Abstract
To monitor, diagnose, and suppress the inter-turn short-circuit faults (ITSCFs) of a submersible motor, an approach for the on-line identification of its winding faults has been proposed based on monitoring the stator current. First, an ITSCF model with the global leakage referred to the stator is given. With this model, the detection parameter, which is equal to the ratio of the turns of the fault windings to the total turns of the windings in the healthy phase, can be derived. Second, a faulty model described by the fourth order state-space equation of the motor with a winding fault has been given. Based on sampled stator voltage and stator current, the detection parameter has been solved and used to estimate the location and the turns of inter-turn short-circuit windings of the motor in real time. The accuracy and the robustness of the proposed approach has been illustrated with a 1.5 kW motor that is fed by a 10 kW inverter. Experiment shows that the identification accuracy in terms of the number of the ITSCF windings of the motor stator is less than 3. It can give a reference for the on-line diagnose the ITSCFs of the stator windings of a submersible motor that works in 2 km deep well.
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Abbreviations
- \(\theta_{c}\) :
-
Localization angle between the faulty phase and the reference phase (phase b) (rad)
- \(R_{c}\) :
-
Rotor position (rad)
- \(R_{c}\) :
-
Impedance of the ITSCF winding (\(\Omega\))
- \(B_{c}\) :
-
Short-circuit winding
- \(n_{c}\) :
-
Turn number of the fault windings
- \(n_{s}\) :
-
Total turns in a healthy phase, \(n_{s}\) = 315
- \(\eta_{c}\) :
-
Detection parameter, \(\eta_{c} = n_{c} /n_{s}\)
- \(\eta_{ck}\) :
-
\(k = 1,2,3\) Detection parameters of phases a, b, and c
- \(n_{ck}\) :
-
\(n_{ck} = \eta_{ck} \cdot n_{s} { ,}k = 1,2,3,\) estimation turn of the ITSCF winding of phase a, phase b, and phase c
- \(\mu\) :
-
\(\mu = [\eta_{c1 \, } \, \eta_{c2 \, } \, \eta_{c3 \, } ]^{T}\), detection parameter set
- \(n_{c1}^{*}\) :
-
Actual turns of the artificial ITSCF windings of phase a of the experimental motor
- \(u_{ds} /u_{qs}\) :
-
d axis/q axis components of the stator voltage (V)
- \(u_{dqs}\) :
-
\(u_{dqs} = [u_{ds} \, u_{qs} ]^{T}\)
- \(\overline{u}_{ds} /\overline{u}_{qs}\) :
-
d Axis/q axis components of the stator voltage under ITSCF (V)
- \(\overline{u}_{dqs}\) :
-
\(\overline{u}_{dqs} = [\overline{u}_{ds} \, \overline{u}_{qs} ]^{T}\)
- \(i_{ds} /i_{qs}\) :
-
d Axis/q axis components of the stator current (A)
- \(i_{dqs}\) :
-
\(i_{dqs} = [i_{ds} \, i_{qs} ]^{T}\)
- \(\overline{i}_{dqc}\) :
-
Short-circuit current of the stator under ITSCF (A)
- \(\overline{i}_{dqck}\) :
-
\(k = 1,2,3\), Short-circuit currents of phases a, b, and c (A)
- \(i^{\prime}_{dqs}\) :
-
Equivalent current injected into the fault stator (A)
- \(i_{dqr}\) :
-
Equivalent current injected into the rotor (A)
- \(Q\left( {\theta_{c} } \right)\) :
-
Matrix depending on the short-circuit angle \(\theta_{c}\)
- \(P\left( {\theta_{r} } \right)\) :
-
Transformation matrix
- \(Q_{ck}\) :
-
\(k = 1,2,3\), Short-circuit elements of phases a, b, and c
- \(R_{s} /R_{r}\) :
-
Stator/rotor resistance (\(\Omega\))
- \(L_{f} /L_{m}\) :
-
Stator/mutual inductance (H)
- \(\phi_{ds} /\phi_{qs}\) :
-
d Axis/q axis components of the stator flux linkages (Wb)
- \(\phi_{dqs}\) :
-
\(\phi_{dqs} = [\phi_{ds} \, \phi_{qs} ]^{T}\)
- \(\phi_{dr} /\phi_{qr}\) :
-
d Axis/q axis components of the rotor flux linkages (Wb)
- \(\phi_{dqr}\) :
-
\(\phi_{dqr} = [\phi_{dr} \, \phi_{qr} ]^{T}\)
- \(\omega\) :
-
Rotor electrical frequency (rad/s)
- \(u_{abc}\) :
-
\(u_{abc} = [u_{a} ,u_{b} ,u_{c} ]\), sample voltage of the motor (V)
- \(i_{abc}\) :
-
\(i_{abc} = [i_{a} ,i_{b} ,i_{c} ]\), sample current of the motor (A)
References
Abdallah, H., Benatman, K.: Stator winding inter-turn short-circuit detection in induction motors by parameter identification. IET Electr. Power Appl. 11(02), 272–288 (2017)
Bilal, H., Heraud, N., Roy Sambatra, E.J.: Detection of inter-turn short-circuit on a doubly fed induction machine with D-Q axis representation. In: 2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON), pp. 1–4 (2020)
Rabbi, S.F., Kahnamouei, J.T., Liang, X., Yang, J.: Shaft failure analysis in soft-starter fed electrical submersible pump systems. IEEE Open J. Ind. Appl. 1, 1–10 (2020)
Afrizal, N., Ferrero, R.: Leakage error compensation in motor current signature analysis for shaft misalignment detection in submersible pumps. IEEE Trans. Instrum. Meas. 69(11), 8821–8830 (2020)
Kumar, P.N., Isha, T.B.: FEM based electromagnetic signature analysis of winding inter-turn short-circuit fault in inverter fed induction motor. CES Trans. Electr. Mach. Syst. 3(03), 309–315 (2019)
