Título:
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Industrial process monitoring by means of recurrent neural networks and Self Organizing Maps
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Autor/a:
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Zurita Millán, Daniel; Sala Cardoso, Enric; Cariño Corrales, Jesús Adolfo; Delgado Prieto, Miquel; Ortega Redondo, Juan Antonio
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Otros autores:
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Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica; Universitat Politècnica de Catalunya. MCIA - Motion Control and Industrial Applications Research Group |
Abstract:
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Industrial manufacturing plants often suffer from reliability problems during their day-to-day operations which
have the potential for causing a great impact on the effectiveness and performance of the overall process and the
sub-processes involved. Time-series forecasting of critical industrial signals presents itself as a way to reduce this
impact by extracting knowledge regarding the internal dynamics of the process and advice any process deviations
before it affects the productive process. In this paper, a novel industrial condition monitoring approach based on the
combination of Self Organizing Maps for operating point codification and Recurrent Neural Networks for critical signal
modeling is proposed. The combination of both methods presents a strong synergy, the information of the operating
condition given by the interpretation of the maps helps the model to improve generalization, one of the drawbacks of
recurrent networks, while assuring high accuracy and precision rates. Finally, the complete methodology, in terms of
performance and effectiveness is validated experimentally with real data from a copper rod industrial plant. |
Materia(s):
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-Àrees temàtiques de la UPC::Informàtica::Automàtica i control -Àrees temàtiques de la UPC::Informàtica::Robòtica -Artificial intelligence -Machinery--Monitoring. -condition monitoring -knowledge acquisition -process monitoring -production engineering computing -recurrent neural nets -self-organising feature maps -industrial process monitoring -recurrent neural network -self-organizing map -industrial manufacturing plant -reliability problem -day-to-day operation -critical industrial signal time-series forecasting -knowledge extraction -internal dynamics -productive process -industrial condition monitoring approach -operating point codification -critical signal modeling -copper rod industrial plant -Intel·ligència artificial -Maquinària -- Monitoratge |
Derechos:
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Tipo de documento:
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Artículo - Versión publicada Objeto de conferencia |
Editor:
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IEEE Press
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Compartir:
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