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This paper addresses the diagnostics of inter-turn short-circuit faults in the stator windings of symmetrical six-phase 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 zero-sequence 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 are becoming a potential solution for several high-power applications since they provide intrinsic fault-tolerance capability. Due to the various stator phase arrangements, standard fault detection techniques are unfeasible and cannot be considered to diagnose faults in the various configurations of multiphase machines, especially those employing closed-loop control strategies, thus precluding Fault Tolerant Operating (FTO) conditions. This article evaluates two distinctive indicators for diagnosing both inter-turn short-circuit faults (ITSCFs) and open-circuit faults (OCFs), resorting to the Short Time Least Square Prony's algorithm (STLSP). The indicators are employed in an asymmetrical six-phase induction motor (ASPIM) drive, controlled by a model predictive control (MPC) algorithm. MPC is selected since it offers an attractive control scheme for the regulation of multiphase electric drives, exploiting their inherent advantages. A variety of operating scenarios confirm the excellent generalization capability of the proposed indicators, high accuracy and robustness, along with the ability to distinguish between the occurrence of motor ITSCFs and converter OCFs, under FTO conditions.

This paper investigates an optimal model-free control design for a synchronous reluctance motor (Syn-RM) with unknown nonlinear dynamic functions, parameter variations, and disturbances. The idea is to combine a predictive control with a time-delay estimation technique (TDE) in order to successfully deal with the system’s uncertainties and make the Syn-RM control scheme easy to implement in real-time. This model-free control strategy comprises two cascade control loops namely outer and inner loops. The outer loop is designed for the mechanical part of Syn-RM to ensure the convergence of the speed dynamics by using a proportional-integral controller while the inner loop is developed to control the uncertain dynamics of currents via an optimal robust controller. In the proposed current loop, the predictive control is enhanced by the inclusion of ultra-local model theory where dynamic functions and disturbances are estimated by instantaneous input-output measurements of the Syn-RM using the TDE approach. Moreover, a particle swarm optimization (PSO) algorithm is also proposed to find the optimal design parameters to improve the dynamic performances of the closed-loop control system. Numerical validation tests of the proposed TDE-based model-free predictive current control (TDE-MFPCC) method are performed in the simulation environment of the Syn-RM system, and the results show the robustness and the effectiveness of the proposed TDE-MFPCC compared to the conventional model-based PCC.

In recent years, the adoption of synchronous reluctance machine (SynRM) drives for safety-critical equipment has witnessed notorious growth. The difficulties inherent to monitoring and fault diagnostics of SynRM drives are highly prominent. Interturn short-circuit faults (ITSCFs) are among the failure modes, which are most critical and, simultaneously, more challenging to identify, in all types of motor drives. Still, the effective diagnostic task becomes even more challenging in SynRM drives because of the harmonic pollution and intricated control configuration. To overcome the aforementioned challenges, the current research proposes a universal and effective online diagnostics technique, based on the computation and monitoring of a relevant severity factor, 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’s estimation and reduced requirements regarding variables’ measurements make the proposed approach extremely advantageous for motor drives with complex control architecture and operating conditions. The experimental results demonstrate the excellent generalization capability of the proposed method, as well as high accuracy and robustness. To confirm the claims, the proposed technique is implemented on a 2.2-kW SynRM drive, tested in both healthy and faulty conditions.

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 research investigates the significant role of Industrial Internet of Things (IIoT) to enable Coopetition Network Practices (CNPs) in enhancing the performance of Small and Medium Enterprises (SMEs) within the context of global digital supply chains. Employing a quantitative approach, our study reveals that CNPs contribute to a noTable 51.0 % improvement in factors determining customer satisfaction. This underscores the strategic importance of blending competition with collaboration to refine production processes and align with consumer expectations. Additionally, the research presents a remarkable 69.1 % boost in operational consistency and reports substantial progress in manufacturing flexibility and the value-to-weight ratio, witnessing increases of 125.8 % and 33.2 %, respectively. These improvements are pivotal in optimizing production resources, which in turn, have led to a 29.3 % decrease in customer complaints and a 15.6 % rise in on-time delivery rates. Conversely, a slight decline in the consistency of the value-to-weight ratio was observed, pointing to potential areas for future research. The findings decisively show that CNPs offer concrete advantages by enhancing customer satisfaction determinants and operational efficiency in SMEs. The paper advocates for future studies to directly measure customer satisfaction and to formulate actionable guidelines for the effective implementation of coopetition strategies. This proposed research direction aims to provide solutions to the manufacturing sector's emerging challenges, thereby promoting competitive advantage and growth in the digital era.

