Detection of the stator inter-turn fault using the energy feature of the wavelet coeffcients obtained through continuous wavelet transform

Document Type : Article

Authors

Electrical Engineering Department, Shahid Beheshti University, Tehran, P.O. Box 19839-69411, Iran

Abstract

This research aims to investigate a fault detection method applicable to the stator part of the Brush-Less DC motor (BLDC). Indeed, it is a concern to make sure the motor is operating in a healthy mode, and in any other case, it is of great importance to detect the fault as soon as possible to prevent the further ruin of the major system. Regarding this, a sub-branch method of the Wavelet Transform (WT) analysis, named Continuous Wavelet Transform (CWT), is utilized to observe the short-circuit fault in the stator coils. Thus, a novel simulator of the BLDC motor is developed by making an interconnection between ADAMS and MATLAB in which different electrical and mechanical components are included. Therefore, a close-to-reality model of the BLDC motor is achieved, leading to a more accurate evaluation of the proposed method. An energy-type feature will be suggested to characterize the fault happening. Through acquiring the normalized energy amount for one of the Wavelet Coefficient (WC) signals, obtained by the CWT, and comparing the energy with a predefined threshold amount of energy for that signal, it is feasible to detect the stator's flawed performance. By conducting different simulations, the proposed method will be validated.

