Journal Publication

  1. Ananda Shankar Hati and T. K. Chatterjee “Some studies on condition monitoring techniques for online condition monitoring and fault diagnosis of mine winder motor”, International Journal of Engineering Science and Technology (IJEST), vol. 4, no—08, pp. 3785-3793, August 2012.
  2. Ananda Shankar Hati and T. K. Chatterjee “Axial leakage flux-based online condition monitoring instrumentation system for mine winder motor”, Journal of Mines, Metals & Fuels, vol. 63, no. 5&6, pp. 132-140, May-June 2015. (SCOPUS|Q4|0.123).
  3. Ananda Shankar Hati and T. K. Chatterjee “Current monitoring Instrumentation system for detecting airgap eccentricity in mine winder motor”, International Journal of Applied Engineering Research, vol. 10, no. 22, pp. 43000-43007, 2015. (SCOPUS|Q2|0.18).
  4. Ananda Shankar Hati and T. K. Chatterjee “Symmetrical component filter based online condition monitoring instrumentation system for mine winder motor” Measurement, (Elsevier), vol. 82, pp. 284-300, 2016 https://doi.org/10.1016/j.measurement.2016.01.005 (SCI|Q1|IF: 3.927).
  5. Ananda Shankar Hati “Vibration monitoring instrumentation system for detecting airgap eccentricity in mine winder motor”, Journal of Mine Metals and Fuels, vol. 64, no. 5&6, pp. 240-248, May-June 2016. (SCOPUS|Q4|0.123).
  6. Prashant Kumar and Ananda Shankar Hati “Review on Machine Learning Algorithm Based Fault Detection in Induction Motors,” Archives of Computational Methods in Engineering (2020), vol: 28, pp: 1929-1940, 2021 https://doi.org/10.1007/s11831-020-09446-w (SCI|Q1|IF: 7.351).
  7. Prashant Kumar and Ananda Shankar Hati “Convolutional Neural Network with batch normalisation for fault detection in SCIM,” IET Electric Power Application (2020), Vol: 15, issue: 1, pp. 39-50, 2021 https://doi.org/10.1049/elp2.12005 (SCI|Q2|IF: 2.926).
  8. Prashant Kumar and Ananda Shankar Hati “Deep Convolutional Neural Network based on adaptive gradient optimiser for fault detection in SCIM,” ISA Transactions (2020), Vol: 111, pp: 350-359, 2021 https://doi.org/10.1016/j.isatra.2020.10.052 (SCI|Q1|IF: 5.468).
  9. Prince, Ananda Shankar Hati, Prasun Chakrabarti, Jemal Hussein Abawajy and Ng Wee Keong “Development of Energy Efficient Drive for Ventilation System using Recurrent Neural Network,” Neural Computing and Applications (2021), Vol. 33, pg. 8659–8668 https://doi.org/10.1007/s00521-020-05615-x (SCI|Q1|IF: 5.606).
  10. Ashish Kumar Sinha, Ananda Shankar Hati, Mohamed Benbouzid and Prasun Chakrabarti “ANN-based Pattern Recognition for Induction Motor Broken Rotor Bar Monitoring under Supply Frequency Regulation” Machines (2021), Vol: 9(5) https://doi.org/10.3390/machines9050087 (SCI|Q2|IF: 2.428).
  11. Prince and Ananda Shankar Hati “A Comprehensive Review of Energy-Efficiency of Ventilation System using Artificial Intelligence” Renewable and Sustainable Energy Reviews (2021), Vol: 146, 2021 https://doi.org/10.1016/j.rser.2021-.111153 (SCI|Q1|IF: 14.982).
  12. Prashant Kumar and Ananda Shankar Hati “Transfer Learning Based Deep CNN Model for Multiple Faults Detection in SCIM” Neural Computing and Applications (2021), Vol: 33, pg. 15851–15862 https://doi.org/10.1007/s00521-021-06205-1 (SCI|Q1|IF: 5.606).
