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Análisis de armónicos de un motor trifásico mediante transformadas integrales para analizar fallas de funcionamiento

 

Harmonic analysis of a three-phase motor through integral transforms to analyze malfunctions

 

Wilson Marcelo Román Vargas.[1], Norma del Pilar Barreno Layedra.[2], Juan Manuel Martínez Nogales.[3] & Jorge Cachuput Gusñay.[4]

Recibido: 14-07-2019 / Revisa= do: 23-07-2019 /Aceptado: 15-08-2019/ Publicado: 10-09-2019=

 Abstract.                                 DOI: https://doi.org/10.33262/cie= nciadigital.v3i3.4..869 

The research establishes a mathematical modelin= g of the study of the harmonics produced in the stator currents of a three-phase squirrel cage motor, considering that the information contained in the sign= al harmonics can indicate the presence of various types of both electrical and= mechanical failures, To perform the simulation of the mathematical model, Matlab Simulink software was used, the assessment of = the mathematical model is given experimentally by correlating the total harmonic distortion value of the current signal of each phase of the stator obtained= in the simulation and comparing with the values ​​established by t= he CONELEC entity in charge of determining the limit values ​​that= a current signal must have in order for a motor to be functioning correctly a= nd not to have any electrical and / or mechanical failure; the analysis of variance was implemented accompanied by the Tuckey test for the evaluation = of results obtaining a difference of 2% between the determined model and an en= gine that is in optimal operating conditions.

Keywords: Harmonic analysis, squirrel cage motor, Simulink, Fourier Transform

Resumen.

La investigación establece una modelación matemática del estudio de los armóni= cos producidos en las corrientes del estator de un motor trifásico jaula de ardilla, considerando que la información contenida en los armónicos de la s= eñal pueden indicar la presencia de diversos tipos de fallas tanto eléctricas co= mo mecánicas, para realizar la simulación del modelo matemático se utilizó el software de Simulink de Matlab, la valoración d= el modelo matemático esta dado de forma experimental al correlacionar el valor= de distorsión armónica total de la señal de corriente de cada fase del estator obtenida en la simulación y comparar con los valores establecidos por el CONELEC entidad encargada de determinar los valores límites que debe tener una señal de corriente para q= ue un motor esté funcionando correctamente y no tenga ninguna falla eléctrica = y/o mecánica; se implementó el análisis de varianza acompañado de la prueba de = Tuckey para la valoración de resultados obteniendo una diferencia del 2% entre el modelo determinado y un motor que se encuentra en condiciones óptimas de funcionamiento.

Palabras claves: Análisis armónico, motor jaula de ardilla, Simulink, Transformada de Fourier.

Introducción

Los motores eléctricos jaula de ardilla tienen una gran presencia en la automatización de los procesos industriales, donde su consumo eléctrico esta dado aproximadamente en un 63% de la energía eléctrica producida según [1],= el estudio realizado en [2] determina que una de las técnicas de mantenimiento predictivo para determinar el estado técnico de las máquinas rotatorias esta dado en función del análisis de los armónicos producidos por los motores, su mal funcionamiento  implica un incr= emento en el consumo de energía, el estado de carga y la temperatura de los rodamientos del motor, el trabajo realizado por [3] determina que los componentes armónicos constituyen parámetros importantes para  el diagnóstico de falla del sistema de = rotor, en este contexto, la presente investigación desarrolla la modelación y simulación de un motor trifásico jaula de ardilla en S= imulink para detectar fallas mediante el análisis de armónicos utilizando la Transformada de Fourier, la misma que nos permite extraer de forma eficient= e y eficaz los componentes armónicos del sistema del rotor.

El estudio realizado por [4] muestra el análisis comparativo entre un motor de inducción  jaula de ardilla trifásico tradicional y un motor de inducción trifá= sico asimétrico alimentado por voltaje monofásico, referenciando este trabajo se determina a la variación del voltaje, frecuencia y velocidad del motor como= los parámetros que son analizados en la presente investigación, en [5] se muest= ra el estudio para la evaluación y clasificación de fallas en el aislamiento eléctrico de los motores de inducción y [6] investiga los diferentes factor= es de desequilibrio utilizados para los motores de inducción, estas investigaciones promueven utilizar las diferentes herramientas tecnológicas para realizar investigaciones sobre problemas de motores.=

