Abstract
Stator current signals are widely used in fault detection and monitoring of voltage inverters. This paper proposes a method of automatic faultdiagnosis voltage inverters. The emphasis is on a signal processing technique and an artificial intelligence technique to detect and locate the open-circuit fault of an IGBT in an inverter feeding induction motor. The first technique is based on the fourier transform (FT) to detect the amplitude of the three harmonics (continuous component: f0, the amplitude of the fundamental harmonic: f50 and the harmonic which characterizes the open-circuit fault of an IGBT: f100) for each phase current (ias, ibs and ics). The second technique is based on the artificial neural network (ANN), to locate the faulty IGBT. The characteristics used to train the ANN model are the amplitudes of three frequencies f0, f50 and f100. The results obtained by the ANN show a good performance with a very high classification rate equal to 97.50%.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Cherif, B.D.E., Bendiabdellah, A., Tabbakh, M.: An Automatic Diagnosis of an Inverter IGBT Open-Circuit Fault Based on HHT-ANN. Electric Power Compon. Syst. 48(6–7), 589–602 (2020)
Cherif, B.D.E., Bendiabdellah, A., Tabbakh, M.: Diagnosis of an inverter IGBT open-circuit fault by Hilbert-Huang transform application. Traitement du Signal 36(2), 127–132 (2019)
Mostefa, T., Tarak, B., Hachemi, G.: An automatic diagnosis method for an open switch fault in unified power quality conditioner based on artificial neural network. Traitement du Signal 35(1), 7–21 (2018)
Chappa, A., Gupta, S., Sahu, L.K., Gupta, K.K.: Fault diagnosis of cascaded H-bridge multilevel inverter by DWPT multi resolution and ANN. In: 2020 First International Conference on Power, Control and Computing Technologies (ICPC2T), pp. 128–133. IEEE (2020)
Bendiabdellah, A., Cherif, B.D.E., Boudinar, A.H.: Diagnosis of an inverter by Clark transform technique based on neural network. In: 2018 6th International Conference on Control Engineering & Information Technology (CEIT), pp. 1–5. IEEE (2018)
Wang, T., Qi, J., Xu, H., Wang, Y., Liu, L., Gao, D.: Fault diagnosis method based on FFT-RPCA-SVM for cascaded-multilevel inverter. ISA Trans. 60, 156–163 (2016)
Xia, X., Ning, P.: Fault diagnosis of frequency control system based on FFT. In 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), pp. 1–5. IEEE (2019)
Mahdi, H.: Fault diagnosis of induction motor fed by frequency converter. The signal signature analysis technique. GRIN Verlag (2016)
Cherif, B.D.E., Bendiabdellah, A., Bendjebbar, M., et al.: Review on external and internal faults of an association inverter-motor and their impact on the motor operation. In: 2017 International Conference on Green Energy Conversion Systems (GECS), pp. 1–7. IEEE (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Cherif, B.D.E., Seninete, S., Defdaf, M., Berrabah, F. (2022). Diagnosis of Three-Phase Two-Level Voltage Inverter Under Open-Circuit Fault of an IGBT. In: Hatti, M. (eds) Artificial Intelligence and Heuristics for Smart Energy Efficiency in Smart Cities. IC-AIRES 2021. Lecture Notes in Networks and Systems, vol 361. Springer, Cham. https://doi.org/10.1007/978-3-030-92038-8_67
Download citation
DOI: https://doi.org/10.1007/978-3-030-92038-8_67
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-92037-1
Online ISBN: 978-3-030-92038-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)