The purpose of this paper is the performance investigation of a Permanent Magnet Synchronous Generator (PMSG) system, suitable for wind power applications and the comparison of the machine electromagnetic characteristics under open and closed control loop implementations. The copper and iron losses are estimated and compared for the above control systems with the use of the Steinmetz-Bertotti loss separation equation. In addition, the effect of the rotating magnetic field on the total losses is studied. The generator is simulated using Finite Element Analysis (FEA), while the rest of the components are connected to the machine model using a drawing window of the FEA software and suitable command files. The close loop control used in the present study results to less losses and greater machine efficiency. The main novelty of the paper is the simulation of the PMSG coupled with a converter and control schemes using FEA, which ensures more accurate results of the whole system and allows the detailed machine electromagnetic study, while the majority of existing papers on this topic uses simulation tools that usually simulate in detail the electric circuits but not the machine. The FEM model is validated by experimental results.

This paper investigates the total demagnetization fault in Axial Flux Permanent Magnet (AFPM) synchronous generator, suitable for wind power applications, using the three-dimensional Finite Element Method (3D-FEM). The machine, in which the demagnetization diagnosis has been investigated, consists of one coreless stator with concentrating winding, embed in resin and two rotors. In the current study, faulty cases of different number and relative position of total demagnetized magnets are studied. Finally, simulation results are compared to experimental results for validation. The stator current spectrum is studied as fault identification mean and it is shown that the fault signatures depend on the number of total demagnetized magnets, the relative position of the magnets on the rotor and the stator winding topology. In addition, there is an investigation of the partial demagnetization fault for comparison purposes. Moreover, analytical expressions for the magnetic flux density in the healthy case and in every faulty case are exported. These novel expressions, related to every demagnetized case, are presented for the first time in the literature.

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.

A new method for detecting demagnetization faults in axial flux permanent magnet synchronous wind generators is presented in this study. Demagnetization faults occur in the case of total or partial loss of the magnetic properties of one or more permanent magnets of the machine. Fault signatures appearing in the current or voltage signal due to a demagnetization fault can often be confused with those produced by eccentricity faults, making the discrimination between the two types of faults difficult. The proposed methodology is based on the analysis of the instant power spectrum of the generator, combined with an estimator to derive the permanent magnet flux, based on the machine equations. Short-Time Fourier Transform is proposed as the means for spectrum analysis to ensure performance during variations of the generator speed. Results derived from the experimental tests are presented, which show that the proposed methodology is capable of detecting demagnetization faults and distinguishing them from eccentricity ones under a wide variety of operating conditions.

This article investigates the neutral voltage difference signal, V_NO 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 V_NO 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 1.5f_s 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, f_s. 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.

This article sums up and compares the most important techniques for magnetic sensing of ferromagnetic nanoparticles. In addition, the most well-known magnetic sensing instruments are presented, while the advantages and disadvantages of each instrument category are summarized. Finally, a measurement system based on fluxgate magnetometers is proposed for the magnetic characterization of a cobalt-based material applicable in the catalysis process. The authors conclude that this arrangement can provide ferromagnetic material sensing with the most advantages for this catalysis application. Indeed, as nanoparticle materials can be used in many applications, like catalysis, their properties and the phase of the catalyst should be known at any time. Moreover, as the industrial processes operate at a rapid pace, the need for simple, fast, and low-cost measurement systems that will also enable in vivo material characterization is rising. Consequently, this article aims to propose the best candidate magnetic sensing method as well as the best candidate instrument for every application based on the advantages and disadvantages of each sensor.