| Leak detection in gas distribution pipelines using acoustic impact monitoring P Karkulali, H Mishra, A Ukil, J Dauwels IECON 2016-42nd Annual Conference of the IEEE Industrial Electronics Society …, 2016 | 35 | 2016 |
| A holistic comparison of the different resampling algorithms for particle filter based prognosis using lithium ion batteries as a case study K Pugalenthi, N Raghavan Microelectronics Reliability 91, 160-169, 2018 | 32 | 2018 |
| Pressure and flow variation in gas distribution pipeline for leak detection RS Reddy, G Payal, P Karkulali, M Himanshu, A Ukil, J Dauwels 2016 IEEE International Conference on Industrial Technology (ICIT), 679-683, 2016 | 23 | 2016 |
| Prognosis of power MOSFET resistance degradation trend using artificial neural network approach K Pugalenthi, H Park, N Raghavan Microelectronics Reliability 100, 113467, 2019 | 20 | 2019 |
| Piecewise model-based online prognosis of lithium-ion batteries using particle filters K Pugalenthi, H Park, N Raghavan Ieee Access 8, 153508-153516, 2020 | 16 | 2020 |
| Online Prognosis of Bimodal Crack Evolution for Fatigue Life Prediction of Composite Laminates Using Particle Filters K Pugalenthi, PL Trung Duong, J Doh, S Hussain, MH Jhon, N Raghavan Applied Sciences 11 (13), 6046, 2021 | 11 | 2021 |
| Testbed for real-time monitoring of leak in low pressure gas pipeline H Mishra, P Karkulali, A Ukil, J Dauwels IECON 2016-42nd Annual Conference of the IEEE Industrial Electronics Society …, 2016 | 10 | 2016 |
| Hybrid particle filter trained neural network for prognosis of lithium-ion batteries K Pugalenthi, H Park, S Hussain, N Raghavan IEEE Access 9, 135132-135143, 2021 | 9 | 2021 |
| Remaining useful life prediction of lithium-ion batteries using neural networks with adaptive bayesian learning K Pugalenthi, H Park, S Hussain, N Raghavan Sensors 22 (10), 3803, 2022 | 8 | 2022 |
| Roughening particle filter based prognosis on power MOSFETs using ON-resistance variation K Pugalenthi, N Raghavan 2018 Prognostics and system health management conference (PHM-Chongqing …, 2018 | 4 | 2018 |
| Predicting Lumen Degradation of Light Emitting Diodes Using Hybrid Particle Filter Trained Neural Networks K Pugalenthi, H Park, S Hussain, N Raghavan IEEE Access 9, 167292-167304, 2021 | 3 | 2021 |
| Study on partial stratified resampling for particle filter based prognosis on li-ion batteries K Pugalenthi, N Raghavan 2018 Prognostics and System Health Management Conference (PHM-Chongqing …, 2018 | 3 | 2018 |
| Remaining Useful Life Estimation of Lithium-Ion Batteries Via Hyperparameter Optimized Bi-Long Short-Term Memory Recurrent Neural Networks R Sahay, K Pugalenthi, N Raghavan 2023 Global Reliability and Prognostics and Health Management Conference …, 2023 | | 2023 |
| Prognosis of LED lumen degradation using Bayesian optimized neural network approach K Pugalenthi, SLH Lim, H Park, S Hussain, N Raghavan Microelectronics Reliability 138, 114728, 2022 | | 2022 |
Nagarajan RaghavanAssociate Professor, Singapore University of Technology & Design (SUTD)Verified email at sutd.edu.sg
