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Vibration signal forecasting on rotating machinery by means of signal decomposition and neuro-fuzzy modeling

Autor
Zurita, D.; Delgado Prieto, M.; Saucedo, J.; Cariño , J.A.; Osornio, R.; Ortega, J.A.; Romero, R.
Tipus d'activitat
Article en revista
Revista
Shock and vibration
Data de publicació
2016-09-21
Volum
2016
Pàgina inicial
1
Pàgina final
13
DOI
https://doi.org/10.1155/2016/2683269 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/99553 Obrir en finestra nova
URL
https://www.hindawi.com/journals/sv/2016/2683269/ Obrir en finestra nova
Resum
Vibration monitoring plays a key role in the industrial machinery reliability since it allows enhancing the performance of the machinery under supervision through the detection of failure modes. Thus, vibration monitoring schemes that give information regarding future condition, that is, prognosis approaches, are of growing interest for the scientific and industrial communities. This work proposes a vibration signal prognosis methodology, applied to a rotating electromechanical system and its as...
Citació
Zurita, D., Delgado Prieto, M., Saucedo, J., Cariño , J.A., Osornio, R., Ortega, J.A., Romero, R. Vibration signal forecasting on rotating machinery by means of signal decomposition and neuro-fuzzy modeling. "Shock and vibration", 21 Setembre 2016, vol. 2016, p. 1-13.
Paraules clau
Condition Monitoring, Forecasting, Fuzzy Neural Networks, Machine Learning, Predictive models, Time Series analysis, Vibration analysis.
Grup de recerca
MCIA - Motion Control and Industrial Applications Research Group
PERC-UPC - Centre de Recerca d'Electrònica de Potència UPC

Participants

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