Classification of the status of the voltage supply in induction motors using Support Vector Machines

Ramon Perez; Alexander Aguila; Carmen Vasquez

doi:10.1109/TDC.2016.7520012

Classification of the status of the voltage supply in induction motors using Support Vector Machines

Título traducido de la contribución: Clasificación del estado de la alimentación de tensión en motores de inducción mediante máquinas Vectoriales de Apoyo

Ramon Perez
, Alexander Aguila
, Carmen Vasquez

Producción científica: Contribución a una conferencia › Documento

7 Citas (Scopus)

Resumen

© 2016 IEEE. Induction motors represent a mainstay in the industry. Its optimum performance is related to the quality of electrical supply. In this sense, when there are variations in the quality of electricity supply, the induction motor can operate in conditions that can affect its performance and shorten its life. In this paper we propose a monitoring of the voltage condition of the supply voltage in induction motors, through a classification using Support Vector Machines (SVM) to detect and classify these events. The necessary data for defining the events associated with the supply voltage are obtained with the use of ATP software, simulating these different conditions in a low voltage motor and the event classification is carried out with the use of SVM. With the use of this mathematical tool, defined areas of disturbs in the voltage will be established from measurements obtained in the simulation of each of the events, which are considered as perturbations in voltage, such as: overvoltage, undervoltage, voltage unbalance, distortion of the voltage wave, voltage sags and simultaneous combinations of some of these events. Assigning tags to each type of disturbance or disturbance combinations allows us to detect and classify the condition of energy supply in induction motors through the SVM. The results show perfect accuracy in the classification of events in the condition of voltage supply of the induction motor, which represents an alternative to the monitoring of these machines in the industry.

Título traducido de la contribución	Clasificación del estado de la alimentación de tensión en motores de inducción mediante máquinas Vectoriales de Apoyo
Idioma original	Inglés estadounidense
DOI	https://doi.org/10.1109/TDC.2016.7520012
Estado	Publicada - 22 jul. 2016
Evento	Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference - Duración: 22 jul. 2016 → …

Conferencia

Conferencia	Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference
Período	22/07/16 → …

Areas de Conocimiento del CACES

317A Electricidad y energía

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10.1109/TDC.2016.7520012

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Diagnóstico de Fallas y Control Volt-Var Basado en Comportamiento Fasorial de Smart Grid Usando PMU
Carrion Galarza, D. F. (Investigador principal), Aguila Tellez, A. (Investigador Secundario), Perez Pineda, R. E. (Investigador Secundario), Quishpe Ushiña, F. G. (Estudiante Investigador), Jaramillo Perugachi, C. A. (Estudiante Investigador), Benavides Larreina, F. P. (Estudiante Investigador), Pillajo Quijia, J. O. (Estudiante Investigador), Gomez Alban, S. V. (Estudiante Investigador), Caisapanta Tapia, W. H. (Estudiante Investigador), Salazar Alava, E. J. (Estudiante Investigador), Yaguana Gutierrez, G. A. (Estudiante Investigador), Pabon Plaza, F. A. (Estudiante Investigador), Ramos Contero, O. O. (Estudiante Investigador), Pareja Espinoza, J. Y. (Estudiante Investigador), Camacho Vera, R. M. (Estudiante Investigador), Criollo Caisaguano, D. A. (Estudiante Investigador), Jacome Avila, D. A. (Estudiante Investigador), Trujillo Armijos, J. A. (Estudiante Investigador), Villa Endara, V. A. (Estudiante Investigador) & Castillo Muñoz, F. A. (Estudiante Investigador)
1/01/16 → 31/12/16
Proyecto: Investigación y Desarrollo

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title = "Classification of the status of the voltage supply in induction motors using Support Vector Machines",

abstract = "{\textcopyright} 2016 IEEE. Induction motors represent a mainstay in the industry. Its optimum performance is related to the quality of electrical supply. In this sense, when there are variations in the quality of electricity supply, the induction motor can operate in conditions that can affect its performance and shorten its life. In this paper we propose a monitoring of the voltage condition of the supply voltage in induction motors, through a classification using Support Vector Machines (SVM) to detect and classify these events. The necessary data for defining the events associated with the supply voltage are obtained with the use of ATP software, simulating these different conditions in a low voltage motor and the event classification is carried out with the use of SVM. With the use of this mathematical tool, defined areas of disturbs in the voltage will be established from measurements obtained in the simulation of each of the events, which are considered as perturbations in voltage, such as: overvoltage, undervoltage, voltage unbalance, distortion of the voltage wave, voltage sags and simultaneous combinations of some of these events. Assigning tags to each type of disturbance or disturbance combinations allows us to detect and classify the condition of energy supply in induction motors through the SVM. The results show perfect accuracy in the classification of events in the condition of voltage supply of the induction motor, which represents an alternative to the monitoring of these machines in the industry.",

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N2 - © 2016 IEEE. Induction motors represent a mainstay in the industry. Its optimum performance is related to the quality of electrical supply. In this sense, when there are variations in the quality of electricity supply, the induction motor can operate in conditions that can affect its performance and shorten its life. In this paper we propose a monitoring of the voltage condition of the supply voltage in induction motors, through a classification using Support Vector Machines (SVM) to detect and classify these events. The necessary data for defining the events associated with the supply voltage are obtained with the use of ATP software, simulating these different conditions in a low voltage motor and the event classification is carried out with the use of SVM. With the use of this mathematical tool, defined areas of disturbs in the voltage will be established from measurements obtained in the simulation of each of the events, which are considered as perturbations in voltage, such as: overvoltage, undervoltage, voltage unbalance, distortion of the voltage wave, voltage sags and simultaneous combinations of some of these events. Assigning tags to each type of disturbance or disturbance combinations allows us to detect and classify the condition of energy supply in induction motors through the SVM. The results show perfect accuracy in the classification of events in the condition of voltage supply of the induction motor, which represents an alternative to the monitoring of these machines in the industry.

AB - © 2016 IEEE. Induction motors represent a mainstay in the industry. Its optimum performance is related to the quality of electrical supply. In this sense, when there are variations in the quality of electricity supply, the induction motor can operate in conditions that can affect its performance and shorten its life. In this paper we propose a monitoring of the voltage condition of the supply voltage in induction motors, through a classification using Support Vector Machines (SVM) to detect and classify these events. The necessary data for defining the events associated with the supply voltage are obtained with the use of ATP software, simulating these different conditions in a low voltage motor and the event classification is carried out with the use of SVM. With the use of this mathematical tool, defined areas of disturbs in the voltage will be established from measurements obtained in the simulation of each of the events, which are considered as perturbations in voltage, such as: overvoltage, undervoltage, voltage unbalance, distortion of the voltage wave, voltage sags and simultaneous combinations of some of these events. Assigning tags to each type of disturbance or disturbance combinations allows us to detect and classify the condition of energy supply in induction motors through the SVM. The results show perfect accuracy in the classification of events in the condition of voltage supply of the induction motor, which represents an alternative to the monitoring of these machines in the industry.

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M3 - Paper

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Classification of the status of the voltage supply in induction motors using Support Vector Machines

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Proyectos

Diagnóstico de Fallas y Control Volt-Var Basado en Comportamiento Fasorial de Smart Grid Usando PMU

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