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Comprehensive design analysis of a 3D printed sensor for readiness assessment applications

    1. [1] Lamar University

      Lamar University

      Estados Unidos

    2. [2] University of Alabama, USA
  • Localización: Compel: International journal for computation and mathematics in electrical and electronic engineering, ISSN 0332-1649, Vol. 40, Nº 3, 2021, págs. 414-426
  • Idioma: inglés
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  • Resumen
    • Purpose This paper aims to develop a comprehensive model of a magnetic sensor array that will be operational for a multitude of electric components in continuous and nonintrusive condition monitoring (CM) or in readiness assessment (RA) applications.

      Design/methodology/approach A universal nonintrusive model of a flexible antenna array is introduced to monitor and identify failures in electric machine drives. An adjustable sensor is designed to serve as a RA for a vast range of electrical elements in a typical power system by capturing the low-frequency radiated magnetic fields.

      Findings The optimal placement of the most sensitive radiated fields from several components has been discovered in this case study, enabling the detection of healthy current flow throughout. Thereafter, the short-circuit investigation, representing faulty situations, is implemented and compared with healthy cases.

      Practical implications This sensing technique can be used for nonintrusive CM of components that are out of reach and cannot have the sensor to be held around it such as components in offshore winds, wind energy generation and power and chemical plants.

      Originality/value The results are provided for three commonly used machines with a single sensor array with numerous settings. The three dimensional (3 D) finite element analysis is applied in the structuring of the sensor, detection of the optimum location and recognition of faults in the machines. Finally, based on the setup design, 3 D printing is used for the construction of the sensor array. Thus, the sensor array with fault detection avoids major component failures and increases system reliability/resiliency.


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