A critical factor in industrial production maintenance is decision‐making in fault diagnosis. Motor current signature analysis (MCSA) is an established condition‐based maintenance method to make fault diagnosis in induction motors (IMs). The occurrence of multiple interacting faults, as well as emergent behaviour, can be tackled efficiently especially when MCSA is combined with distributed problem‐solving artificial intelligence (AI) techniques. Therefore, in this study, an intelligent multi‐agent system (MAS) is presented to make decisions on the fault conditioning of a three‐phase squirrel cage IM. The incorporated agents represent different health conditions of the same IM, with faults that may occur in the rotor bars. All agents utilise an AI method, and use for training MCSA experimental data. A supervisor agent (SA) initially communicates with agents employing feed‐forward artificial neural networks trained with the back‐propagation algorithm and performs the final fault diagnosis by evaluating their responses. When a decision cannot be made on the fault type, the SA employs another agent that uses the k‐nearest neighbour rule. The proposed method achieves high fault diagnosis accuracy. Its performance is also compared with results previously obtained from the same motor when an adaptive neuro‐fuzzy inference system combined with a subtractive clustering method had been used.

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An alternative to traditional low‐speed/high‐torque drive systems, which are currently used in industry, could be the use of a permanent magnet synchronous motor directly coupled to the load and running at low speed, instead of the induction motor along with its mechanical transmission parts. The paper—in this context—deals with the analytical design procedure, optimization, and evaluation of such a motor (5 kW/50 rpm) and focuses on 2 topologies, ie, with inner and outer rotor. Finite element method designs of the permanent magnet machines are implemented as solutions of a complex optimization problem and several goals (multiobjectives) are considered (ie, machine weight minimization or efficiency maximization) with respect to relevant constraints. Three optimization methods are adopted and applied and a weighted cost function is proposed. The effectiveness of our problem design formulation approach and the use of these methods, in finding alternative and competitive permanent magnet synchronous motor designs, are also evaluated. The results reveal satisfactory design solutions and present acceptable performance. Moreover, by means of simulations, the application of several commercially available ferromagnetic materials for the motors' stator and rotor cores is performed. Last but not least, the effect of pole‐arc per pole‐pitch ratio along with the magnets length variation is also investigated.

The design of electrical machines is gaining more popularity in the last years especially in electrical engineering courses. However, commonly‐used teaching techniques seem to limit students' understanding and prevent the attainment of the learning objectives. The competence of this subject can be significantly improved when a practical approach based on the use of computer‐aided educational tools is followed. Thus, this paper proposes an effective and user‐friendly educational tool, which has been developed and successfully implemented in post‐graduate courses in order to facilitate the conception of brushless direct current (BLDC) machines design aspect. At first, a step‐by‐step design procedure is analytically described and then the main tool's characteristics and capabilities are also presented. Finally, its impact assessment has been conducted and the derived results revealed that its application could be extended to the design of various types of electrical motors and generators.

Abstract.Most of the electrical machines design studies found in literature lie on the concept that the design under investigation (and optimization) focuses mainly on the geometrical aspects of the machine and thus takes into account only a certain ferromagnetic material (i.e. iron) for its parts. These studies, give little or no information about the influence of material alternatives on the same (and optimized) design. From a manufacturers' point of view though, this information is crucial especially nowadays that there are a lot of commercially available materials in the market. In this context, this paper presents the results of a research project in the design stage of an energy efficient three phase squirrel cage induction motor (SCIM), by investigating the effects of several soft magnetic materials (adopted for its stator and/or its rotor parts) on multiple quantities of primary concern such as: efficiency, power factor, output torque, losses, weight and cost. After a brief proposed design procedure, a total of twenty-two different materials from recent manufacturers' data were examined. Also, the main electromagnetic analysis was performed through commercial analysis software. Simple ranking methods are also proposed here for different application areas and the results obtained are then thoroughly discussed and commented.

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