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A Kalman Filter Based Technique for Stator Turn-Fault Detection of the Induction Motors

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Veröffentlicht/Copyright: 18. November 2017

Abstract

Monitoring of the Induction Motors (IMs) through stator current for different faults diagnosis has considerable economic and technical advantages in comparison with the other techniques in this content. Among different faults of an IM, stator and bearing faults are more probable types, which can be detected by analyzing signatures of the stator currents. One of the most reliable indicators for fault detection of IMs is lower sidebands of power frequency in the stator currents. This paper deals with a novel simple technique for detecting stator turn-fault of the IMs. Frequencies of the lower sidebands are determined using the motor specifications and their amplitudes are estimated by a Kalman Filter (KF). Instantaneous Total Harmonic Distortion (ITHD) of these harmonics is calculated. Since variation of the ITHD for the three-phase currents is considerable in case of stator turn-fault, the fault can be detected using this criterion, confidently. Different simulation results verify high performance of the proposed method. The performance of the method is also confirmed using some experiments.

Appendix

Kalman filter process:

1. Set initial estimate of the state vector and its error covariance matrix (X^nand Pn)

2. Compute the filter gain at instant n by: Kn=PnhhTPnh+rn

3. Update the estimate using the measurement at instant n by: X^n+=X^n+Kn(ynhTX^n)

where, q=˙E{ψn2},rn=˙E{vn2}, X^n=˙E^{Xn|yn1,...,yn}is the a priori estimate of the state vector Xn in the nth stage using the observations y1 to yn−1, and X^n+=˙E^{Xn|yn,...,y1}is the a posteriori estimate of this state vector after using the nth observation yn. PnandPn+are the state vector covariance matrices before and after using the nth observation, respectively and are defined similarly.

4. Compute the error covariance for the update estimate using: Pn+=PnKnhTPn

5. Project the filter ahead as: Pn+=PnKnhTPnX^n+1=AnX^n,P^n+1=AnPn+AnT+qnbbT

6. Start from 2.

Nomenclature

if

Stator short-circuit current

Lp

Mutual inductance between stator windings

Lg

Self-inductance of the stator windings

nf

Number of short-circuit turns

ns

Total number of stator winding in each phase

Pandp

Number of IM poles and pole pairs, respectively

rf

Stator short-circuit resistance

rsabc

Three-phase stator winding resistances

rrabc

Three-phase rotor winding resistances

Tem

Electromagnetic torque

Tmech

The load torque

Tdamp

The damping torque

usabcandisabc

Three-phase stator voltages and currents

urabcandirabc

Three-phase rotor voltages and currents

λsabc

Three-phase stator fluxes

λrabc

Three-phase rotor fluxes

λgαβ

Leakage flux

λmαβ

Magnetizing flux

λf

Stator short-circuit flux

ωr

The rotor velocity

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Received: 2017-4-16
Accepted: 2017-11-10
Published Online: 2017-11-18

© 2017 Walter de Gruyter GmbH, Berlin/Boston

Heruntergeladen am 17.4.2026 von https://www.degruyterbrill.com/document/doi/10.1515/ijeeps-2017-0071/html
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