Fuzzy Logic Diagnostics for Open-Circuit Faults in Renewable Energy Voltage Source Inverters with Changeable Load Conditions

Authors

  • N. R. Dhumale AISSMS Institute of Information Technology, Pune, India. 1,6 Sinhgad College of Engineering, Pune, India.
  • R. B. Dhumale AISSMS Institute of Information Technology, Pune, India. 1,6 Sinhgad College of Engineering, Pune, India.
  • M. V. Shelke AISSMS Institute of Information Technology, Pune, India. 1,6 Sinhgad College of Engineering, Pune, India.
  • S. S. Nikam AISSMS Institute of Information Technology, Pune, India. 1,6 Sinhgad College of Engineering, Pune, India.
  • P. B. Mane AISSMS Institute of Information Technology, Pune, India. 1,6 Sinhgad College of Engineering, Pune, India.
  • A. N. Sarawade AISSMS Institute of Information Technology, Pune, India. 1,6 Sinhgad College of Engineering, Pune, India.

Keywords:

Fuzzy logic, voltage source inverter, varied load, Park’s Vector Transform

Abstract

In this paper, a three-phase voltage source inverter (VSI) fault diagnosis system based on Fuzzy Logic is proposed. The Fuzzy Logic Fault Diagnosis (FLFD) system consists of four main stages such as PVM-Current Normalizer and Typical Transient Suppressor, Discrete Wavelet Transform, Feature Selection and Fuzzy Logic (FL). The crucial prerequisites for the aforementioned steps, including feature selection, mother wavelet selection, and FL structure, are covered in detail. The time domain waveform is used to clarify the terms PVM-current normalizer and typical transient suppressor. Due to the employment of a PVM-current normalizer and a conventional transient suppressor, this system is less dependent on mechanical or electrical operating conditions than other fault diagnostic methods. The choice of the mother wavelet and the level of decomposition are described in detail. By using the fewest possible features, the FLFD system identifies a variety of potential faults under varied load and different frequency. The approach for selecting features that work well is described. To categories faults, a FL's architecture is built. On a suitable dataset, the system is implemented, and its performance is assessed. The experimental findings demonstrate the suggested system's superior performance and ability to accurately diagnose VSI issues. 

Downloads

Download data is not yet available.

References

İ. Şahin, “Model Predictive Torque Control of an Induction Motor Enhanced With an Inter-Turn Short Circuit Fault Detection Feature a Thesis Submitted To the Graduate School of Natural and Applied Sciences of Middle East Technical University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Electrical and Electronic Engineering,” no. September, 2021.

L. Kou, C. Liu, G. wei Cai, Z. Zhang, J. ning Zhou, and X. mei Wang, “Fault diagnosis for three-phase PWM rectifier based on deep feedforward network with transient synthetic features,” ISA Trans., vol. 101, no. xxxx, pp. 399–407, 2020, doi: 10.1016/j.isatra.2020.01.023.

H. S. Khan, M. Aamir, K. Kauhaniemi, M. Mumtaz, M. W. Hassan, and M. Ali, “Improved finite control set model predictive control for distributed energy resource in islanded microgrid with fault-tolerance capability,” Eng. Sci. Technol. an Int. J., vol. 24, no. 3, pp. 694–705, 2021, doi: 10.1016/j.jestch.2020.12.015.

E. B. Rocha Junior, O. E. Batista, and D. S. L. Simonetti, “Differential Analysis of Fault Currents in a Power Distribution Feeder Using abc, αβ0, and dq0 Reference Frames,” Energies, vol. 15, no. 2, pp. 1–22, 2022, doi: 10.3390/en15020526.

J. Liu, H. Tan, Y. Shi, Y. Ai, S. Chen, and C. Zhang, “Research on Diagnosis and Prediction Method of Stator Interturn Short-Circuit Fault of Traction Motor,” Energies, vol. 15, no. 10, 2022, doi: 10.3390/en15103759.

N. Koteleva, N. Korolev, Y. Zhukovskiy, and G. Baranov, “A soft sensor for measuring the wear of an induction motor bearing by the park’s vector components of current and voltage,” Sensors, vol. 21, no. 23, 2021, doi: 10.3390/s21237900.

M. R. Mullali Kunnontakath Puthiyapurayil, M. Nadir Nasirudeen, Y. A. Saywan, M. W. Ahmad, and H. Malik, “A Review of Open-Circuit Switch Fault Diagnostic Methods for Neutral Point Clamped Inverter,” Electron., vol. 11, no. 19, pp. 1–29, 2022, doi: 10.3390/electronics11193169.

J. Kim, S. Park, D. Min, and W. Kim, “Comprehensive survey of recent drug discovery using deep learning,” Int. J. Mol. Sci., vol. 22, no. 18, 2021, doi: 10.3390/ijms22189983.

L. Xu, R. Ma, R. Xie, J. Xu, Y. Huangfu, and F. Gao, “Open-Circuit Switch Fault Diagnosis and Fault- Tolerant Control for Output-Series Interleaved Boost DC-DC Converter,” IEEE Trans. Transp. Electrif., vol. 7, no. 4, pp. 2054–2066, 2021, doi: 10.1109/TTE.2021.3083811.

H. O. A. Ahmed, Y. Yu, Q. Wang, M. Darwish, and A. K. Nandi, “Intelligent Fault Diagnosis Framework for Modular Multilevel Converters in HVDC Transmission,” 2022.

A. Dianov, S. Member, A. Anuchin, and S. Member, “Phase Loss Detection Using Current Signals : A Review,” IEEE Access, vol. 9, pp. 114727–114740, 2021, doi: 10.1109/ACCESS.2021.3105483.

Y. Wang, Y. Ding, and Y. Yin, “Reliability of Wide Band Gap Power Electronic Semiconductor and Packaging : A Review of,” 2022.

R. B. Dhumale and S. D. Lokhande, “Diagnosis of multiple open switch faults in three phase voltage source inverter,” J. Intell. Fuzzy Syst., vol. 30, no. 4, pp. 2055–2065, 2016, doi: 10.3233/IFS-151918.

Goyal, A. ., Kanyal, H. S. ., & Sharma, B. . (2023). Analysis of IoT and Blockchain Technology for Agricultural Food Supply Chain Transactions. International Journal on Recent and Innovation Trends in Computing and Communication, 11(3), 234–241. https://doi.org/10.17762/ijritcc.v11i3.6342

Moore, B., Clark, R., Muñoz, S., Rodríguez, D., & López, L. Automated Grading Systems in Engineering Education: A Machine Learning Approach. Kuwait Journal of Machine Learning, 1(2). Retrieved from http://kuwaitjournals.com/index.php/kjml/article/view/125

Downloads

Published

25.12.2023

How to Cite

Dhumale, N. R. ., Dhumale, R. B. ., Shelke, M. V. ., Nikam, S. S. ., Mane, P. B. ., & Sarawade, A. N. . (2023). Fuzzy Logic Diagnostics for Open-Circuit Faults in Renewable Energy Voltage Source Inverters with Changeable Load Conditions . International Journal of Intelligent Systems and Applications in Engineering, 12(1), 80–86. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3678

Issue

Vol. 12 No. 1 (2024)

Section

Research Article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.

IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.

Most read articles by the same author(s)