A strategy for interturn short-circuit fault detection in PMSM with partitioned stator windings

Mazzoletti, Manuel A.; Bossio, Guillermo R.; Angelo, Cristian H. De

doi:10.23919/rpic.2017.8214325

Cited by 4 publications

(5 citation statements)

References 11 publications

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“…The PMSM dynamic model with partitioned stator windings that allows us to include the effects of the interturn short‐circuit fault in any phase windings is derived similar to [27]. The PMSM dynamic model including an interturn short‐circuit fault in the a ‐phase winding is given by

v_{normalf, a b c} = R_{normalf a} i_{normalf, a b c} + p L_{normalf a} i_{normalf, a b c} + e_{normalpm, normalf a},

where

v_{normalf, a b c} = {[v_{a 1} v_{a 2} v_{b 1} v_{b 2} v_{c 1} v_{c 2} 0]}^{T}

is the voltage vector,

i_{normalf, a b c} = {[i_{a 1} i_{a 2} i_{b 1} i_{b 2} i_{c 1} i_{c 2} i_{normalf}]}^{T}

is the current vector,

e_{normalpm, normalf a} = {[e_{a 1} e_{a 2} e_{b 1} e_{b 2} e_{c 1} e_{c 2} e_{normalf}]}^{T}

is the induced back‐EMF vector and

p = d / <...>

…”

Section: Pmsm Models With Partitioned Windings Including An Intertumentioning

confidence: 99%

“…For the case,

μ = 0

, adding the voltages on the right of (1) correspond to the healthy PMSM [28]. On the other hand, for

μ \neq 0

, adding voltages,

v_{a} = v_{a 1} + v_{a 2}

, define the faulty PMSM dynamic model for a ‐phase winding, similar to [27]. However, the difference between the measured voltage results as

v_{normalRV a} = v_{a 1} - v_{a 2},

where

v_{normalRV a}

, is the RV of the phase a .…”

Section: Pmsm Models With Partitioned Windings Including An Intertumentioning

confidence: 99%

“…The PMSM dynamic model with partitioned stator windings that allows us to include the effects of the interturn short-circuit fault in any phase windings is derived similar to [27]. The PMSM dynamic model including an interturn short-circuit fault in the a-phase winding is given by v f, abc = R fa i f, abc + pL fa i f, abc + e pm, fa ,…”

Section: Stator Fault In A-phase Windingmentioning

confidence: 99%

“…However, the difference between the relative position of the back-EMF and the output voltage will be constant and small magnitude [32]. Thus, the rotor speed may be estimated from (27) as…”

Section: Pmsm Operating With Stator Fault Under the Non-stationary Comentioning

confidence: 99%

“…where Δ T is the sample/hold interval. From (27), the angular rotor position relative to the stator axis, θ^e, is sampled with a fixed sampling frequency, t = t 0 , t 1 , …, t n , as follows:…”

Section: Pmsm Operating With Stator Fault Under the Non-stationary Comentioning

confidence: 99%

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Interturn short‐circuit fault diagnosis in PMSM with partitioned stator windings

Mazzoletti

Bossio

Angelo

2020

IET Electric Power Applications

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A new signal‐based strategy for stator winding interturn short‐circuit fault detection and isolation in permanent magnet synchronous machines (PMSM) is proposed. The strategy is based on an analysis of the midpoint voltage of the phase windings. A PMSM model with partitioned stator windings including an interturn short‐circuit fault is presented. Unlike the motor current signature analysis methods, the midpoint voltage measurement allows detecting an incipient stator fault even under external disturbances without false alarms. For PMSM generators used in variable‐speed wind turbines, the random changes of wind produce fluctuations in the rotor speed. In this situation, conventional fault detection methods used for the steady‐state condition may produce errors in the fault diagnosis. However, the proposed strategy is capable of rejecting the effects of the non‐stationary speed conditions by resampling the voltage signals at fixed increments of the rotor angular position. Several experimental results in time and frequency‐domain are presented for different speed conditions using a PMSM with modified stator winding.

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v_{normalf, a b c} = R_{normalf a} i_{normalf, a b c} + p L_{normalf a} i_{normalf, a b c} + e_{normalpm, normalf a},

where

v_{normalf, a b c} = {[v_{a 1} v_{a 2} v_{b 1} v_{b 2} v_{c 1} v_{c 2} 0]}^{T}

is the voltage vector,

i_{normalf, a b c} = {[i_{a 1} i_{a 2} i_{b 1} i_{b 2} i_{c 1} i_{c 2} i_{normalf}]}^{T}

is the current vector,

e_{normalpm, normalf a} = {[e_{a 1} e_{a 2} e_{b 1} e_{b 2} e_{c 1} e_{c 2} e_{normalf}]}^{T}

is the induced back‐EMF vector and

p = d / <...>

…”

Section: Pmsm Models With Partitioned Windings Including An Intertumentioning

confidence: 99%

“…For the case,

μ = 0

, adding the voltages on the right of (1) correspond to the healthy PMSM [28]. On the other hand, for

μ \neq 0

, adding voltages,

v_{a} = v_{a 1} + v_{a 2}

, define the faulty PMSM dynamic model for a ‐phase winding, similar to [27]. However, the difference between the measured voltage results as

v_{normalRV a} = v_{a 1} - v_{a 2},

where

v_{normalRV a}

, is the RV of the phase a .…”

Section: Pmsm Models With Partitioned Windings Including An Intertumentioning

confidence: 99%

Section: Stator Fault In A-phase Windingmentioning

confidence: 99%

“…However, the difference between the relative position of the back-EMF and the output voltage will be constant and small magnitude [32]. Thus, the rotor speed may be estimated from (27) as…”

Section: Pmsm Operating With Stator Fault Under the Non-stationary Comentioning

confidence: 99%

Section: Pmsm Operating With Stator Fault Under the Non-stationary Comentioning

confidence: 99%

See 3 more Smart Citations

Interturn short‐circuit fault diagnosis in PMSM with partitioned stator windings

Mazzoletti

Bossio

Angelo

2020

IET Electric Power Applications

Self Cite

View full text Add to dashboard Cite

show abstract

Fault Diagnosis in PMSM with Partitioned Stator Windings−Part II: Interturn Short-Circuit and Static Eccentricity

Mazzoletti

Bossio

et al. 2020

2020 IEEE Congreso Bienal De Argentina (ARGENCON)

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Fault Diagnosis in PMSM with Partitioned Stator Windings−Part I: Experimental Validation with Static Eccentricity

Mazzoletti¹,

Bossio

et al. 2020

2020 IEEE Congreso Bienal De Argentina (ARGENCON)

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A strategy for interturn short-circuit fault detection in PMSM with partitioned stator windings

Cited by 4 publications

References 11 publications

Interturn short‐circuit fault diagnosis in PMSM with partitioned stator windings

Interturn short‐circuit fault diagnosis in PMSM with partitioned stator windings

Fault Diagnosis in PMSM with Partitioned Stator Windings−Part II: Interturn Short-Circuit and Static Eccentricity

Fault Diagnosis in PMSM with Partitioned Stator Windings−Part I: Experimental Validation with Static Eccentricity

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