Neural network based industrial processes monitoring

Luis P. Sánchez-Fernández; Cornelio Yáñez-Márquez; Oleksiy Pogrebnyak

doi:10.1007/11760191_136

Neural network based industrial processes monitoring

Luis P. Sánchez-Fernández, Cornelio Yáñez-Márquez, Oleksiy Pogrebnyak

Centro de Investigación en Computación (CIC)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This industrial processes monitoring based on a neural network presents low run-time, and it useful for critical time tasks with periodic processing, This method allows the time prediction in which a variable will arrive to abnormal or important values. The data of each variable are used to estimate the parameters of a continuous mathematical model. At this moment, four models are used: first-order or second-order in three types (critically damped, overdamped or underdamped). An optimization algorithm is used for estimating the model parameters for a dynamic response to step input function, because this is the most frequent disturbance. Before performing the estimation, the most appropriate model is determined by means of a feed-forward neural network.

Original language	English
Title of host publication	Advances in Neural Networks - ISNN 2006
Subtitle of host publication	Third International Symposium on Neural Networks, ISNN 2006, Proceedings - Part III
Publisher	Springer Verlag
Pages	933-938
Number of pages	6
ISBN (Print)	3540344829, 9783540344827
DOIs	https://doi.org/10.1007/11760191_136
State	Published - 2006
Event	3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks - Chengdu, China Duration: 28 May 2006 → 1 Jun 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3973 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks
Country/Territory	China
City	Chengdu
Period	28/05/06 → 1/06/06

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10.1007/11760191_136

Cite this

Sánchez-Fernández, L. P., Yáñez-Márquez, C., & Pogrebnyak, O. (2006). Neural network based industrial processes monitoring. In Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings - Part III (pp. 933-938). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3973 LNCS). Springer Verlag. https://doi.org/10.1007/11760191_136

Sánchez-Fernández, Luis P. ; Yáñez-Márquez, Cornelio ; Pogrebnyak, Oleksiy. / Neural network based industrial processes monitoring. Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings - Part III. Springer Verlag, 2006. pp. 933-938 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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author = "S{\'a}nchez-Fern{\'a}ndez, {Luis P.} and Cornelio Y{\'a}{\~n}ez-M{\'a}rquez and Oleksiy Pogrebnyak",

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Sánchez-Fernández, LP , Yáñez-Márquez, C & Pogrebnyak, O 2006, Neural network based industrial processes monitoring. in Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings - Part III. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3973 LNCS, Springer Verlag, pp. 933-938, 3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks, Chengdu, China, 28/05/06. https://doi.org/10.1007/11760191_136

Neural network based industrial processes monitoring. / Sánchez-Fernández, Luis P.; Yáñez-Márquez, Cornelio; Pogrebnyak, Oleksiy.
Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings - Part III. Springer Verlag, 2006. p. 933-938 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3973 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Neural network based industrial processes monitoring

AU - Sánchez-Fernández, Luis P.

AU - Yáñez-Márquez, Cornelio

AU - Pogrebnyak, Oleksiy

PY - 2006

Y1 - 2006

N2 - This industrial processes monitoring based on a neural network presents low run-time, and it useful for critical time tasks with periodic processing, This method allows the time prediction in which a variable will arrive to abnormal or important values. The data of each variable are used to estimate the parameters of a continuous mathematical model. At this moment, four models are used: first-order or second-order in three types (critically damped, overdamped or underdamped). An optimization algorithm is used for estimating the model parameters for a dynamic response to step input function, because this is the most frequent disturbance. Before performing the estimation, the most appropriate model is determined by means of a feed-forward neural network.

AB - This industrial processes monitoring based on a neural network presents low run-time, and it useful for critical time tasks with periodic processing, This method allows the time prediction in which a variable will arrive to abnormal or important values. The data of each variable are used to estimate the parameters of a continuous mathematical model. At this moment, four models are used: first-order or second-order in three types (critically damped, overdamped or underdamped). An optimization algorithm is used for estimating the model parameters for a dynamic response to step input function, because this is the most frequent disturbance. Before performing the estimation, the most appropriate model is determined by means of a feed-forward neural network.

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DO - 10.1007/11760191_136

M3 - Contribución a la conferencia

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SN - 9783540344827

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Advances in Neural Networks - ISNN 2006

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Sánchez-Fernández LP , Yáñez-Márquez C, Pogrebnyak O. Neural network based industrial processes monitoring. In Advances in Neural Networks - ISNN 2006: Third International Symposium on Neural Networks, ISNN 2006, Proceedings - Part III. Springer Verlag. 2006. p. 933-938. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11760191_136

Neural network based industrial processes monitoring

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