Electrical monitoring under transient conditions: a new paradigm in electric motors predictive maintenance
[EN] Electric motors condition monitoring is a field of paramount importance for industry. In recent decades, there has been a continuous effort to investigate on new techniques and methods that are able to determine the health of these machines with high accuracy and reliability. Classical methods...
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/166213 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/166213 |
| Access Level: | acceso abierto |
| Palabra clave: | Induction motor Fault diagnosis Electrical monitoring Transient analysis Rotor Reliability Predictive maintenance Wavelet transforms Current Stray flux INGENIERIA ELECTRICA |
| Sumario: | [EN] Electric motors condition monitoring is a field of paramount importance for industry. In recent decades, there has been a continuous effort to investigate on new techniques and methods that are able to determine the health of these machines with high accuracy and reliability. Classical methods based on the analysis of diverse machine quantities under stationary condition are being replaced by modern methodologies that are adapted to any operation regime of the machine (including transients). These new methods (especially those based on motor startup signal monitoring), that imply the use of advanced signal processing tools, have shown a great potential and have provided spectacular advantages versus conventional approaches enabling, among other facts, a much more reliable determination of the machine health. This paper reviews the background of this recent condition monitoring trend and shows the advantages of this new approach, with regards to its application to the analysis of electrical quantities. Examples referred to its application to real motors operating in industry are included, proving the huge potential of the transient-based approach and its benefits versus conventional methods. |
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