Influence of position of mq-6 sensor and elapsed time on the concentration detection of LPG in a domestic leak
Descripción del Articulo
Gas leaks in Lima and Ica (Peru) increase every year, causing accidents and irreparable damage to the population. In this article, a controlled leak was produced using a two-burner kitchen and an array of MQ-6 sensors positioned at different angles (45°, 0° and 30°) with respect to the kitchen. The...
| Autores: | , , |
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| Formato: | artículo |
| Fecha de Publicación: | 2022 |
| Institución: | Universidad de Lima |
| Repositorio: | Revistas - Universidad de Lima |
| Lenguaje: | español |
| OAI Identifier: | oai:ojs.pkp.sfu.ca:article/6112 |
| Enlace del recurso: | https://revistas.ulima.edu.pe/index.php/Ingenieria_industrial/article/view/6112 |
| Nivel de acceso: | acceso abierto |
| Materia: | Arduino Matlab machine learning MQ-6 LPG gas detection GLP detección de gas |
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Influence of position of mq-6 sensor and elapsed time on the concentration detection of LPG in a domestic leakInfluencia de la posición del sensor MQ-6 y el tiempo transcurrido en la detección de concentración de GLP en una fuga domésticaBueno Vera, AlejandroLuis Ortiz, Gianfranco Taquía Gutiérrez, José AntonioBueno Vera, Alejandro Luis Ortiz, Gianfranco Taquía Gutiérrez, José AntonioArduinoMatlabmachine learningMQ-6LPGgas detectionArduinoMatlabmachine learningMQ-6GLPdetección de gasGas leaks in Lima and Ica (Peru) increase every year, causing accidents and irreparable damage to the population. In this article, a controlled leak was produced using a two-burner kitchen and an array of MQ-6 sensors positioned at different angles (45°, 0° and 30°) with respect to the kitchen. The results show that, if the kitchen is in a high position (87 cm), the detected concentration is lower, but the detection is faster (6,419 s) if the arrangement is located 50 cm from the origin of the leak. The detection time is between 13,515 s and 21,740 s and the maximum concentration detected is 98 ppm. The best adapted learning model is Support Vector Machine, with an RMSE of 4,61 ppm. It is concluded that the best position for gas detection was at a height of 47 cm above the ground, at 50 cm from the sensor and at an angle of 0°. The detection time is 13,84 s. Finally, it is concluded that 30 seconds of leakage are not enough to reach the harmful limit (147 ppm).Las fugas de gas en Lima e Ica (Perú) aumentan cada año, provocando accidentes y daños irreparables para la población. En esta investigación se produjo una fuga controlada usando una cocina de dos hornillas y un arreglo de sensores MQ-6 dispuestos en distintos ángulos con respecto a la cocina (45°, 0° y 30 °). Se encontró que, si la cocina se ubica en la posición alta (87 cm), la concentración detectada es menor, pero la detección es más rápida (6,419 s) si el arreglo se ubica a 50 cm del origen de la fuga. El tiempo de detección se encuentra entre 13,515 s y 21,740 s y la máxima concentración detectada es de 98 ppm. El modelo de aprendizaje que mejor se adaptó es Support Vector Machine, con un RMSE de 4,61 ppm. Se concluye que la mejor posición para la detección de gas fue a una altura de 47 cm sobre el suelo, a una distancia de 50 cm del sensor y a un ángulo de 0°. El tiempo de detección es de 13,84 s. Por último, se concluye que 30 segundos de fuga no son suficientes para alcanzar el límite dañino (147 ppm).Universidad de Lima2022-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdftext/htmlhttps://revistas.ulima.edu.pe/index.php/Ingenieria_industrial/article/view/611210.26439/ing.ind2022.n43.6112Ingeniería Industrial; No. 43 (2022); 117-136Ingeniería Industrial; Núm. 43 (2022); 117-1362523-63261025-992910.26439/ing.ind2022.n43reponame:Revistas - Universidad de Limainstname:Universidad de Limainstacron:ULIMAspahttps://revistas.ulima.edu.pe/index.php/Ingenieria_industrial/article/view/6112/5894https://revistas.ulima.edu.pe/index.php/Ingenieria_industrial/article/view/6112/5911info:eu-repo/semantics/openAccessoai:ojs.pkp.sfu.ca:article/61122024-10-14T17:49:53Z |
| dc.title.none.fl_str_mv |
Influence of position of mq-6 sensor and elapsed time on the concentration detection of LPG in a domestic leak Influencia de la posición del sensor MQ-6 y el tiempo transcurrido en la detección de concentración de GLP en una fuga doméstica |
