Three-phase induction motor loading estimation based on Wavelet Transform and low-cost piezoelectric sensors

Against the backdrop of high-level industrial process monitoring, the enhancement of sensor-based solutions to increase the efficiency of predictive maintenance plans and anticipate equipment failures has been the focus of several studies. Among the industrial machinery, three-phase induction motors...

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Detalhes bibliográficos
Autores: Lucas, Guilherme Beraldi [UNESP], Castro, Bruno Albuquerque de [UNESP], Rocha, Marco Aurelio [UNESP], Andreoli, Andre Luiz [UNESP]
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:Brasil
Recursos:Universidade Estadual Paulista (UNESP)
Repositorio:Repositório Institucional da UNESP
Idioma:inglés
OAI Identifier:oai:repositorio.unesp.br:11449/197075
Acesso em linha:http://dx.doi.org/10.1016/j.measurement.2020.107956
http://hdl.handle.net/11449/197075
Access Level:acceso abierto
Palavra-chave:Wavelet Transform
Piezoelectric sensors
Non-destructive techniques
Acoustic emission
Descrição
Resumo:Against the backdrop of high-level industrial process monitoring, the enhancement of sensor-based solutions to increase the efficiency of predictive maintenance plans and anticipate equipment failures has been the focus of several studies. Among the industrial machinery, three-phase induction motors (TIMs) stand out as protagonists due to their operational qualities and easy acquisition. In this context, the main goal of this work is to assess the application of low-cost piezoelectric sensors to estimate the loading of a TIM by applying the Wavelet transform (WT). Therefore, this novel technique may offer a helpful control tool for TIM powered processes. The proposed approach offers the benefit of being a non-destructive technique (NDT) for industrial monitoring. In addition to the loading estimation, the results also outlined the capability of the piezoelectric sensor for AE signal analysis. Finally, this work demonstrates that the loading can modify the vibration pattern in TIMs, allowing the proposed estimation. (C) 2020 Elsevier Ltd. All rights reserved.