Three-phase induction motors are widely used in industrial facilities, where the maintenance of these machines is preponderant for industrial processes. Recent research reports that vibration-based data acquisition is the most common approach to perform bearing condition monitoring because it can extract more relevant information. However, the acquisition of vibration-based signals is expensive, requiring accelerometers and other external devices to transmit and process the signal information. Otherwise, current-based signals are directly measured by the supply system or inverters, enabling the current-based data acquisition in most industrial cases. In this context, this work introduces a new current-based method to identify bearing damages, applying artificial intelligence algorithms. Experimental and on-site tests present promising results, validating this approach for bearing damage diagnosis.

This paper proposes a single fault diagnostic method for regenerative permanent magnet synchronous machine drives with the ability to handle multiple insulated gate bipolar transistor faults, single current sensor fault, and rotor-position disconnection. The considered faults are discriminated, and the faulty device is correctly identified in each case. The robustness against false alarms is improved by using adaptive thresholds and normalized diagnostic variables. The proposed algorithm requires the information given by current sensors and the rotor position sensor that are already available from the drive system, without requiring a high computational burden. Simulation and experimental results are presented to validate the effectiveness of the considered algorithm for both motoring and regenerative operations.

ABSTRACTThis paper presents a non-isolated DC–DC converter for fuel-cell electric vehicle applications. An H-infinity control, based on mixed sensitivity, applied to a three-phase interleaved boost converter, is proposed. This controller is intended for an outer voltage loop and an inner current loop, to ensure a high stability, especially of the dynamic responses, under any operating conditions. The proposed H-infinity controller for the fuel cell system is implemented in a digital signal processor, thus ensuring both excellent reference tracking and disturbance rejection properties.

ABSTRACTDuring the bovine spongiform encephalopathy (BSE) epidemic, Portugal was the third most affected country. As a result of a successful national eradication plan, the number of BSE affected animals has been progressively declining in Portugal with no cases identified in 2013. However, within the scope of this active surveillance scheme, we have identified the first H-type BSE case born after the introduction of the reinforced ban in fallen stock. Here, we report the phenotypic features of this case and the analysis of the protein coding sequence of prnpas well as the prnppromoter and intron 1 insertion-deletions.

Fault-tolerant permanent magnet synchronous generator drives might play an important role in improving the reliability and availability levels of the modern wind turbines. However, the acceptance by the wind turbine industry will be low if its implementation cannot be accomplished in a cost-effective way. In this paper, a low-cost fully integrated fault-tolerant converter with the ability to handle power switch open-circuit faults is proposed. The two topologies proposed for post-fault operation of the grid- and PMSG-side converters are a five-leg converter with a shared leg connected to a phase of the generator and to the transformer neutral point and a three-switch three-phase rectifier, respectively. Both do not require the oversizing of any component of the conventional system in order to operate within a limited range. Moreover, the fault diagnostic technique does not require additional measurements, and the integration into the drive controller of all diagnostic and control algorithms can be performed without great increase of the computational effort. Control strategies are proposed for the considered converter topologies, and their performance is analyzed by means of experimental results.

The objective of this study was to investigate the effects of 17 weeks of swimming exercise on the lipid profile of hypothyroid rats.

This paper introduces a new approach, based on the spectral analysis of the motor current Park's Vector modulus, for detecting the occurrence of rotor cage faults in operating three-phase induction machines. The major theoretical principles of the Extended Park's Vector Approach are described. Both simulation and laboratory test results demonstrate how the presence of rotor cage faults can be effectively detected by the application of this new approach. These results are also correlated with the ones obtained by the conventional motor current spectral analysis and by the classic Park's Vector Approach.