Keywords

References

References:
1. Rkhissi-Kammoun, Y., Ghommam, J., Boukhnifer, M., et al. "Two current sensor fault detection and isolation schemes for induction motor drives using algebraic estimation approach", Math. Comput. Simul., 157, pp. 39-62 (2019).
2. Sakunthala, S., Kiranmayi, R., and Mandadi, P.N. "A study on industrial motor drives: Comparison and applications of PMSM and BLDC motor drives", 2017 Int. Conf. Energy, Commun. Data Anal. Soft Comput. ICECDS 2017, pp. 537-540 (2017).
3. Khan, K.R. and Miah, M.S. "Fault-tolerant BLDC motor-driven pump for  fluids with unknown specific gravity: an experimental approach", IEEE Access, 8, pp. 30160-30173 (2020).
4. Patton, R.J., Uppal, F.J., Simani, S., et al. "Robust FDI applied to thruster faults of a satellite system", Control Eng. Pract., 18(9), pp. 1093-1109 (2010).
5. Valdes, A. and Khorasani, K. "A pulsed plasma thruster fault detection and isolation strategy for formation  flying of satellites", Appl. Soft Comput. J., 10(3), pp. 746-758 (2010).
6. Aqil, M. and Hur, J. "A direct redundancy approach to fault-tolerant control of BLDC motor with a damaged hall-effect sensor", IEEE Trans. Power Electron., 35(2), pp. 1732-1741 (2020).
7. Roy, S., Alam, M.K., Khan, F., et al. "An irradianceindependent, robust ground-fault detection scheme for PV arrays based on spread spectrum time-domain reflectometry (SSTDR)", IEEE Trans. Power Electron., 33(8), pp. 7046-7057 (2017).
8. Park, J.K. and Hur, J. "Detection of inter-turn and dynamic eccentricity faults using stator current frequency pattern in IPM-type BLDC motors", IEEE Trans. Ind. Electron., 63(3), pp. 1771-1780 (2016).
9. Nayak, N.R., Dash, P.K., and Bisoi, R. "A hybrid time frequency response and fuzzy decision tree for nonstationary signal analysis and pattern recognition", Int. J. Autom. Comput., 16(3), pp. 398-412 (2018).
10. Da Costa, C., Kashiwagi, M., and Mathias, M.H. "Rotor failure detection of induction motors by wavelet transform and Fourier transform in non-stationary condition", Case Stud. Mech. Syst. Signal Process., 1, pp. 15-26 (2015).
11. Moravej, Z., Mortazavi, S.H., and Shahrtash, S.M. "DT-CWT based event feature extraction for high impedance faults detection in distribution system", Int. Trans. Electr. energy Syst., 25(12), pp. 3288-3303 (2014).
12. Abed, W., Sharma, S., Sutton, R., et al. "A robust bearing fault detection and diagnosis technique for brushless DC motors under non-stationary operating conditions", J. Control. Autom. Electr. Syst., 26(3), pp. 241-254 (2015).
13. Elbouchikhi, E., Amirat, Y., Feld, G., and Benbouzid, M. "Generalized likelihood ratio test based approach for stator-fault detection in a PWM inverter-fed induction motor drive", IEEE Trans. Ind. Electron., 66(8), pp. 6343-6353 (2019).
14. Afrandideh, S., Milasi, M.E., Haghjoo, F., et al. "Turn to turn fault detection, discrimination, and faulty region identification in the stator and rotor windings of synchronous machines based on the rotational magnetic field distortion", IEEE Trans. Energy Convers., 35(1), pp. 292-301 (2020).
15. Hu, R., Wang, J.B., Mills, A., et al. "Current residual based stator inter-turn fault detection in permanent magnet machines", IEEE Trans. Ind. Electron., 68(1), pp. 59-69.
16. Sa, B.A., Barros, C.M.V., Siebra, C.A., et al. "A multilayer perceptron-based approach for stator fault detection in permanent magnet wind generators", 2019 IEEE PES Conf. Innov. Smart Grid Technol. ISGT Lat. Am.,, pp. 1-6 (2019).
17. Shifat, T.A., and Hur, J.W. "An effective stator fault diagnosis framework of BLDC motor based on vibration and current signals", IEEE Access, 8, pp. 106968-106981 (2020).
18. Akhil Vinayak, B., Anjali Anand, K., and Jagadanand, G. "Wavelet-based real-time stator fault detection of inverter-fed induction motor", IET Electr. Power Appl., 14(1), pp. 82-90 (2020).
19. Awadallah, M.A., Morcos, M.M., Gopalakrishnan, S., et al. "Detection of stator short circuits in VSI-Fed brushless DC motors using wavelet transform", IEEE Trans. Energy Convers., 21(1), pp. 1-8 (2006).
20. Zandi, O., and Poshtan, J. "Brushless DC motor bearing fault detection using hall effect sensors and a two stage wavelet transform", 26th Iran. Conf. Electr. Eng. ICEE, pp. 827-833 (2018).
21. Frosini, L., Zanazzo, S., and Albini, A. "A waveletbased technique to detect stator faults in inverter-fed induction motors", Proc. - 2016 22nd Int. Conf. Electr. Mach. ICEM 2016, pp. 2917-2923 (2016).
22. Salehifar, M., and Moreno-Equilaz, M. "Fault diagnosis and fault-tolerant finite control set-model predictive control of a multiphase voltage-source inverter supplying BLDC motor", ISA Trans., 60, pp. 143-155 (2016).
23. Irimia, N.D., Lazar, F.I., and Luchian, M. "Highly redundant actuation system concept with dual stator six phases BLDC motor suitable for automotive industry applications: fault tolerant system actuation design", 2018 Int. Conf. Expo. Electr. Power Eng., pp. 785-790 (2018).
24. Skowron, M., Orlowska-kowalska, T., Wolkiewicz, M., et al. "Convolutional neural network-based stator current data-driven incipient stator fault diagnosis of inverter-fed induction motor", Energies, 13(6), 1475, pp. 1-21 (2020). (2020).
25. Maraaba, L.S., Al-Hamouz, Z.M., Milhem, A.S., et al. "Neural network-based diagnostic tool for detecting stator inter-turn faults in line start permanent magnet synchronous motors", IEEE Access, 7, pp. 89014- 89025 (2019).
26. Rao, A.P.C., Obulesh, Y.P., and Babu, C.S. "Mathematical modeling of bldc motor with closed loop speed control using pid controller under various loading conditions", ARPN J. Eng. Appl. Sci., 7(10), pp. 1321-1328 (2012).
27. Cheema, M.A.M., Fletcher, J.E., Xiao, D., et al. "A linear quadratic regulator-based optimal direct thrust force control of linear permanent-magnet synchronous motor", IEEE Trans. Ind. Electron., 63(5), pp. 2722- 2733 (2016).
28. Hanselman, D., Brushless Permanent Magnet Motor Design, 2nd edition, Magna Physics Publishing, Motorsoft Division of Fisher Electric Technology, 3000 M Henkle Drive, Lebanon, Ohio 45036, Ohio (2006).
29. Du, B., Wu, S., Han, S., et al. "Interturn fault diagnosis strategy for interior permanent-magnet synchronous motor of electric vehicles based on digital signal processor", IEEE Trans. Ind. Electron., 63(3), pp. 1694-1706 (2016).
30. Saghafinia, A., Kahourzade, S., Mahmoudi, A., et al. "On line trained fuzzy logic and adaptive continuous wavelet transform based high precision fault detection of IM with broken rotor bars", Conf. Rec.-IAS Annu. Meet., IEEE Ind. Appl. Soc., pp. 1-8 (2012).
Scientia Iranica
Volume 30, Issue 2
Transactions on Computer Science & Engineering and Electrical Engineering (D)
March and April 2023
Pages 536-550

Files

Share

How to cite

Statistics