Speed Estimator for a Hydraulic System

Erick Narvaez; Pablo Sáenz; Walter Orozco

doi:10.1007/978-3-030-32033-1_6

Speed Estimator for a Hydraulic System

Erick Narvaez, Pablo Sáenz, Walter Orozco

Research Group on Interaction, Robotics and Automatics (GIIRA)

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

Abstract

The estimation of the speed of rotating hydraulic systems (motors) is an important task in processes (control) that merit an exact measurement of the rotating speed. The implementation of a filtering technique based on adaptive filtering algorithms offers a new proposal in the treatment of feedback signals from hydraulic systems (Speed). The implementation of adaptive filtering in obtaining training parameters of Machine Learning algorithms for the estimation of the speed of a variable speed hydraulic system proposes a novel and highly applicable technique. In this article, a speed estimator system for a rotating hydraulic system is proposed using the adaptive filtering technique based on the noise canker topology in conjunction with multilayer neural networks, evaluated by: the mean square error, the absolute average error, the standard deviation and the correlation obtaining values of 0.59, 0.19, 0.23 and 0.99 in comparison with its counterpart of conventional census (transducer). According to the results, the system is appropriate for a speed estimation of the proposed rotary hydraulic system.

Original language	English
Title of host publication	Advances in Emerging Trends and Technologies - Volume 2
Editors	Miguel Botto-Tobar, Joffre León-Acurio, Angela Díaz Cadena, Práxedes Montiel Díaz
Publisher	Springer
Pages	54-62
Number of pages	9
ISBN (Print)	9783030320324
DOIs	https://doi.org/10.1007/978-3-030-32033-1_6
State	Published - 1 Jan 2020
Event	1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019 - quito, Ecuador Duration: 29 May 2019 → 31 May 2019

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1067
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019
Country/Territory	Ecuador
City	quito
Period	29/05/19 → 31/05/19

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

Keywords

Filter
Hydraulic
Neural networks
Noise
Signal
Speed estimator
Transductor

Access to Document

10.1007/978-3-030-32033-1_6

Cite this

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title = "Speed Estimator for a Hydraulic System",

abstract = "The estimation of the speed of rotating hydraulic systems (motors) is an important task in processes (control) that merit an exact measurement of the rotating speed. The implementation of a filtering technique based on adaptive filtering algorithms offers a new proposal in the treatment of feedback signals from hydraulic systems (Speed). The implementation of adaptive filtering in obtaining training parameters of Machine Learning algorithms for the estimation of the speed of a variable speed hydraulic system proposes a novel and highly applicable technique. In this article, a speed estimator system for a rotating hydraulic system is proposed using the adaptive filtering technique based on the noise canker topology in conjunction with multilayer neural networks, evaluated by: the mean square error, the absolute average error, the standard deviation and the correlation obtaining values of 0.59, 0.19, 0.23 and 0.99 in comparison with its counterpart of conventional census (transducer). According to the results, the system is appropriate for a speed estimation of the proposed rotary hydraulic system.",

keywords = "Filter, Hydraulic, Neural networks, Noise, Signal, Speed estimator, Transductor",

author = "Erick Narvaez and Pablo S{\'a}enz and Walter Orozco",

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Narvaez, E, Sáenz, P & Orozco, W 2020, Speed Estimator for a Hydraulic System. in M Botto-Tobar, J León-Acurio, A Díaz Cadena & P Montiel Díaz (eds), Advances in Emerging Trends and Technologies - Volume 2. Advances in Intelligent Systems and Computing, vol. 1067, Springer, pp. 54-62, 1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019, quito, Ecuador, 29/05/19. https://doi.org/10.1007/978-3-030-32033-1_6

Speed Estimator for a Hydraulic System. / Narvaez, Erick; Sáenz, Pablo; Orozco, Walter.
Advances in Emerging Trends and Technologies - Volume 2. ed. / Miguel Botto-Tobar; Joffre León-Acurio; Angela Díaz Cadena; Práxedes Montiel Díaz. Springer, 2020. p. 54-62 (Advances in Intelligent Systems and Computing; Vol. 1067).

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

TY - GEN

T1 - Speed Estimator for a Hydraulic System

AU - Narvaez, Erick

AU - Sáenz, Pablo

AU - Orozco, Walter

PY - 2020/1/1

Y1 - 2020/1/1

N2 - The estimation of the speed of rotating hydraulic systems (motors) is an important task in processes (control) that merit an exact measurement of the rotating speed. The implementation of a filtering technique based on adaptive filtering algorithms offers a new proposal in the treatment of feedback signals from hydraulic systems (Speed). The implementation of adaptive filtering in obtaining training parameters of Machine Learning algorithms for the estimation of the speed of a variable speed hydraulic system proposes a novel and highly applicable technique. In this article, a speed estimator system for a rotating hydraulic system is proposed using the adaptive filtering technique based on the noise canker topology in conjunction with multilayer neural networks, evaluated by: the mean square error, the absolute average error, the standard deviation and the correlation obtaining values of 0.59, 0.19, 0.23 and 0.99 in comparison with its counterpart of conventional census (transducer). According to the results, the system is appropriate for a speed estimation of the proposed rotary hydraulic system.

AB - The estimation of the speed of rotating hydraulic systems (motors) is an important task in processes (control) that merit an exact measurement of the rotating speed. The implementation of a filtering technique based on adaptive filtering algorithms offers a new proposal in the treatment of feedback signals from hydraulic systems (Speed). The implementation of adaptive filtering in obtaining training parameters of Machine Learning algorithms for the estimation of the speed of a variable speed hydraulic system proposes a novel and highly applicable technique. In this article, a speed estimator system for a rotating hydraulic system is proposed using the adaptive filtering technique based on the noise canker topology in conjunction with multilayer neural networks, evaluated by: the mean square error, the absolute average error, the standard deviation and the correlation obtaining values of 0.59, 0.19, 0.23 and 0.99 in comparison with its counterpart of conventional census (transducer). According to the results, the system is appropriate for a speed estimation of the proposed rotary hydraulic system.

KW - Filter

KW - Hydraulic

KW - Neural networks

KW - Noise

KW - Signal

KW - Speed estimator

KW - Transductor

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BT - Advances in Emerging Trends and Technologies - Volume 2

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T2 - 1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019

Y2 - 29 May 2019 through 31 May 2019

ER -

Speed Estimator for a Hydraulic System

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Keywords

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