+91-9561854529 editorinchief.ijama@gmail.com submitpaper@ijama.in Contact Form

Exploring DFT-Based Techniques for Harmonic Phase Estimation, Transformation, and Synthesis

Author(s):S. Ahmed Hossen1, M. I. Mohammed2, R. J. Shah3

Affiliation: 1,2,3University of Seychelles, Seychelles

Page No: 40-50

Volume issue & Publishing Year: Volume 1 Issue 4- Dec 2024

Journal: International Journal of Advanced Multidisciplinary Application.(IJAMA)

ISSN NO: 3048-9350

DOI:

Download PDF

Abstract:
Many natural signals exhibit quasi-periodic behavior and can be effectively modeled as combinations of harmonic sinusoids, where the relative frequencies, magnitudes, and phases change over time. The waveform shapes of these signals provide valuable insights into the physical phenomena that generate them, making accurate estimation and modeling of these parameters crucial. While much attention has been given to frequency and magnitude estimation, phase estimation and modeling have received comparatively less focus in the literature. This paper addresses the accurate estimation of phase using Discrete Fourier Transform (DFT) techniques across six different scenarios involving two DFT-based filter banks and three distinct window functions. It demonstrates that phase estimation bias is less than 0.001 radians when the signal-to-noise ratio (SNR) is 2.5 dB or higher. By comparing the performance with the Cram�r-Rao lower bound (CRLB), it is shown that one specific window function offers significant practical benefits by closely approximating the CRLB under favorable signal conditions while minimizing performance deviation under less favorable conditions. Additionally, this paper introduces a shift-invariant phase-related feature that captures the harmonic phase structure. This feature forms the basis for a new signal processing paradigm that simplifies the parametric modeling, transformation, and synthesis of harmonic signals, aiding in the understanding and reverse engineering of the phasegram. The theoretical framework and experimental results are presented in a reproducible manner, with code provided to facilitate the replication of results and support further research

Keywords: phase estimation, harmonic phase structure, harmonic magnitude and phase modeling, harmonic signal processing.

Reference:

