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The subject of on-line detection and location of inter-turn short circuits in the stator windings of three-phase induction motors is discussed, and a noninvasive approach, based on the computer-aided monitoring of the stator current Parks Vector, is introduced. Experimental results, obtained by using a special fault producing test rig, demonstrate the effectiveness of the proposed technique, for detecting inter-turn stator winding faults in operating three-phase induction machines. On-site tests conducted in a power generation plant, using the diagnostic instrumentation system developed, are also reported.

As one of the most important assets of the industry, it is crucial to fully characterise all failure modes showing potential to degrade the normal operation of induction motors (IMs). One of the failure modes which lacks detailed knowledge and proper diagnostic tools is the inter‐turn short‐circuit (SC) fault. Given the severity of such failure mode, it is pivotal to ensure that incipient fault symptoms are correctly identified, thus preventing critical damages to the IM. Unfortunately, the state‐of‐the‐art does not provide enough data to confirm whether the available diagnostic tools act out in due time to avoid permanent damage to the faulty IM. To evaluate the impacts of this failure mode in the temperature of the stator windings of an IM, this paper presents the results obtained from two alternative thermal models of the same IM, resorting to the lumped parameter thermal network method and to the finite elements method. The results confirm that diagnostic tools reported in the literature might not be effective, failing to correctly diagnose an inter‐turn SC fault and to warrant the lead time required to take actions suitable to prevent permanent damage to the IM.

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Resumo-Com o objetivo de divulgar o potencial e a aptidão de Data Mining Educacional (EDM), como um instrumento de análise e de investigação, no apoio à gestão de instituições dedicadas ao ensino, apresenta-se, no presente artigo, uma sucinta descrição de alguns dos estudos mais relevantes da área. A análise efetuada permite evidenciar as inovações que o EDM tem vindo a promover, bem como as tendências de investigação atuais e futuras. Palavras Chave-data mining educacional, data mining, eficiência institucional.

Abstruct-This paper concerns the design of LinearSwitched Reluctance Machines (LSRM), by evaluating the traction forces under defined speed operation conditions. A new methodology concerning optimised design of LSRM, for. urban systems of electric traction a t low and medium speeds, is proposed. This methodology, supposed to be original, is based on the systematic use of 3 known and fast processing calculation process, in which some changes are made in order to turn it more generic. For each one of the several design machines the respective magnetization curves are calculated, based on the B=f(H) characteristic of the used material, as well as on the calculated machine dimensions. This calculation was made through the linearization of the airgap length mean value between the unaIigned and aligned positions. The simulation of different machines permits the selection of proper model for specific requested application. Simultaneously, machine simulation allows to define the best control strategy for continuous operation.The developed software, for machine simulation, still allows to simulate any LSRM with known magnetization curve I=f( I @ ) . most basic sizing calculations, compurer-based design methods must incorporate simulation capability as an integral part of the design process.". The proposed machine design methodology can be divided in to the following steps:1.

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