  13. Prince and Ananda Shankar Hati “Temperature and Humidity Dependent MRAS Based Speed Estimation Technique for Induction Motor used in Mine Ventilation Drive” Journal of Mining Science, (2021), Vol. 57, No. 5, pp. 842–851., https://doi.org/10.1134/S1062739121050148 (SCI|Q4|IF: 0.85).
  14. Prashant Kumar and Ananda Shankar Hati “Dilated Convolutional Neural Network Based Model For Bearing Faults and Broken Rotor Bar Detection in Squirrel Cage Induction Motors“ Expert Systems With Applications (2022), Vol. 191 https://doi.org/10.1016/j.eswa.2021.116290 (SCI|Q1|IF: 8.665).
  15. Prince and Ananda Shankar Hati “Convolutional Neural Network-Long Short-Term Memory Optimization for Accurate Prediction of Airflow in a Ventilation System” Expert Systems with Applications (2022), Vol. 195 https://doi.org/10.1016/j.eswa.2022.116618 (SCI|Q1|IF: 8.665).
  16. Aniket Vatsa and Hati Ananda Shankar Hati “Depolarization Current Prediction of Transformers OPI System Affected From Detrapped Charge Using LSTM,” in IEEE Transactions on Instrumentation and Measurement (2022), Vol. 71, pp. 1-11, Art no. 2511711, https://doi.org/10.1109/TIM.2022.3181286 (SCI|Q1|IF: 5.332).
  17. Prashant Kumar, Prince, Ananda Shankar Hati and Kim Heung Soo “Deep Transfer Learning Framework for Bearing Fault Detection in Motors” Mathematics (2022); 10(24):4683, https://doi.org/10.3390/math10244683 (SCI|Q1|IF: 2.592).
  18. Prince, Ananda Shankar Hati and Prashant Kumar “An Adaptive Neural Fuzzy Interface Structure Optimisation for Prediction of Energy Consumption and Airflow of a Ventilation System” Applied Energy (2023), Vol. 337 https://doi.org/10.1016/j.apenergy.2023.120879 (SCI|Q1|IF: 11.446).
  19. Aniket Vatsa, Ananda Shankar Hati, Vadim Bolshev, Alexander Vinogradov, Vladimir Panchenko and Prasun Chakrabarti “Deep Learning-Based Transformer Moisture Diagnostics Using Long Short-Term Memory Networks” Energies (2023), Vol. 16, no. 5: 2382 https://doi.org/10.3390/en16052382 (SCI|Q3|IF: 3.252).
  20. Prashant Kumar and Ananda Shankar Hati, and Prince “A transfer learning-based deep convolutional neural network approach for induction machine multiple faults detection” International Journal of Adaptive Control and Signal Processing (2023), https://doi.org/10.1002/acs.3643 (SCI|Q2|IF: 3.369).
  21. Md Asif Hussain, Ananda Shankar Hati, Prasun Chakrabarti, Bui Thanh Hung, Vadim Bolshev, and Vladimir Panchenko “DSVM-Based Model-Free Predictive Current Control of an Induction Motor” Energies (2023) Vol. 16, no. 15: 5657. https://doi.org/10.3390/en16155657 (SCI|Q3|IF: 3.252).
  22. Aniket Vatsa, Ananda Shankar Hati and Akshay Kumar Rathore “Enhancing Transformer Health Monitoring with AI-Driven Prognostic Diagnosis Trends” IEEE Industrial Electronics Magazine (2023), https://doi.org/10.1109/MIE.2023.3329277 (SCI|Q1|IF: 8.360).
  23. Aniket Vatsa and Ananda Shankar Hati “Insulation Aging Condition Assessment of Transformer in the Visual Domain Based on SE-CNN” Engineering Applications of Artificial Intelligence (2024), Volume 128: 107409, https://doi.org/10.1016/j.engappai.2023.107409 (SCI|Q1|IF: 8.0).

Aniket Vatsa, Ananda Shankar Hati, Prashant Kumar “Residual LSTM-Based Short Duration Forecasting of Polarization Current for Effective Assessment of Transformers Insulation” Scientific Reports 14, 1369 (2024). https://doi.org/10.1038/s41598-023-50641-z (SCI|Q2|IF: 4.9).

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