Lasjerdiand, H., Tootoonchian, F.: Improving the accuracy of wound-rotor resolvers under inter-turn short circuit faults. IEEE Sens. J. 21(05), 5944–5951 (2021)
Ballal, M.S., Ballal, D.M., Suryawanshi, H.M., Mishra, M.K.: Wing technique: a novel approach for the detection of stator winding inter-turn short circuit and open circuit faults in three phase induction motors. J. Power Electr. 12(01), 208–214 (2012)
Qi, Y., Zafarani, M., Akin, B., Fedigan, S.E.: Analysis and detection of inter-turn short-circuit fault through extended self-commissioning. IEEE Trans. Ind. Appl. 53(03), 2730–2739 (2017)
He, Y.-L., et al.: Impact of stator interturn short circuit position on end winding vibration in synchronous generators. IEEE Trans. Energy Convers. 36(02), 713–724 (2021)
Wang, L., Wang, Y., Xu, D., Fang, B., Liu, Q., Zou, J.: Application of HHT for online detection of inter-area short circuits of rotor windings of turbo-generators based on the thermodynamics modeling method. J. Power Electr. 11(05), 759–766 (2011)
Jannati, M., Idris, N.R.N., Aziz, M.J.A.: Performance evaluation of the field-oriented control of star-connected 3-phase induction motor drives under stator winding open-circuit faults. J. Power Electr. 16(03), 982–993 (2016)
Tian, L., Wu, F., Shi, Y., Zhao, J.: A current dynamic analysis based open-circuit fault diagnosis method in voltage-source inverter fed induction motors. J. Power Electr. 17(03), 725–732 (2017)
Cui, R., Fan, Y., Li, C.: On-line inter-turn short-circuit fault diagnosis and torque ripple minimization control strategy based on OW five-phase BFTHE-IPM. IEEE Trans. Energy Convers. 33(04), 2200–2209 (2018)
Burkart, R.M., Tsoumas, I.P.: In-depth analytical investigation of induction motor short-circuit currents. In: 2018 XIII International Conference on Electrical Machines (ICEM), pp. 2371–2377 (2018)
Eftekhari, M., Moallem, M., Sadri, S., Hsieh, M.: Online detection of induction motor’s stator winding short-circuit faults. IEEE Syst. J. 8(04), 1272–1282 (2014)
Bachir, S., Tnani, S., Trigeassou, J., Champenois, G.: Diagnosis by parameter estimation of stator and rotor faults occurring in induction machines. IEEE Trans. Ind. Electr. 53(03), 963–973 (2006)
Nguyen, V., Wang, D., Seshadrinath, J., Nadarajan, S. Vaiyapuri, V.: Fault severity estimation using nonlinear Kalman filter for induction motors under inter-turn fault. In: IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society, pp. 1488–1493 (2016)
Liu, H., Huang, J., Cheng, M., Hou, Z., Zhao, L.: Stator inter-turn fault detection for the converter-fed induction motor based on the adjacent-current phase-shift. In: 2014 17th International Conference on Electrical Machines and Systems (ICEMS), pp. 981–987 (2014)
Funding
This research was funded by Open Foundation 2019 of China Electric Power Research Institute, Grant no [FXB51201901053].
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Appendices
Appendix 1
To further analyze the influence of the ITSCF on the stator current of the motor, the d axis and q axis components of the stator current \(i_{abc}\) have been derived by transforming the synchronized rotating coordinates based on Fig. 12. As can be seen in Fig. 23, when Fig. 23a is the stator current in condition, there is no ITSCF in the experimental motor. Meanwhile, when Fig. 23b is the stator current, the turns of the ITSCF windings are 12. Comparing Fig. 23b with Fig. 23a shows that the fault current includes a large number of harmonic components which can result in motor instability.
Stator current of the motor in the dq coordinate system where the turns of the ITSCF windings are 12: a normal state; b faulty state
It should be noted that only the 12 turns short-circuit state of the ITSCF motor has been considered for emphasizing the distortion influence of the faulty current. Comparing Figs. 23b with 12b shows that the ITSCF significantly distorts the waveform of the stator current, which makes the motor invalid.
Appendix 2
As can be seen in Fig. 24, since the ESM woks in a wellbore with a length of about 2 km, it is difficult to achieve the on-line monitoring of ITSCFs caused by overheating and overpressure. Therefore, to extend the motor inspection period of oil wells it is necessary to develop an approach to localize and identify ITSCFs in real time.
Schematic diagrams of the submersible motor
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Wang, L., Feng, M., Tian, Z. et al. On-line identifying stator winding short-circuit approach for a submersible motor based on faulty current monitoring. J. Power Electron. 22, 1872–1884 (2022). https://doi.org/10.1007/s43236-022-00495-x
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DOI: https://doi.org/10.1007/s43236-022-00495-x