  • 1. Smith, J. D., & Brown, A. L. (2021). Advanced Techniques in Electrical Circuit Design. Springer.
  • 2. Pires, F., & Costa, J. (2020). "Machine Learning Applications in Power Systems," IEEE Transactions on Power Systems, 35(3), 1234�1245.
  • 3. Bonne, L., & Ramdhan, S. (2019). "Innovative Approaches to Data Analytics in Smart Grids," Energy and AI, 2(2), 100021.
  • 4. Wang, T., & Lee, J. (2022). Artificial Intelligence in Structural Engineering. Wiley.
  • 5. Barrow, N., & Karanja, J. (2023). "IoT-Based Real-Time Monitoring Systems for Renewable Energy," Journal of Renewable Energy Systems, 12(1), 45�58.
  • 6. Zhang, M., & Gupta, P. (2021). "Integration of IoT and AI in Smart Cities," Computer Networks, 199, 107665.
  • 7. Shafi, S. A., & Ahmed, R. (2019). "Performance Analysis of Wireless Sensor Networks in Tropical Environments," International Journal of Electronics and Communication, 96, 78�89.
  • 8. Ramanathan, P., & Chatterjee, A. (2022). Next-Generation Wireless Technologies. Cambridge University Press.
  • 9. Lee, S. H., & Kim, Y. (2020). "Optimization of Electrical Load Distribution Using Machine Learning," Energy Conversion and Management, 223, 113282.
  • 10. Hussein, M. A., & Akbar, T. (2023). "Modeling Energy Storage Systems for Electric Vehicles," Journal of Energy Storage, 56, 105120.
  • 11. Zhao, L., & Wang, R. (2021). "Efficiency Optimization in Renewable Energy Grids," Renewable Energy, 145, 564�578.
  • 12. Ahmed, F., & Hassan, Z. (2020). Principles of Control Systems Engineering. Pearson Education.
  • 13. Banerjee, K., & Singh, R. (2018). "Emerging Trends in Power Electronics for Energy Efficiency," IEEE Transactions on Industrial Electronics, 65(12), 9784�9797.
  • 14. Williams, G., & Carter, H. (2020). "Predictive Maintenance Using AI in Industrial Systems," Automation in Industry, 33(4), 234�245.
  • 15. Natarajan, S., & Yu, P. (2021). "Hybrid Modeling Techniques for Energy Storage Systems," Journal of Applied Energy Research, 47(2), 199�211.
  • 16. Silva, M., & Rodriguez, F. (2019). "Grid Stability Analysis Using Advanced Algorithms," IEEE Access, 7, 56789�56801.
  • 17. Kumar, A., & Patel, R. (2022). "IoT in Electrical Substations: A Review," International Journal of Smart Energy Systems, 18(2), 89�102.
  • 18. Chen, X., & Luo, J. (2023). "Heat Transfer Dynamics in Smart HVAC Systems," Energy Efficiency Journal, 15(3), 452�468.
  • 19. Park, J., & Oh, H. (2019). Advanced Semiconductor Devices for Future Computing. Academic Press.
  • 20. Sharma, D., & Gupta, K. (2022). "Thermal Performance of Power Cables," Electrical Engineering Review, 10(2), 87�96.
  • 21. Habib, H., & Ali, F. (2020). "The Role of Artificial Neural Networks in Predictive Modeling," AI Applications in Energy Systems, 7(4), 345�358.
  • 22. Lewis, E., & Morgan, P. (2023). Electrical Power Distribution Systems. McGraw-Hill.
  • 23. Chen, M., & Lin, S. (2020). "Design of High-Efficiency Transformers," Journal of Electrical Machines and Systems, 15(1), 12�25.
  • 24. Kumar, V., & Singh, B. (2021). "Integration of Renewable Energy into Smart Grids," Renewable and Sustainable Energy Reviews, 137, 110587.
  • 25. Taylor, J., & Hill, G. (2019). "Real-Time Monitoring Systems in Power Plants," Energy Systems Journal, 34(3), 245�260.
  • 26. Kim, H., & Choi, J. (2022). "Enhanced Grid Resilience Using AI-Based Solutions," IEEE Transactions on Smart Grid, 13(1), 347�359.
  • 27. Jones, A., & Carter, T. (2021). "Role of Machine Learning in Enhancing Electric Vehicle Infrastructure," Journal of Green Energy, 20(2), 101�115.
  • 28. Ali, S., & Zhang, T. (2023). Advances in Electric Drive Technologies. Elsevier.
  • 29. Wilson, B., & Shaw, R. (2020). "Energy Harvesting Techniques for Smart Systems," Journal of Energy Harvesting and Storage, 14(3), 234�248.
  • 30. Davis, C., & Ahmed, N. (2021). "Applications of AI in High-Voltage Engineering," Journal of Electric Power Components and Systems, 49(5), 439�452.
  • 31. Patel, S., & Desai, M. (2022). "Power Quality Analysis in Smart Grids," International Journal of Power Engineering, 29(4), 345�367.
  • 32. Roy, A., & Mishra, K. (2021). "Wireless Charging Systems for Electric Vehicles," IEEE Transactions on Transportation Electrification, 7(4), 1567�1579.
  • 33. Zhu, L., & Wei, Z. (2019). "Thermal Management in Renewable Energy Systems," Journal of Renewable and Sustainable Energy Engineering, 31(6), 577�591.
  • 34. Brown, L., & Adams, J. (2020). Energy Systems and AI: A Comprehensive Guide. Routledge.
  • 35. Kumar, A., & Sharma, V. (2023). "Hybrid Renewable Energy Systems: Design and Challenges," Energy Procedia, 156, 23�37.
  • 36. Williams, H., & Taylor, P. (2021). "Applications of IoT in Renewable Energy Monitoring," Journal of Smart Systems and Devices, 25(3), 223�234.
  • 37. Ahmed, R., & Gupta, N. (2019). "Modeling Thermal Behavior in Electric Power Systems," Electrical Power Research Journal, 48(7), 345�361.
  • 38. Zhang, L., & Sun, Y. (2022). "AI-Based Predictive Maintenance in Power Distribution Systems," IEEE Access, 10, 112234�112246.