Two common defects in induction machines (IMs) are eccentricity and interturn faults, which should be diagnosed to prevent performance degradation and further damage. A popular fault-detection approach is the current signature analysis (CSA), because of its simplicity and nonintrusiveness. Under closed-loop control, it is combined with analogous voltage-reference (VR) signature analysis (VRSA). However, by using these methods in three-phase IMs, it is difficult to discriminate between these faults, which cause similar symptoms. Multiphase machines provide remarkable advantages such as inherent tolerance to open-phase faults. Six-phase IMs are particularly attractive since they allow adopting three-phase converters. Among them, those with symmetrical spatial arrangement of the stator phases offer superior fault tolerance. Nonetheless, the distinction between eccentricity and interturn failures in these IMs has not been addressed so far. This article studies the discrimination between eccentricity and interturn faults in symmetrical six-phase (S6) IMs by CSA or VRSA. It is shown that, conversely to three-phase IMs and most other multiphase IMs, in S6 ones, these two types of failures can be easily distinguished: interturn faults considerably alter the currents or VRs in the so-called $\boldsymbol{x}$ - $\boldsymbol{y}$ plane, whereas eccentricity leads to current/voltage symptoms only in the $\boldsymbol{\alpha} _{\mathbf{1}}$ - $\boldsymbol{\beta} _{\mathbf{1}}$ plane. Experimental results confirm the theory.

In recent years, multiphase machines have been presented as a good alternative to the classical three-phase machines, mainly due to their ability to operate smoothly under fault conditions. Due to multiple stator phase arrangements, existing fault diagnostic (FD) methods are not sufficiently universal and cannot be applied to the multiple configurations of multiphase machines. In this regard, the current research proposes a universal and effective online diagnostics technique based on the computation and monitoring of a relevant severity factor, which is defined as the ratio of the zero, negative and positive voltage symmetrical components. The Short Time Least Square Prony’s (STLSP) approach is used to implement this method online in LabVIEW environment. In addition to the wide applicability of the method, the obviation of any motor parameter estimation and limited requirements regarding variables measurements make the proposed approach extremely advantageous for motors with high number of phases. This article addresses at stator faults in symmetrical six-phase induction machines (6PIM). The proposed method’s experimental results on six-phase motor drive platforms demonstrate the excellent generalization capability of the proposed method, as well as high accuracy and robustness, along with the ability to accurately distinguish between the occurrence of Inter-Turn Short Circuit (ITSC) faults and the presence of Unbalance Supply Voltage (USV) conditions. A 6PIM is put through its paces in both healthy and faulty conditions. The obtained results demonstrate the effectiveness of the proposed method for diagnosing the occurrence of ITSC faults and USV operating conditions with high reliability, fastness and high precision.

This paper addresses the occurrence of stator faults in six-phase induction machines, with a symmetrical winding, operating under both balanced and unbalanced supply voltage conditions. A dynamic model of the motor was developed in Matlab/Simulink environment, taking into consideration the occurrence of inter-turn short circuit faults. To validate the proposed approach, simulation results, covering the full range of operation and different fault severity levels, are compared with the motor experimental performance. The voltages and currents obtained from the simulation present a good agreement with the corresponding experimental results, demonstrating the accuracy of the proposed model

This paper addresses the diagnostics of inter-turn short-circuit faults in the stator windings of symmetrical sixphase induction motors supplied by an unbalanced voltage three-phase system, or under the occurrence of a single-phasing condition. A new approach based on the analysis of the zerosequence component of the apparent power is proposed to diagnose the inter-turn short circuit faults, independently of the presence of unbalanced supply voltages or single-phasing conditions. Additionally, the voltage Park's vector modulus, and the analysis of the rms values of the six-phase motor currents are also considered in the proposed technique, to monitor and detect the existence of unbalanced supply voltage conditions and open-circuit faults, respectively. Experimental results prove the effectiveness of the proposed approach in discriminating between all these conditions.

Multiphase machines have recently been promoted as a viable alternative to traditional three-phase machines. Most experts are looking for strategies to estimate the rotation speed of such complex systems, since speed data are required for high-performance control purposes. Traditionally, electromechanical sensors were used to detect the rotor speed of electric motors. These devices are extremely accurate, but they are also delicate and costly to deploy. New speed estimating algorithms must be created for these situations. This paper looks at how to estimate rotor speed in symmetrical six-phase induction motors (IMs) using a novel strategy for rotor speed estimation based on the Short Time Fourier Transform (STFT) method. The technique is based on tracking the frequencies of the rotor slot harmonics (RSH) seen in most squirrel-cage IM stator currents, thus assuring a broad range of applications. To monitor the RSH, the STFT employs a sliding window to perform the discrete Fourier transform technique, making it more suitable for online use with noisy and nonstationary signals. Experimental tests demonstrate the effectiveness of the suggested approach.

Inter-turn short-circuit faults diagnostics in induction motors under unbalanced supply voltage conditions has been a challenging task since both conditions affect the machine in the same manner. An investigation of two harmonic components (related to the principal slot harmonics) of the alpha-beta plane current modulus signature is addressed to detect stator faults in a symmetrical six-phase induction motor fed by unbalanced voltages. Experimental results, including different load torques, fault severities, and unbalanced supply voltage levels show that the detection of stator faults without being affected by the presence of unbalanced supply voltage conditions can be achieved efficiently without adding complexity to the diagnostics methodology.