Dr. Arnaud NANFAK | transformateurs de puissance Award | Excellence in Research

Dr. Arnaud NANFAK | transformateurs de puissance Award | Excellence in Research

Dr. Arnaud NANFAK , Université de Douala – Cameroun , Cameroon

Dr. Arnaud Nanfak is a passionate educator and researcher in Electrical Energy and Robotics, currently serving as a contractual lecturer at Polytechnique de Douala and teaching at secondary school technical and professional levels. With over 5 years of experience in electrical engineering and more than 5 years in academia, he combines a dynamic teaching style with a rigorous research focus on power transformer fault diagnosis. Arnaud has supervised numerous Bachelor’s and Master’s theses, demonstrating leadership and innovation in his field. He holds a Ph.D. from the University of Douala, Cameroon, and is proficient in French, English, and various programming languages. 🌐

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ACADEMIC BACKGROUND

  • Ph.D. in Electrical Energy and Robotics, 2023
    • Energy, Materials, Modeling, and Methods Laboratory
    • Faculty of Engineering Sciences, University of Douala, Cameroon
  • D.E.A. in Physics and Engineering Sciences, 2015
    • Option: Electronics and Instrumentation
    • School of Fundamental and Applied Sciences, Doctoral School
  • DIPET 2 in Electrical Engineering, 2015
    • Option: Electronics
    • Higher Normal School of Technical Education of Douala, University of Douala, Cameroon
  • Master’s in Physics, 2014
    • Option: Electronics Sciences
    • Faculty of Sciences, University of Douala, Cameroon
  • Bachelor’s in Physics, 2012
    • Option: Electronics, Electrotechnics, and Automation
    • Faculty of Sciences, University of Ngaoundéré, Cameroon
  • Secondary Education Diplomas, 2009
    • Option: Physical Sciences and Mathematics

ARNARD NANFAK Ph.D. in Electrical Energy and Robotics Contractual Lecturer at Polytechnique de Douala Teacher at Technical and Professional Secondary Schools Tel: (+237) 695 26 23 80 / 620 150 808 / 678 289 787 Douala, Cameroon | nanfak.arnaud@yahoo.fr

RESEARCH AND THESES

  • Nano-ampere CMOS current reference with little temperature dependence using small offset voltage (June 2014)
    • Faculty of Sciences, University of Douala (Master’s in Physics)
  • Observation and control of asynchronous machine without mechanical sensor using fuzzy controller (June 2015)
    • Higher Normal School of Technical Education of Douala (DIPET 2)
  • Study and development of a mini-supervisor for hybrid electrical energy sources network/solar for very good air conditioner power supply (December 2015)
    • School of Fundamental and Applied Sciences, Doctoral School (D.E.A)
  • Contribution to the diagnosis of internal faults in power transformers using conventional and hybrid approaches (July 2023)
    • School of Fundamental and Applied Sciences, Doctoral School (Ph.D.)

SCIENTIFIC ARTICLES

  • Arnaud Nanfak, et al., “A combined technique for power transformer fault diagnosis based on k-means clustering and support vector machine,” IET Nanodielectrics, 2024.
  • Arnaud Nanfak, et al., “Traditional fault diagnosis methods for mineral oil-immersed power transformer based on dissolved gas analysis: Past, present and future,” IET Nanodielectrics, 2024.
  • Arnaud Nanfak, et al., “Hybrid DGA method for power transformer faults diagnosis based on evolutionary k-means clustering and dissolved gas subsets analysis,” IEEE Transactions on Dielectrics and Electrical Insulation, 2023.
  • Arnaud Nanfak, et al., “Hybrid Method for Power Transformers Faults Diagnosis Based on Ensemble Bagged Tree Classification and Training Subsets Using Rogers and Gouda Ratios,” International Journal of Intelligent Engineering & Systems, 2022.
  • Arnaud Nanfak, et al., “Interpreting dissolved gases in transformer oil: A new method based on the analysis of labelled fault data,” IET Generation Transmission & Distribution, 2021.

Publication Top Notes:

Improved intelligent methods for power transformer fault diagnosis based on tree ensemble learning and multiple feature vector analysis

Citation: 3

Hybrid DGA Method for Power Transformer Faults Diagnosis Based on Evolutionary k-Means Clustering and Dissolved Gas Subsets Analysis

Citation -5

Interpreting dissolved gases in transformer oil: A new method based on the analysis of labelled fault data

Citation -19

Design of new duty-cycle modulator structures for industrials applications, an alternative to pulse-width modulation

Citation -4

Hybrid Method for Power Transformers Faults Diagnosis Based on Ensemble Bagged Tree Classification and Training Subsets Using Rogers and Gouda Ratios

Citation -3