En tal virtud, la presente investigación es de carácter experimental comparativo, donde se varían los diferentes parámetros citados anteriormente con la intención de analizar el comportamiento del mo= tor y verificar que los resultados obtenidos se enmarquen en las especificacion= es técnicas de funcionamiento dados por los fabricantes y controlados por el CONELEC, la modelación se realiza considerando el análisis de Fourier, para= lo cual, se obtiene la expansión en Serie de Fourier en su forma trigonométric= a y compleja de la señal continua x(t), se aplica el cálculo numérico ante la d= ificulta de resolver de forma analítica los diferentes integrales de la onda, por lo= que es necesario realizar la discretización de la señal mediante la Trasformada= de Fourier lo cual se logra realizando un muestreo del plano tiempo-frecuencia obteniendo la Transformada Discreta de Fourier la misma que esta implementa= da en Matlab mediante la función fft, y su algoritmo reduce el tiempo de cálculo de  pasos a , la eficiencia del algoritmo requiere considerar una muestra de  puntos de la serie.

Los armónicos son ondas que se presentan tanto en tensión como en corriente y afecta a la calidad de la potencia eléctrica[7]= , e influye directamente en el rendimiento y vida útil del equipo eléctrico [8], específicamente al motor al cual se le proporciona energía eléctrica, se analiza el fenómeno de la distorsión armónica en un motor de inducción trifásico jaula de ardilla, donde los motores de inducción constituyen disp= ositivos de accionamiento muy empleados en el mundo industrial [9], el análisis de e= ste tipo de fenómenos resulta un poco complicado de realizarse manualmente pero existen herramientas informáticas e incluso software y hardware especializa= do para su análisis y monitoreo constante, por esto [10] nos muestras las vent= ajas de la utilización de software muy fuerte en este tipo de análisis como Matl= ab, específicamente con la aplicación Simulink que = es considerado como la herramienta más fuerte y con mayores aplicaciones en simulaciones y cálculo de todo índole.

Este articulo presenta una metodología que emplea = de forma directa el uso de software matemático para una mayor facilidad de cál= culo y de gráficas en comparación de los métodos convencionales, ahorrando mucho tiempo al análisis de los armónicos presentes en motores de inducción trifásicos. La metodología se fundamenta en el análisis experimental de las corrientes armónicas producidas en un motor de inducción trifásico desde el momento en que se estabiliza y el mismo funciona a velocidad, intensidad y corriente nominal para evitar así datos del arranque del motor en donde los datos son muy diferentes a cuando el motor funciona en estado nominal, del desarrollo experimental se determina la relación entre el orden de armónicos utilizados y el margen de error originado.

Metodología

A.    Armónicos 

 Los armón= icos se definen habitualmente con los dos datos más importantes que les caracterizan, que son: La amplitud la misma que hace referencia al valor de= la tensión o intensidad del armónico y el orden que hace referencia al valor d= e su frecuencia referido a la fundamental (50 Hz). Así, un armónico de orden 3 t= iene una frecuencia 3 veces superior a la fundamental, es decir 3 * 50 Hz =3D 15= 0 Hz [11]. En la Figura 1, se visualiza los parámetros ingresados en el Simulink para representar la forma de la onda sin con= tenido de armónicos, con una frecuencia constante de 60Hz y una amplitud constante= de 1 pu.

Figura 1 Valores del motor de inducción jaula de ardilla en= Simulink

La frecuencia de la onda periódica se denomina frecuencia fundamental y los armónicos son señales cuya frecuencia es un múltiplo entero de esta frecuencia.    Cuando una onda peri= ódica no tiene esta forma sinusoidal se dice que tiene contenido armónico, lo cua= l puede alterar su valor pico y/o valor RMS causando alteraciones en el funcionamie= nto normal de los equipos que estén sometidos a esta tensión o corriente. La distorsión armónica total (THD) [11] va ser fundamental para el análisis de fallas mecánicas o eléctricas en el motor jaula de ardilla ya que es una herramienta para definir los efectos de los armónicos en el motor y así pod= er comparar en base a los valores establecidos por la CONELEC para que un motor este en correcto funcionamiento.

