Diagnosis and performance analysis of three-phase permanent magnet synchronous motors with static, dynamic and mixed eccentricity

Ebrahimi, Bashir Mahdi; Faiz, Jawad

doi:10.1049/iet-epa.2008.0308

Cited by 78 publications

(42 citation statements)

References 18 publications

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“…In this subsection, author proposes method of feature extraction of loaded synchronous motor -SMOFS- 25 …”

Section: Shorted Methods Of Frequencies Selection-25-expandedmentioning

confidence: 99%

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Fault diagnostics of acoustic signals of loaded synchronous motor using SMOFS-25-EXPANDED and selected classifiers

Głowacz

2016

Teh. vjesn.

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Original scientific paper A system of fault diagnostics of loaded synchronous motor was proposed. Proposed system was based on acoustic signals of loaded synchronous motor. A new method of feature extraction SMOFS-25-EXPANDED (shorted method of frequencies selection-25-Expanded) was proposed. Presented method was analysed for 3 classifiers: LDA (Linear Discriminant Analysis), NN (Nearest Neighbour), SOM (Self-organizing Map). Analysis was carried out for real incipient states of loaded synchronous motor. Acoustic signals generated by motor were used in analysis. The following states of motor were analysed: healthy motor, motor with shorted stator coil, motor with shorted stator coil and broken coil, motor with shorted stator coil and two broken coils. These states are caused by natural degradation of rotating synchronous motor. The results of recognition were good. Proposed method of acoustic signal recognition can be used to protect loaded synchronous motors. Keywords: acoustic signal; fault detection; loaded synchronous motor; recognitionDijagnostika greške akustičkih signala opterećenog sinkronog motora primjenom SMOFS-25-EXPANDED i odabranih klasifikatora Izvorni znanstveni članak Predlaže se sustav dijagnostike greške opterećenog sinkronog motora. Predloženi se sustav zasniva na akustičkim signalima opterećenog sinkronog motora. Predlaže se nova metoda određivanja karakteristika SMOFS-25-EXPANDED (shorted method of frequencies selection-25-expaned -skraćena metoda za izbor frekvencija-25-proširena). Predložena se metoda analizirala u odnosu na tri klasifikatora: LDA (Linear Discriminant Analysis -analiza linearnog diskriminatora), NN (Nearest Neighbour -najbliži susjed), SOM (Self-organizing Map -samoorganizirajuća mapa). Analiza je provedena za stvarno početna stanja opterećenog sinkronog motora. U analizi su iskorišteni akustički signali koje je stvarao motor. Analizirala su se sljedeća stanja motora: ispravan motor, motor sa skraćenim namotajem statora, motor sa skraćenim namotajem statora i prekinutim namotajem, motor sa skraćenim namotajem statora i dva prekinuta namotaja. Do takvih je stanja došlo zbog prirodne degradacije rotirajućeg sinkronog motora. Rezultati analize su dobri. Predložena metoda prepoznavanja akustičkog signala može se primijeniti za zaštitu opterećenih sinkronih motora.

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“…In this subsection, author proposes method of feature extraction of loaded synchronous motor -SMOFS- 25 …”

Section: Shorted Methods Of Frequencies Selection-25-expandedmentioning

confidence: 99%

“…1). The most important profit of the system is that the probable fault of the synchronous motor can be predicted [25]. Moreover incipient faults of motor may cause production and operation shutdowns.…”

Section: Introductionmentioning

confidence: 99%

Fault diagnostics of acoustic signals of loaded synchronous motor using SMOFS-25-EXPANDED and selected classifiers

Głowacz

2016

Teh. vjesn.

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“…Ebrahimi and Faiz [11] monitored the spectrum component of the electromagnetic torque signal for the detection of static, dynamic, and mixed eccentricity faults in PMSMs. They were able to verify the results obtained via simulations with their experimental results.…”

Section: Eccentricity Faults In Pmsmsmentioning

confidence: 99%

Eccentricity fault diagnosis in a permanent magnet synchronous motor under nonstationary speed conditions

Eker¹,

Akar²

2017

Turk J Elec Eng & Comp Sci

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Electric motor faults decrease production capacity and increase maintenance costs. Today, predictive detection based on real-time monitoring and fault detection is taking the place of periodic applications. In this study, a new method is presented for the detection of eccentricity faults in permanent magnet synchronous motors. The motor current and the rotor speed were monitored under stationary and nonstationary speed and different load conditions, after which the fault detection was carried out via angular domain-order tracking method. The obtained results were compared with traditional fast Fourier transform results. It was observed that the suggested method can successfully detect the fault for stationary and nonstationary signals. In addition, the position of the fault-related components are constant independent of the motor current frequency, speed, and load levels.

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“…Furthermore, several researches have been carried out and published utilizing WFA approach which is a powerful method in this realm of study and are briefly dealt with in the following. In several papers [13][14][15][16][17][18][19], WFA and FEM was vastly employed to compute the inductance and to diagnose the faults and also to monitor the electrical machine behavior. In other papers, WFA was utilized to study the unbalanced magnetic pull (UMP) [20] and also FEM was used to perform the spectral analysis of machine parameters to diagnose the fault [21,22].…”

Section: Introductionmentioning

confidence: 99%

Cage-rotor induction motor inter-turn short circuit fault detection with and without saturation effect by MEC model

Naderi

2016

ISA Transactions

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Diagnosis and performance analysis of three-phase permanent magnet synchronous motors with static, dynamic and mixed eccentricity

Cited by 78 publications

References 18 publications

Fault diagnostics of acoustic signals of loaded synchronous motor using SMOFS-25-EXPANDED and selected classifiers

Fault diagnostics of acoustic signals of loaded synchronous motor using SMOFS-25-EXPANDED and selected classifiers

Eccentricity fault diagnosis in a permanent magnet synchronous motor under nonstationary speed conditions

Cage-rotor induction motor inter-turn short circuit fault detection with and without saturation effect by MEC model

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