Dr. Srinivas Chikkam
Qualification : Ph.D. (NIT, Delhi)
Details of Educational Qualification:
| Course | Specialization | Group | College Name/University | Year of Passing |
|---|---|---|---|---|
| Ph.D. | Electrical and Electronics Engineering | Electrical and Electronics Engineering | National Institute of Technology, Delhi | 2024 |
| M.Tech. | Power Electronics | Electrical Engineering | JNTU Kakinada | 2015 |
| B.E. | Electrical and Electronics Engineering | Electrical and Electronics Engineering | SRKR Engineering College, Andhra university | 2008 |
List of Publications
| S.No | Title of the Paper | Full Details of Journal Name / Conference Name, Volume number, page number, Date |
|---|---|---|
| 1 | “Stockwell Transform of Quadrature Stator Current- Based Fault Assessment in Induction Machine at Different Load Condition” | Journal of Vibration Engineering & Technologies, 2022. DOI: https:// doi.org/10.1007/s42417-022-00835-y (SCI,I.F. 2.33) |
| 2 | “Condition monitoring and fault diagnosis of induction motor using DWT and ANN” | Arabian Journal for Science and Engineering 2022. DOI: https:// doi.org/10.1007/s13369-022-07294-3 (SCI,I.F. 2.807) |
| 3 | High-Resolution-Based Electrical Fault Diagnosis of Induction Motor Using Gabor analysis of Quadrature Stator Current at Variable Speed Regime | Arab J Sci Eng 47, 14055–14074 (2022). https://doi.org/10.1007/s13369- 022-06623-w (SCI,I.F 2.807) |
| 4 | Smart Classifiers Based Classification and Condition Monitoring of Induction Motor Faults | International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8 Issue-12, October 2019,DOI: 10.35940/ijitee.L2887.1081219 |
| 5 | Modeling and simulation of a novel three- phase multilevel inverter with induction motor drive | International Journal of Research in Advent Technology, 2(11), 40-44 |
| 6 | Motor Bearing Fault Prediction Using Artificial Intelligence Techniques | 2023 International Conference on Microwave, Optical, and Communication Engineering (ICMOCE), Bhubaneswar, India, 2023, pp. 1-4, doi: 10.1109/ICMOCE57812.2023.10165790 |
| 7 | Machine Learning Based Incipient Fault Diagnosis of Induction Motor. In: Challa, R.K., et al | Artificial Intelligence of Things. ICAIoT 2023. Communications in Computer and Information Science, vol 1930. Springer, Cham. https://doi.org/10.1007/978-3-031-48781-1_10 |