Frecu= encia fundamental (f 1): Frecuencia de la onda original (50/60 Hz)

·&nb= sp;        Orden de un armónico (n= ): Número entero dado por la relación de la frecuencia de un armónico a la frecuencia fundamental. Con el orden se determina la frecuencia del armónico (Ejemplo: 5º armónico → 5•50 Hz =3D 250 Hz). [10]

·&nb= sp;        Tasa de distorsión armó= nica (THD) [11]: Relación entre el valor eficaz del residuo armónico de la tensi= ón y/o corriente y el valor de la componente fundamental.

La medición y la result= ante de los armónicos se explica por la distorsión armónica total (THD: Total Harmonics Distortion), el= método de cálculo se fundamenta en la utilización de la norma CEI 61000-2-2 [11] d= onde define el THDF como la relación (en porcentajes) entre el valor eficaz de l= as componentes armónicas y la amplitud de la armónica fundamental

Donde:

U representa los armónicos

B.     El análisis de Fourier = en el estudio de armónicos producidos por un motor

 

En [12], menciona que la transformada de Fourier rápida se usa para cambiar entre dominios espaciales y de frecuenci= a, e indica que este procedimiento se puede aplicar para simular máquinas de inducción con fallas de bobinado, en [13] se determina la relación de conmutación a frecuencias fundamentales entre el contenido armónico más alt= o y más bajo como un criterio de distorsión armónica, en el  trabajo publicado en [14] se encuentra = la formulación del Teorema de Fourier, la ecuación (2) indica que toda onda periódica no sinusoidal puede ser descompuesta como la suma de ondas sinusoidales, mediante la aplicación de la serie de Fourier, siempre y cuan= do se cumplan las siguientes condiciones:

§  Que la integral a lo la= rgo de un periodo de la función sea un valor finito,

§  Que la función posea un número finito de discontinuidades en un periodo, y

§&nb= sp; Que la función posea un número finito de máximos y mínimos en un periodo.

Cualq= uier función con periodo  tiene su representación en series de Fou= rier de acuerdo con la siguiente expresión:

=  

 

Donde   representan los coeficientes de la expan= sión en Serie de Fourier para la función  dado en su forma trigonométrica.

=  

Para el análisis espectral de las ondas es necesario definir la Transformada de Fourier de la señal continua  dada por

Donde la ecuación (3) representa la suma de funciones exponenciales complejas periódicas [15]; la Transformada Discreta de Fourier se define co= mo un operador lineal que actúa sobre un vector de entrada  de  muestras en el dominio de tiempo discret= o y que genera coeficientes  de longitud , la misma que está dado por

 

La transformada rápida de Fourier está dada por

La transformada inversa rápida de Fourier está dada por

Con <= /span>

Para [16], la necesidad de utilizar los algoritmos computacionales de las ecuaciones 4, 5, y 6; están dadas en la necesidad de desarrollar técnic= as avanzadas de diagnóstico de máquinas eléctricas.

La Transformada de Fourier en tiempo corto, el método consiste en dividir la señal no estacionaria en pequeños intervalos donde se supone que= la señal es estacionaria, mediante una función ventana de anchura determinada,= que se desplaza y se multiplica con la señal, al aplicarse la DFT en cada inter= valo se obtiene una distribución tiempo-frecuencia de la señal, este proceso se formula mediante

=  

=

De esta forma se pretende abordar el problema de incertidumbre de Heisenberg [17], en cual manifiesta que no es posible la representación exa= cta de una señal dada en tiempo-frecuencia, salvo se considere intervalos de ti= empo en las cuales existan determinadas bandas de frecuencia.<= /p>

C.      = Simulación del motor de inducción

El software de simulación representa una herramienta importante para desarrollar controladores, simplificando la obtención de los parámetros de = este y además permitiendo visualizar el comportamiento del sistema para diferent= es valores del controlador. Se utiliza como herramienta para la simulación, análisis y obtención de parámetros el Simulink = de Matlab [18], debido a que cuenta con una amplia gama de herramientas para el diseño de sistemas dinámicos, ya sea en función del tiempo o en función de = la frecuencia (transformada de Fourier rápida).

En la Figura 2, se muestra el diseño del motor de inducción seleccio= nado para trabajar, el cual tiene un voltaje nominal de 460V, una frecuencia de = 60Hz que es la frecuencia con la que se maneja la transmisión ecuatoriana de ene= rgía eléctrica y la velocidad nominal que trabaja el motor es de 1750 RPM, ademá= s se presenta el modo de conexión de un motor de inducción en Simulink para analizar sus armónicos en estator y en el rotor.