| title |
Influence of position of mq-6 sensor and elapsed time on the concentration detection of LPG in a domestic leak |
| spellingShingle |
Influence of position of mq-6 sensor and elapsed time on the concentration detection of LPG in a domestic leak Bueno Vera, Alejandro Arduino Matlab machine learning MQ-6 LPG gas detection Arduino Matlab machine learning MQ-6 GLP detección de gas |
| title_short |
Influence of position of mq-6 sensor and elapsed time on the concentration detection of LPG in a domestic leak |
| title_full |
Influence of position of mq-6 sensor and elapsed time on the concentration detection of LPG in a domestic leak |
| title_fullStr |
Influence of position of mq-6 sensor and elapsed time on the concentration detection of LPG in a domestic leak |
| title_full_unstemmed |
Influence of position of mq-6 sensor and elapsed time on the concentration detection of LPG in a domestic leak |
| title_sort |
Influence of position of mq-6 sensor and elapsed time on the concentration detection of LPG in a domestic leak |
| dc.creator.none.fl_str_mv |
Bueno Vera, Alejandro Luis Ortiz, Gianfranco Taquía Gutiérrez, José Antonio Bueno Vera, Alejandro Luis Ortiz, Gianfranco Taquía Gutiérrez, José Antonio |
| author |
Bueno Vera, Alejandro |
| author_facet |
Bueno Vera, Alejandro Luis Ortiz, Gianfranco Taquía Gutiérrez, José Antonio Bueno Vera, Alejandro |
| author_role |
author |
| author2 |
Luis Ortiz, Gianfranco Taquía Gutiérrez, José Antonio Bueno Vera, Alejandro |
| author2_role |
author author author |
| dc.subject.none.fl_str_mv |
Arduino Matlab machine learning MQ-6 LPG gas detection Arduino Matlab machine learning MQ-6 GLP detección de gas |
| topic |
Arduino Matlab machine learning MQ-6 LPG gas detection Arduino Matlab machine learning MQ-6 GLP detección de gas |
| description |
Gas leaks in Lima and Ica (Peru) increase every year, causing accidents and irreparable damage to the population. In this article, a controlled leak was produced using a two-burner kitchen and an array of MQ-6 sensors positioned at different angles (45°, 0° and 30°) with respect to the kitchen. The results show that, if the kitchen is in a high position (87 cm), the detected concentration is lower, but the detection is faster (6,419 s) if the arrangement is located 50 cm from the origin of the leak. The detection time is between 13,515 s and 21,740 s and the maximum concentration detected is 98 ppm. The best adapted learning model is Support Vector Machine, with an RMSE of 4,61 ppm. It is concluded that the best position for gas detection was at a height of 47 cm above the ground, at 50 cm from the sensor and at an angle of 0°. The detection time is 13,84 s. Finally, it is concluded that 30 seconds of leakage are not enough to reach the harmful limit (147 ppm). |
| publishDate |
2022 |
| dc.date.none.fl_str_mv |
2022-12-01 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
https://revistas.ulima.edu.pe/index.php/Ingenieria_industrial/article/view/6112 10.26439/ing.ind2022.n43.6112 |
| url |
https://revistas.ulima.edu.pe/index.php/Ingenieria_industrial/article/view/6112 |
| identifier_str_mv |
10.26439/ing.ind2022.n43.6112 |
| dc.language.none.fl_str_mv |
spa |
| language |
spa |
| dc.relation.none.fl_str_mv |
https://revistas.ulima.edu.pe/index.php/Ingenieria_industrial/article/view/6112/5894 https://revistas.ulima.edu.pe/index.php/Ingenieria_industrial/article/view/6112/5911 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf text/html |
| dc.publisher.none.fl_str_mv |
Universidad de Lima |
| publisher.none.fl_str_mv |
Universidad de Lima |
| dc.source.none.fl_str_mv |
Ingeniería Industrial; No. 43 (2022); 117-136 Ingeniería Industrial; Núm. 43 (2022); 117-136 2523-6326 1025-9929 10.26439/ing.ind2022.n43 reponame:Revistas - Universidad de Lima instname:Universidad de Lima instacron:ULIMA |
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Universidad de Lima |
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ULIMA |
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ULIMA |
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Revistas - Universidad de Lima |
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Revistas - Universidad de Lima |
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Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).