MITS has secured NIRF India Ranking 2024 in the band 201 to 300.
Dr. Srinivas Chikkam

Qualification : Ph.D. (NIT, Delhi)

Designation : Asst. Professor

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