Figura 2 Motor de inducción jaula de ardilla en Simulink

Resultados

Los datos de corriente en el estator por fase, el THD por fase y los parámetros mecánicos [20] son extrapolados y vectorizados a través del Matl= ab para aplicar los análisis estadísticos descriptivos que permitan definir intervalos de confianza para los errores detectados a la variación de diferentes armónicos.

A.    Señales de las corrientes de estator

La señal de la figura 3 muestra la corriente de las fases del estator con respecto al tiempo como podemos observar al inicio de la señal hay una distorsión lo cual se produce por el arranque del motor y luego se estabili= za llegando al valor nominal de corriente consumido por el motor [21]. Se proc= ede analizar las señales del estator por fase mediante la FFT análisis (transformada rápida de Fourier), con armónicos y sin armónicos.=

<= /span>

Figura 3 Señales de corriente de las fases del estator

B.     Señal de corriente sin armónicos

 

En la figura 4 observam= os una señal de corriente sinusoidal pura que es producida por la fuente de alimentación trifásica de la fase B, la cual no contiene armónicos y esta s= eñal la analizamos en 11 ciclos con una frecuencia fundamental de 60 HZ para hal= lar su FFT y observar el comportamiento de los armónicos en la señal. En este análisis también nos brinda información del THD que es igual a 0.56%.<= /o:p>

Figura 4 Señal de corriente pura del estator de la fase B c= on voltaje nominal y su FFT

C.     Señal con armónicos con voltaje nominal (460v)

Corriente de la fase A = del estator

En la figura 5 observam= os una señal de corriente producida por la fase A del estator con distorsión al inicio esto es debido al arranque del motor y luego se estabiliza debido al comportamiento normal del mismo, la señal se analiza desde que se estabiliz= a a los 0.13 (s) en 7 ciclos con una frecuencia fundamental de 60 Hz para halla= r su FFT y observar el comportamiento de los armónicos en la señal. En este anál= isis también nos brinda información del THD que es igual a 4.53%, lo cual nos in= dica un aumento de armónicos que sería causante de pérdidas en el motor.

Figura = 5 Señal de corriente del estator de la fase A con voltaje nominal y su FFT

Corriente de la fase B = del estator

En la figura 6 observam= os una señal de corriente producida por la fase B del estator con distorsión al inicio esto es debido al arranque del motor y luego se estabiliza debido al comportamiento normal del mismo, la señal se analiza desde que se estabiliz= a a los 0.13 (s) en 7 ciclos con una frecuencia fundamental de 60 Hz para halla= r su FFT y observar el comportamiento de los armónicos en la señal. En este anál= isis también nos brinda información del THD que es igual a 4.74%, lo cual nos in= dica un aumento de armónicos que sería causante de pérdidas en el motor.

Figura = 6 Señal de corriente del estator de la fase B con voltaje nominal y su FFT

Corriente de la fase C = del estator

 En la figura 7 observamos una señal de corriente producida por la fase C del estator con distorsión al inicio esto= es debido al arranque del motor y luego se estabiliza debido al comportamiento normal del mismo, la señal se analiza desde que se estabiliza a los 0.13 (s= ) en 7 ciclos con una frecuencia fundamental de 60 Hz para hallar su FFT y obser= var el comportamiento de los armónicos en la señal. En este análisis también nos brinda información del THD que es igual a 4.99%, lo cual nos indica un aume= nto de armónicos que sería causante de pérdidas en el motor.

 

= <= /span>

Figura = 7. Señal de corriente del estator de la fase C con voltaje nominal y = su FFT

 

Los resultados de la experimentación se muestran en la tabla 1, los armónicos se clasifican segú= n su amplitud (indicada en % con respecto a la fundamental) y señales con armóni= cos a 450 V y 460 V.

