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Madhav Mishra
Madhav Mishra

Madhav Mishra

Operation, Maintenance and Acoustics
Department of Civil, Environmental and Natural Resources Engineering
madhav.mishra@ltu.se
F115 Luleå

Bio

Currently, Madhav Mishra is a senior researcher at the Division of Operation and Maintenance Engineering, Luleå. He is a visiting researcher at the NASA Ames Research Center, California, USA.

Dr. Madhav Mishra has completed a PhD Degree at the Division of Operation and Maintenance Engineering at Luleå University of Technology in Sweden within the framework of the SKF-University of Technology Center (UTC). His research focus lies to improve the diagnosis and prognosis of the RUL of an asset by the development of hybrid models based on Industrial Artificial Intelligence and Machine Learning. He obtained Master degree in Control Systems Engineering with specialisation in Mechatronics from the Netherlands. He worked at Philips Semiconductors/NXP in Nijmegen in the Netherlands as a Senior Design Engineer Mechatronics where he has involved in design and developed of the high speed rotating machine.

Research interests:

  • Industrial Artificial Intelligence and Machine Learning 
  • Diagnostics, Prognostics, and Health Monitoring
  • Development of model-based and data-driven diagnostic and prognostic approaches
  • Bayesian tracking (Kalman filtering, particle filtering)
  • Fusion based algorithms for Diagnostics and Prognostics

Ongoing research:

  • IAI4PHM- Industrial Artificial Intelligence for Condition Monitoring, Diagnostics and Prognostics & Health Management (PHM) 
  • Machine Learning - Based on RUL Predictions
  • Bayesian Statistical Machine learning

If you are interested in collaborating in the areas of  mentioned above research interests., please contact me at email  

If you are interested in my CV, please send an email to me.

 

 

Publications

Article in journal

A channel model for power line communication using 4PSK technology for diagnosis: Some lessons learned (2018)

Mishra. M, van Riet. M
International Journal of Electrical Power & Energy Systems, Vol. 95, s. 617-634
Article in journal

Bayesian hierarchical model-based prognostics for lithium-ion batteries (2018)

Mishra. M, Martinsson. J, Rantatalo. M, Goebel. K
Reliability Engineering & System Safety, Vol. 172, s. 25-35
Article in journal

Hierarchical model-based prognostics for Li-ion batteries (2018)

Mishra. M, Martinsson. J, Rantatalo. M, Goebel. K
Advances In ENGINEERING
Conference paper

Model-Based Prognostic Approach for Battery Variable Loading Conditions (2017)

Some Accuracy Improved
Mishra. M
Part of: Proceedings of the Asia Pacific Conference of  the Prognostics and Health Management Society 2017, s. 147-149, 2017