In this paper, torsional vibration effects of a planetary gearbox on electrical signatures of a wound-rotor induction generator have been studied in a representative complex electromechanical system through both numerical simulations and experiments. A universal lumped-parameter model has been developed with consideration of impacts of main drive-train mechanical components. This model has been adapted to a reduced-scale wind turbine simulator based on a 5.5-kW three-phase wound-rotor induction generator used for experimental validation at different load conditions. For this system, it has been demonstrated that most of mechanical characteristic frequencies of the planetary gearbox are difficult to be identified in the stator current spectrum. Nevertheless, the proposed approach has been used as an initial stage to assess the effectiveness of noninvasive condition monitoring of a planetary gearbox based on electrical signatures analysis.

In recent years, the use of electroporation process has attracted much attention, due to its application in various industrial and medical fields. Electroporation is a microbiology technique which creates tiny holes in the cell membrane by the applied electric field. The electroporation process needs high-voltage pulses to provide the required electric field. To generate high-voltage pulses, a pulse generator device must be used. High-voltage pulse generators can be mainly divided into two major groups: Classical pulse generators and power electronics-based pulse generators. As their name suggests, the first group is associated with the primary and elementary pulse generators like Marx generators, and the second group is associated with the pulse generators that have been updated with the advancement of power electronics like Modular Multilevel Converters. These two major groups are also divided into several subgroups which are reviewed in detail in this paper. This study reviews the literature presented in the field of pulse power and pulse generators proper for the electroporation process and addresses their strengths and weaknesses. Several tables are provided to highlight and discuss the characteristics of each subgroup. Finally, a comparative study among different groups of pulse generators is performed which is followed by a classification performance analysis.

The performance of multilevel converters (MLCs) is at the risk of uncertainty of DC sources. This issue has a more negative effect on three-phase cascaded H-bridge MLCs (CHB-MLCs) due to more isolated DC sources. DC voltage variation can take place in all phases, but in this paper, the effect of DC voltage variation of one phase on line voltages is considered. This problem can lead to unbalanced line voltages and a lack of third harmonic elimination in a spontaneous way. Therefore, these problems cause to modify the formulation of quarter-wave symmetrical selective harmonic elimination (SHE) for three-phase CHB-MLCs so that the line voltages become resistant to DC voltage variations as well as mitigating third harmonic. To keep line voltages amplitude fixed under variation of DC voltages, it is necessary to take advantage of non-identical modulation indices to exploit the maximum capacity of DC voltages. Furthermore, regarding unequal DC voltages that can appear in numerous states in a phase, a new method based on the average of DC voltages (ADCV) per phase is employed in the formulation of SHE to reduce these states. Finally, both simulation and experimental results are presented to validate the performance of the proposed method.

One of the major challenges of diagnosing rotor symmetry faults in induction machines is severe modulation of fault and supply frequency components. In particular, existing techniques are not able to identify fault components in the case of low slips. In this paper, this problem is tackled by proposing a novel approach. First, a new use of singular spectrum analysis (SSA), as a powerful spectrum analyser, is introduced for fault detection. Our idea is to treat the stator current signature of the wound rotor induction machine as a time series. In this approach, the current signature is decomposed into several eigenvalue spectra (rather than frequency spectra) to find a subspace where the fault component is recognisable. Subsequently, the fault component is detected using some data-driven filters constructed with the knowledge about characteristics of supply and fault components. Then, an inexpensive peak localisation procedure is applied to the power spectrum of the fault component to identify the exact frequency of the fault. The fault detection and localisation methods are then combined in a recursive regime to further improve the diagnosis’ performance particularly at high rotor speeds and small rotor faults. The proposed approach is data-driven and is directly applied to the raw signal with no suppression or filtration of the frequency harmonics with a low computational complexity. The numerical results obtained with real data at several rotation speeds and fault severities, unveil the effectiveness and real-time feature of the proposed approach.

In induction machines (IMs), the characteristic frequency of broken rotor bars (BRB) shows modulations by the fundamental frequency, appearing as sidebands in the motor current signature, and often suffering from frequency leakage. This leakage can obscure fault components, potentially leading to catastrophic motor failure. Effective frequency demodulation must separate fault frequency sidebands from the fundamental frequency, eliminate nearby harmonics, and maintain the fault characteristic amplitude while considering the number of measured phases. To address these challenging tasks, we propose a novel method based on the rectified orthogonal axis technique (ROAT), applied to the stator current. The proposed method preserves the amplitudes of the fault characteristic frequency while transferring the energy of the fundamental frequency to the DC value and the 4th harmonic of the supply frequency (4 f_s ). This frequency shift is crucial for fault diagnosis in inverter-fed induction machines, particularly at low speeds. Our extensive simulations and experiments on motors with several broken rotor bars under single and three-phase conditions demonstrate the high efficiency and performance of the proposed approach.

Low-frequency torque oscillations (LTOs) characteristic components emerge in the stator current spectrum of induction machines (IMs) as additive frequencies near the rotor asymmetry fault (RAF) indices especially in gearbox-based electromechanical system. The interactions between these two components make the fault detection process complicated and lead to false alarm. In this paper, a new technique for detection and separation of RAF from LTOs in IMs based on single phase stator current data is proposed. The method benefits from a novel pre-processing stage based on several sign functions. Hence, a two-axis rotating reference frame with a single phase of stator current of IMs with no prior knowledge of the rotational speed is introduced. The proposed method maps the static reference frame obtained through single stator current and its associated Hilbert transform to the proposed rotating reference frame which can separate the effects of LTOs from RAF, effectively. The validity of the proposed technique is tested through theoretical analysis, and experiments in both steady-state and transient conditions. In this regard, Synchro-squeezing Wavelet Transforms (SWT) is used for time-frequency analysis of faulty stator current in transient conditions. The obtained results confirm the effectiveness of the proposed approach to separate the RAF characteristic frequency from LTOs even in line-fed IMs applications.