 

Tabla= 1. Diferencia de señal pura y con armónicos

FASE=

Señal pur= a

Señal con armónicos a 460V

Señal con= armónicos a 450V

FASE A

0.56%

4.53%

4.36%

FASE B

0.56%

4.74%

4.26%

FASE C

0.56%

4.99%

4.26%

 

Tomando en cuenta los valores permitidos por el CONELEC sobre la calidad de distribución de servi= cio eléctrico del Ecuador, podemos observar que los valores máximos de la tabla= 2 son inferiores a los valores obtenidos de la simulación, tomando en cuenta = que por la situación de la estabilidad de las ondas después del arranque del mo= tor solo se analiza 7 armónicos a partir de que se encuentre en estado estable = el motor.

Tabla 2. Límites de distorsión armónica máxima permisible en corriente para sistemas de 120V a 69,000V [22]

 

 


RELACIÓN

 

LIMITES PARA COMPONENETES ARMÓNICAS IMPARES EN % DE <= /span>

DISTORSIÓN DE DEMANDA TOTAL EN % (%T= DD)

  3 - 11

  11 - 17

17-23

23-35

35-51

 

 < 20

4.0

2.0

1.5

0.6

0.3

5.0

20<

7.0

3.5

2.5

1.0

0.5

8.0

<50

50<

10.0

4.0

4.0

1.5

0.7

12.0

<100

100<

12.0

5.5

5.0

2.0

1.0

15.0

<1000

>1000

15.0

7.0

6.0

2.5

1.4

20.0

 

Para la Fase A, el máxi= mo sugerido por el CONELEC es de 4% mientras que los datos arrojados nos dan un 4.53% a una tensión de 460 V.

 

Para la Fase A, el máxi= mo sugerido por el CONELEC es de 4% mientras que los datos arrojados nos dan un 4.36% a una tensión de 450 v, tomando 450V como la variación mínima de tens= ión en la red eléctrica.

 

Para la Fase B, el máxi= mo sugerido por el CONELEC es de 4% mientras que los datos arrojados nos dan un 4.74% a una tensión de 460 V.

 

Para la Fase B, el máxi= mo sugerido por el CONELEC es de 4% mientras que los datos arrojados nos dan un 4.26% a una tensión de 450 V, tomando 450V como la variación mínima de tens= ión en la red eléctrica.

 

Para la Fase C, el máxi= mo sugerido por el CONELEC es de 4% mientras que los datos arrojados nos dan un 4.99% a una tensión de 460 V.

 

Para la Fase C, el máxi= mo sugerido por el CONELEC es de 4% mientras que los datos arrojados nos dan un 4.26% a una tensión de 450 V, tomando 450V como la variación mínima de tens= ión en la red eléctrica.

=  

= En la tabla 3 se presenta el resumen del análisis realizado determin= ando intervalos de confianza para los índices de tensión y su correspondiente perturbación producida.

Tabla= 3 Intervalos de confianza para los índices de ten= sión=

ÍND= ICE DE TENSIÓN

PER= TURBACIÓN DETECTADAS

THDF< 5%

No existe perturbación

5% < THDF < 10%

Probablemente mal funcionamiento

THDF > 10%

Seguro mal funcionamiento

Para la verificación de la hipótesis entre la comprobación de las me= dias de los armónicos producidos por la simulación del modelo matemático y los valores medios medidos en el motor se obtiene un p-valor de 0.6862 que es superior al valor de 0.05; por lo tanto, no se rechaza   y no se obtiene resultados de un post-h= oc que surgen cuando se rechaza  ,   esto quiere decir que los armónicos producidos por el modelo matemático son virtualmente iguales a los valores reales.

 <= /span>

Conclusiones<= /o:p>

Utilizando los algoritmos del análisis de Fourier implementados en el software Matlab y con la utilización del Simulink se validó de forma experimental la variación en las señales de corriente de las fases para un motor trifásico jaula de ardilla con el fin de conocer la distorsión armónica total (THD), en la simulación se ha logrado determinar = los intervalos de variación se encuentra entre el 1% y 4% considerado como un funcionamiento normal del motor, pero un porcentaje superior al 5% represen= ta un indicador de la presencia de fallas eléctricas o mecánicas en el motor.<= o:p>

Además, por el método de superposición se determinó que la presencia= de los armónicos de mayor orden determina el comportamiento general de un moto= r, de esta forma se puede simular el efecto de cada armónico presente en la on= da que se analiza sobre el comportamiento del motor, que, desde el punto de vi= sta didáctico, permite comparar las características de la máquina sobre la influencia de los diferentes armónicos de tiempo.

