Reliability Engineering & System Safety 217, 107961, 2022 | 331 | 2022 |
| 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 Prognostics and Health Management Society, 2010 | 317 | 2010 |
| Precursor parameter identification for insulated gate bipolar transistor (IGBT) prognostics N Patil, J Celaya, D Das, K Goebel, M Pecht IEEE Transactions on Reliability 58 (2), 271-276, 2009 | 281 | 2009 |
| An Integrated Approach to Battery Health Monitoring using Bayesian Regression, Classification and State Estimation B Saha, S Poll, K Goebel, J Christophersen Proceedings of IEEE Autotestcon, 2007 | 265 | 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 | 245 | 2009 |
| A diagnostic approach for electro-mechanical actuators in aerospace systems E Balaban, P Bansal, P Stoelting, A Saxena, KF Goebel, S Curran Aerospace conference, 2009 IEEE, 1-13, 2009 | 239 | 2009 |
| A comparison of three data-driven techniques for prognostics K Goebel, B Saha, A Saxena, N Mct, N Riacs 62nd meeting of the society for machinery failure prevention technology …, 2008 | 239 | 2008 |
| Uncertainty management for diagnostics and prognostics of batteries using Bayesian techniques B Saha, K Goebel 2008 IEEE aerospace conference, 1-8, 2008 | 230 | 2008 |
| 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 | 229 | 2009 |
| Aircraft engine run-to-failure dataset under real flight conditions for prognostics and diagnostics M Arias Chao, C Kulkarni, K Goebel, O Fink Data 6 (1), 5, 2021 | 220 | 2021 |
| Hybrid soft computing systems: Industrial and commercial applications PP Bonissone, YT Chen, K Goebel, PS Khedkar Proceedings of the IEEE 87 (9), 1641-1667, 1999 | 215 | 1999 |
Abhinav SaxenaGE Aerospace Researchge.com의 이메일 확인됨