Design and validation of a mechanical sorter for municipal organic wastes
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Published:
Dec 13, 2022
Keywords:
organic waste, sorting, anaerobic decomposition, sorting machine.
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Abstract
The population increase has caused an increase in the emission of methane andcarbon dioxide, being gases that cause the negative impact of the greenhouse effect,in greater volume compared to other types of polluting emissions. The increase in organicwaste has been detrimental to the environment as it is the main cause of methane gasemissions. On the other hand, one of the great challenges of current engineering is togenerate clean energies that meet the different needs of the demand of non-renewablesources of fossil origin, highlighting the use of biogas produced by bacterial anaerobicdecomposition. That is why, the present work evidences the second phase of research,which consists of creating a mechanical device for organic waste classification to mitigatethe environmental impact in the municipality of Sopó Cundinamarca, for this purpose threemoments of organic matter collection are used through an initial filtration, a conveyor beltthat will serve as a connecting bridge of an organic waste classification machine at scaleusing neural networks and image recognition techniques to a selector of organic andinorganic matter that will locate the particles in different places.
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Torres Payoma, F., Vega Velásquez , B., Ramírez Alvarado , R., Hernández Aldana, F., & García Guarín , J. (2022). Design and validation of a mechanical sorter for municipal organic wastes. Ingenio Magno, 13(1), 113 - 124. Retrieved from http://revistas.ustatunja.edu.co/index.php/ingeniomagno/article/view/2576
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Artículos Vol. 13-1
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With this document, I/We certify that the article submitted for possible publication in the institutional journal INGENIO MAGNO of the Research Center Alberto Magno CIIAM of the University Santo Tomás, Tunja campus, is entirely of my(our) own writing, and is a product of my(our) direct intellectual contribution to knowledge.
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References
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[14] Castañeda-Torres, S., & Rodríguez- Miranda, J. P. (March 01, 2017). Modelo de aprovechamiento sustentable de residuos sólidos orgánicos en Cundinamarca, Colombia. Universidad Y Salud, 19, 1, 116-125.
[15] Toğaçar, M., Ergen, B., & Cömert, Z. (2020). Waste classification using AutoEncoder network with integrated feature selection method in convolutional neural network models. Measurement, 153, 107459.
[16] Vo, A. H., Vo, M. T., & Le, T. (2019). A novel framework for trash classification using deep transfer learning. IEEE Access, 7, 178631-178639.
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[18] Tanguay-Rioux, F., Spreutels, L., Héroux, M., & Legros, R. (2022). Mixed modeling approach for mechanical sorting processes based on physical properties of municipal solid waste. Waste Management, 144, 533-542. https://doi. org/10.1016/j.wasman.2022.04.025
[19] Borole, A. S., & Phadke, A. R. (2022). A Review on the Development of Solar Power Automatic Biodegradable Waste Sorter and Composter. Smart Technologies for Energy, Environment
[2] Rodríguez, D. (2011). Gestión organizacional. Ediciones UC.
[3] Barrena, M., Gamarra, O., Maicelo, J. «Producción de biogás en laboratorio a partir de residuos domésticos y ganaderos y su escalamiento». Revista Aporte Santiaguino, n.o 1, 2010, pp. 86- 92.
[4] Villemain, C. (2018). Cómo la basura afecta al desarrollo de América Latina. Naciones Unidas. Recuperado de Naciones Unidas website: https://news. un. o rg/es/story/2018/10/1443562.
[5] Martínez, A. L., Montecinos, C. C., Rasillo, L. C., & de Cortázar, A. L. G. CUANTIFICACIÓN DE EMISIONES DIFUSAS MEDIANTE CAMARA DE FLUJO EN UN VERTEDERO DE RESIDUOS URBANOS.
[6] Asís, H., Dopazo, F., & Gianoglio, P. (2006). Producción de energía a partir de biogás obtenido de residuos sólidos urbanos.
[7] Minutillo, M., Perna, A., & Sorce, A. (2020). Plantas de producción de hidrógeno verde mediante vapor de biogás y procesos de reformado autotérmico: análisis energético y exergético. Energía Aplicada, 277, 115452. https://doi.org/10.1016/j. apenergy.2020.115452
[8] Kim, J., Qi, M., Kim, M., Lee, J., Lee, I., & Moon, I. (2022). Biogas reforming integrated with PEM electrolysis via oxygen storage process for green hydrogen production: From design to robust optimization. Energy Conversion and Management, 251, 115021. https://doi.org/10.1016/j. enconman.2021.115021
[9] Kumar, R., Kumar, A., & Pal, A. (2022). Overview of hydrogen production from biogas reforming: Technological advancement. International Journal of Hydrogen Energy, https://doi. org/10.1016/j.ijhydene.2022.08.059
[10] Cabello, A., Mendiara, T., Abad, A., Izquierdo, M. T., & García-Labiano, F. (2022). Production of hydrogen by chemical looping reforming of methane and biogas using a reactive and durable Cu-based oxygen carrier. Fuel, 322, 124250. https://doi. org/10.1016/j.fuel.2022.124250
[11] Vidal-Barrero, F., Baena-Moreno, F. M., Preciado-Cárdenas, C., Villanueva- Perales, Á, & Reina, T. R. (2022). Hydrogen production from landfill biogas: Profitability analysis of a real case study. Fuel, 324, 124438.
[12] Nnamoko, N., Barrowclough, J., & Procter, J. (2022). Solid Waste Image Classification Using Deep Convolutional Neural Network. Infrastructures, 7(4), 47.
[13] Altikat, A. A. A. G. S., Gulbe, A., & Altikat, S. (2022). Intelligent solid waste classification using deep convolutional neural networks. International Journal of Environmental Science and Technology, 19(3), 1285-1292.
[14] Castañeda-Torres, S., & Rodríguez- Miranda, J. P. (March 01, 2017). Modelo de aprovechamiento sustentable de residuos sólidos orgánicos en Cundinamarca, Colombia. Universidad Y Salud, 19, 1, 116-125.
[15] Toğaçar, M., Ergen, B., & Cömert, Z. (2020). Waste classification using AutoEncoder network with integrated feature selection method in convolutional neural network models. Measurement, 153, 107459.
[16] Vo, A. H., Vo, M. T., & Le, T. (2019). A novel framework for trash classification using deep transfer learning. IEEE Access, 7, 178631-178639.
[17] Lubongo, C., & Alexandridis, P. (2022). Assessment of Performance and Challenges in Use of Commercial Automated Sorting Technology for Plastic Waste. Recycling, 7(2), 11. https://doi.org/10.3390/ recycling7020011
[18] Tanguay-Rioux, F., Spreutels, L., Héroux, M., & Legros, R. (2022). Mixed modeling approach for mechanical sorting processes based on physical properties of municipal solid waste. Waste Management, 144, 533-542. https://doi. org/10.1016/j.wasman.2022.04.025
[19] Borole, A. S., & Phadke, A. R. (2022). A Review on the Development of Solar Power Automatic Biodegradable Waste Sorter and Composter. Smart Technologies for Energy, Environment