La determinación del modelo matemático y su implementación en el Simulink de Matlab permite contar con una herramienta didáctica que facilite el estudio de los armónicos de un motor, en el mismo= que se puede ejecutar diferentes variaciones a los parámetros estudiados, sin q= ue éste hecho afecte significativamente las condiciones físicas de un motor de laboratorio.

 

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[14]=             &nb= sp;         Bollen, M. H., Ribeiro, P. F., Larsson= , E. A., & Lundmark, C. M. (2008). Limits for vo= ltage distortion in the frequency range 2 to 9 kHz. IEEE Transactions on Power Delivery, 23(3), 14= 81-1487.

[15]=             &nb= sp;         Sapena-B= ano, A., Martinez-Roman, J., Puche-Panadero, R., Pin= eda-Sanchez, M., Perez-Cruz, = J., & Riera-Guasp, M. (2018). Induction machine model with space harmonics for fault diagnosis based on the convolution theorem. Internat= ional Journal of Electrical Power & Energy Systems= , 100, 463-481.

[16]=             &nb= sp;         Arahal, M. R., Barrero, F., Ortega= , M. G., & Martin, C. (2016). Harmonic analysis of direct digital control of voltage inverters. Mathematics and Computers in Simulatio= n, 130, 155-166.

[17]=             &nb= sp;         Arcila, J. D. (2010). Armónicos en sistemas eléctricos. ieb s= a, 1-26.

[18]=             &nb= sp;         salazar, l. h. c. (2003, january). Programa en Matlab para analisis y simulacion de armonicos. = In Simposio Internacional sobre la Calidad de la Energía Eléctrica-SICEL(Vol. = 2).

[19]=             &nb= sp;         Bañó, A. S. (2014). Desarrollo de técnicas avanzadas de diagnóstico de máquinas eléctricas válidas para cualq= uier régimen de funcionamiento (Doctoral dissertation, Universitat Politècnica de València).

[20]=             &nb= sp;         Hernández, J. U. V., & Yepez, E. C. (2017). Detección de barras rotas en mot= ores de inducción utilizando la STFT. jóvenes en la ciencia, 3(2), 2383-2387.

[21]=             &nb= sp;         García Santamaría, C. (2017). Anál= isis espectral de señales para la detección de fallos de motores de inducción. <= o:p>

[22]=             &nb= sp;         Oviedo, S. J., Quiroga, J. E., &am= p; Ordóñez Plata, G. (2014). Validación Experimental de la Metodología Motor <= span class=3DSpellE>Current Signature Analysis para un Motor de Inducción de 2 HP. Revista Facultad de Ingeniería Universidad de Antioquia, (70).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

PARA CITAR EL ARTÍCULO IND= EXADO.

 

 

Román Vargas, W., Barr= eno Layedra, N., Martínez Nogales, J., & Cachuput Gusñay, J. (2019= ). Análisis de armónicos de un motor trifásico mediante transformadas integral= es para analizar fallas de funcionamiento. Ciencia Digital, 3(3.= 4.), 249-262. https://doi.org/10.33262/cienciadigital.v3i3.4.869

 


 

 

 

El artículo que se publica es de exclusiva responsabilidad de los autores y no necesariamente reflejan el pensamiento de la Revista Ciencia Digital.

 

El artículo queda en propiedad de la revista y, por tanto, su publicación parcial y/o total en otro medio tiene que ser autoriz= ado por el director de la Revista Cien= cia Digital.

 

 

 

 



[2] Universidad de Fuerzas Armadas ES= PE-Sangolquí, Departamento de Ciencias Exactas Sangolquí, Ecuador. npbarreno@espe.edu.ec

[3] Escuela Superior Politécnica de Chimborazo, Facultad de Recursos Naturales. Riobamba, Ecuador, jumartinez@espoch.edu.ec

[4] Escuela Superior Politécnica de Chimborazo, Facultad de Recursos Naturales. Riobamba, Ecuador, jorge.cachuput@espoch.edu.ec

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www.cienciadigital.org=

                                                                        =                                                ISSN: 2602-8085=

                                                 =                             Vol. 3, N°3.4, p. 249-262, septiembre, 2019

 

Desarrollo & Crecimiento (Volumen Especial)                                                =   Página 239

 

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