Publicado:

2022-12-30

Número:

Vol. 19 Núm. 2 (2022): Revista Tekhnê

Sección:

Artículos

Three neural architectures implemented in photovoltaic panel anomaly detection and categorization

Tres arquitecturas neuronales implementadas en la detección y categorización de anomalías en paneles fotovoltaicos

Autores/as

  • Kevin S. Sánchez C. Universidad Distrital Francisco José de Caldas
  • Carlos A. Reyes G. Universidad Distrital Francisco José de Caldas

Palabras clave:

Anomalies, diagnosis, learning, neural network, solar panels, training, visual inspection (en).

Palabras clave:

Anomalías, aprendizaje, diagnóstico, entrenamiento, inspección visual, paneles solares, red neuronal (es).

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Resumen (en)

Solar panels are useful and efficient tools. They need to be kept in excellent working condition, but as time goes by, they suffer from external failures manifested in the environment. Therefore, the need for effective monitoring of such systems is highlighted. Neural models are perfect candidates to perform physical damage recognition. In this case, we compare the performance of three artificial neural networks, the multilayer perceptron, the densely connected neural network, and the ResNet-50 network in this identification problem. What is intended to be obtained from this method is the practical demonstration of the use of neural networks to solve real problems.

Resumen (es)

Los paneles solares son herramientas útiles y eficientes. Necesitan mantenerse en excelente estado de funcionamiento, pero a medida que pasa el tiempo, sufren fallos por externos manifestados en el ambiente. Por lo tanto, se resalta la necesidad de hacer un seguimiento efectivo de dichos sistemas. Los modelos neuronales son candidatos perfectos para realizar el reconocimiento de los daños físicos. En este caso, se compara el desempeño de tres redes neuronales artificiales, el perceptrón multicapa, la red neuronal densamente conectada y la red ResNet-50 en este problema de identificación. Lo que se pretende obtener de este método es la demostración práctica del uso de las redes neuronales para solucionar problemas reales.

Referencias

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Cómo citar

APA

Sánchez C., K. S., y Reyes G., C. A. (2022). Three neural architectures implemented in photovoltaic panel anomaly detection and categorization. Tekhnê, 19(2), 35–44. https://revistas.udistrital.edu.co/index.php/tekhne/article/view/20362

ACM

[1]
Sánchez C., K.S. y Reyes G., C.A. 2022. Three neural architectures implemented in photovoltaic panel anomaly detection and categorization. Tekhnê. 19, 2 (dic. 2022), 35–44.

ACS

(1)
Sánchez C., K. S.; Reyes G., C. A. Three neural architectures implemented in photovoltaic panel anomaly detection and categorization. Tekhnê 2022, 19, 35-44.

ABNT

SÁNCHEZ C., K. S.; REYES G., C. A. Three neural architectures implemented in photovoltaic panel anomaly detection and categorization. Tekhnê, [S. l.], v. 19, n. 2, p. 35–44, 2022. Disponível em: https://revistas.udistrital.edu.co/index.php/tekhne/article/view/20362. Acesso em: 31 ene. 2023.

Chicago

Sánchez C., Kevin S., y Carlos A. Reyes G. 2022. «Three neural architectures implemented in photovoltaic panel anomaly detection and categorization». Tekhnê 19 (2):35-44. https://revistas.udistrital.edu.co/index.php/tekhne/article/view/20362.

Harvard

Sánchez C., K. S. y Reyes G., C. A. (2022) «Three neural architectures implemented in photovoltaic panel anomaly detection and categorization», Tekhnê, 19(2), pp. 35–44. Disponible en: https://revistas.udistrital.edu.co/index.php/tekhne/article/view/20362 (Accedido: 31 enero 2023).

IEEE

[1]
K. S. Sánchez C. y C. A. Reyes G., «Three neural architectures implemented in photovoltaic panel anomaly detection and categorization», Tekhnê, vol. 19, n.º 2, pp. 35–44, dic. 2022.

MLA

Sánchez C., K. S., y C. A. Reyes G. «Three neural architectures implemented in photovoltaic panel anomaly detection and categorization». Tekhnê, vol. 19, n.º 2, diciembre de 2022, pp. 35-44, https://revistas.udistrital.edu.co/index.php/tekhne/article/view/20362.

Turabian

Sánchez C., Kevin S., y Carlos A. Reyes G. «Three neural architectures implemented in photovoltaic panel anomaly detection and categorization». Tekhnê 19, no. 2 (diciembre 30, 2022): 35–44. Accedido enero 31, 2023. https://revistas.udistrital.edu.co/index.php/tekhne/article/view/20362.

Vancouver

1.
Sánchez C. KS, Reyes G. CA. Three neural architectures implemented in photovoltaic panel anomaly detection and categorization. Tekhnê [Internet]. 30 de diciembre de 2022 [citado 31 de enero de 2023];19(2):35-44. Disponible en: https://revistas.udistrital.edu.co/index.php/tekhne/article/view/20362

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