Investigation of Static Angular and Axis Misalignment in an AFPM Generator

Barmpatza, Alexandra C.; Kappatou, J. C.; Skarmoutsos, G. A.

doi:10.1109/wemdcd.2019.8887847

Cited by 8 publications

(4 citation statements)

References 18 publications

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“…This di tortion results in faulty spectra with new harmonics related to the fault. According to o previous study [37], the static angular eccentricity in a single-sided rotor AFPM synchr nous generator does not generate new harmonics in the spectra of either the EMF volta or stator current individually. However, as shown in Figure 10, which depicts the V signal spectrum, a signal depending on both the EMF voltage and stator phase curren new harmonics related to the fault were generated compared with the healthy case.…”

Section: Angular Eccentricity Faultmentioning

confidence: 82%

“…In another study by Ogidi et al [36], static eccentricity and short-circuit faults were separated, using vibration analysis and the stator current spectrum for fault diagnosis. In both studies conducted by Barmpatza et al [37,38], static angular eccentricity and axial eccentricity faults were studied utilizing the EMF voltage, the stator current, and the sum of the generator's three-phase EMF voltage values. In another study by Ogidi et al [20], the space harmonics and subharmonics of the current, together with torque ripples, were investigated for static angular eccentricity diagnosis.…”

Section: Introductionmentioning

confidence: 99%

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The Neutral Voltage Difference Signal as a Means of Investigating Eccentricity and Demagnetization Faults in an AFPM Synchronous Generator

Barmpatza

2023

Machines

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This article investigates the neutral voltage difference signal, VNO signal, for fault diagnosis. The aforementioned signal is the signal of the voltage between the common star point of the stator and the common star point of the load. The under-study faults are demagnetization and static eccentricity faults, while the machine in which the faults are investigated is an axial flux permanent magnet (AFPM) synchronous generator, suitable for wind power applications. This study was conducted using a 3D finite element method (3D-FEM), and the machine’s FEM model was validated through experiments. This method is one of the most accurate methods for electrical machine computation, allowing for a detailed study of electromagnetic behavior. The components that constitute the VNO signal were determined using a 3D-FEM software program (Opera 18R2). Subsequently, further analysis was performed using MATLAB R2022b software, and a fast Fourier transform (FFT) was applied to this signal. In all the investigated faulty cases, new harmonics appeared, and the healthy amplitudes of most of the already existing harmonics increased. These findings can be used for fault identification. The analysis revealed that the harmonic frequency of 1.5fs was the most dominant in the case of demagnetization, while in the case of static eccentricity, the most dominant harmonic was a frequency equal to the machine’s operating frequency, fs. The novelty of this study is that this signal has not previously been used for fault identification, especially in AFPM synchronous machines. This signal depends on EMF voltage and stator phase currents but is less sinusoidal. Consequently, it can detect faults in cases where the aforementioned signals cannot be used for detection.

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Section: Angular Eccentricity Faultmentioning

confidence: 82%

Section: Introductionmentioning

confidence: 99%

The Neutral Voltage Difference Signal as a Means of Investigating Eccentricity and Demagnetization Faults in an AFPM Synchronous Generator

Barmpatza

2023

Machines

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“…For example, static angular and axis misalignment fault in a stator coreless SSSR AFPM generator was studied in Ref. [34]; a comparative performance study of three different PCB winding stators for SSSR topology was presented in Ref. [35]; the merits and drawbacks of the coreless PCB stator AFPM motor with SSSR topology for high speed, low‐power applications were explored in Ref.…”

Section: Substantive Analysismentioning

confidence: 99%

A systematic review on current research and developments on coreless axial‐flux permanent‐magnet machines

Habib

Zainuri

Seng

et al. 2022

IET Electric Power Appl

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In recent years, coreless axial-flux permanent-magnet (AFPM) machines have been gaining attention. Being coreless, these machines do not experience eddy current (hence hysteresis losses) and has lower cogging torque leading to higher efficiency. However, limitations such as high leakage flux and weak mechanical structure impede its wide application. The results of a systematic review on coreless AFPM machine research is presented, wherein a total of 123 studies have been selected through the Preferred Reported Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol. About 55% of the articles have been published between 2017 and 2021, indicating recent attention of the researchers on coreless AFPM machines. More than 70% (87 out of 123) of the records have been published by IEEE, which proves the quality and acceptance of the studies. In two-thirds (77 out of 123) of the studies, single-stator double-rotor has been adopted as the machine topology, and in 71.8% (84 out of 123) cases, trapezoidal shape magnets have been used in conventional array. The key research areas on coreless AFPM identified through this review are to produce an efficient design for multiphase and multistage topology and develop lightweight rotor and stator structures.

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“…During recent years, the demagnetization and the eccentricity fault have also been studied in the AFPM synchronous machine. More specifically [2,[8][9][10][11][12][13][14][15][16][17][18][19][20][21]] study the eccentricity fault, while [21][22][23][24][25][26][27][28][29][30] investigate the demagnetization fault in AFPM synchronous machines. In [31] a combined eccentricity and demagnetization fault in a double-sided AFPM synchronous machine using a time analytical model is presented.…”

Section: Introductionmentioning

confidence: 99%

Study of a Combined Demagnetization and Eccentricity Fault in an AFPM Synchronous Generator

Barmpatza

Kappatou

2020

Energies

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This article investigates the combined partial demagnetization and static eccentricity fault in an Axial Flux Permanent Magnet (AFPM) Synchronous Generator. The machine is simulated using 3D FEM, while the EMF spectrum is analyzed in order to export the fault related harmonics using the FFT analysis. Firstly, the partial demagnetization fault, without the coexistence of eccentricity, and both the static angular and axis eccentricity faults, without the coexistence of partial demagnetization, are studied. In the case of eccentricity fault, the phase EMF sum spectrum has also been used as a diagnostic mean, because, when only eccentricity fault exists in the generator (either angular or axis) new harmonics do not appear in the EMF spectrum. Secondly the combination of partial demagnetization fault with static axis and static angular eccentricity is investigated and different comparisons are made when the demagnetization and the eccentricity level changes. The investigation revealed that the combination of eccentricity and demagnetization creates new harmonics in the EMF spectrum. The novelty of the article is that these combined faults are studied for the first time in the international literature, and the phase EMF sum spectrum has not been previously used for eccentricity diagnosis in this machine type.

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Investigation of Static Angular and Axis Misalignment in an AFPM Generator

Cited by 8 publications

References 18 publications

The Neutral Voltage Difference Signal as a Means of Investigating Eccentricity and Demagnetization Faults in an AFPM Synchronous Generator

The Neutral Voltage Difference Signal as a Means of Investigating Eccentricity and Demagnetization Faults in an AFPM Synchronous Generator

A systematic review on current research and developments on coreless axial‐flux permanent‐magnet machines

Study of a Combined Demagnetization and Eccentricity Fault in an AFPM Synchronous Generator

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