Modelling heat-flow prototype dryer using ANFIS optimized by PSO
2023
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Конференцијски прилог (Објављена верзија)
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Chamber dryers are widely used in various industries in order to remove the moisture from solid materials efficiently. Optimizing the design and operational parameters of chamber dryers plays a crucial role in enhancing their performance and energy efficiency. In order to maintain the temperature at the desired level, it is necessary to implement a good control system. To be able to facilitate the process of finding and setting parameters of the controller, for many control algorithms it is essential to make the reliable model of the object. The aim is to develop both reliable and accurate predictive model that can assist in optimizing the design, structures, and inspection processes of chamber dryers, which will lead to enhanced energy efficiency, harvesting and improved drying performance.
In this paper, the authors propose a novel approach for modeling heat flow transfer in chamber dryers using an Adaptive Neuro-Fuzzy Inference System (ANFIS). The Quanser chamber was selected as th...e object of the research because of how closely its geometry, material choice, and air flow resemble the structural properties of a dryer. To obtain the most realistic model possible, parameters of ANFIS were found using Particle Swarm Optimization algorithm. By incorporating historical operational data of experimental measurements, the ANFIS model can learn and adapt to the dynamic behavior of the dryer system.
Кључне речи:
Design and Structures / Optimization / ANFIS / PSO / Heat-Flow Chamber Dryer / Energy EfficiencИзвор:
ISAE 2023 - Proceedings ; The 6th International Symposium on Agricultural Engineering - ISAE 2023 19th - 21st October 2023, Belgrade, Serbia, 2023, 219-228Финансирање / пројекти:
- Истраживање и развој опреме и система за индустријску производњу, складиштење и прераду поврћа и воћа (RS-MESTD-Technological Development (TD or TR)-35043)
- Иновативни приступ у примени интелигентних технолошких система за производњу делова од лима заснован на еколошким принципима (RS-MESTD-Technological Development (TD or TR)-35004)
Колекције
Институција/група
Mašinski fakultetTY - CONF AU - Vesović, Mitra AU - Jovanović, Radiša AU - Perišić, Natalija AU - Sretenović, Aleksandra PY - 2023 UR - https://machinery.mas.bg.ac.rs/handle/123456789/7297 AB - Chamber dryers are widely used in various industries in order to remove the moisture from solid materials efficiently. Optimizing the design and operational parameters of chamber dryers plays a crucial role in enhancing their performance and energy efficiency. In order to maintain the temperature at the desired level, it is necessary to implement a good control system. To be able to facilitate the process of finding and setting parameters of the controller, for many control algorithms it is essential to make the reliable model of the object. The aim is to develop both reliable and accurate predictive model that can assist in optimizing the design, structures, and inspection processes of chamber dryers, which will lead to enhanced energy efficiency, harvesting and improved drying performance. In this paper, the authors propose a novel approach for modeling heat flow transfer in chamber dryers using an Adaptive Neuro-Fuzzy Inference System (ANFIS). The Quanser chamber was selected as the object of the research because of how closely its geometry, material choice, and air flow resemble the structural properties of a dryer. To obtain the most realistic model possible, parameters of ANFIS were found using Particle Swarm Optimization algorithm. By incorporating historical operational data of experimental measurements, the ANFIS model can learn and adapt to the dynamic behavior of the dryer system. C3 - ISAE 2023 - Proceedings ; The 6th International Symposium on Agricultural Engineering - ISAE 2023 19th - 21st October 2023, Belgrade, Serbia T1 - Modelling heat-flow prototype dryer using ANFIS optimized by PSO EP - 228 SP - 219 UR - https://hdl.handle.net/21.15107/rcub_machinery_7297 ER -
@conference{ author = "Vesović, Mitra and Jovanović, Radiša and Perišić, Natalija and Sretenović, Aleksandra", year = "2023", abstract = "Chamber dryers are widely used in various industries in order to remove the moisture from solid materials efficiently. Optimizing the design and operational parameters of chamber dryers plays a crucial role in enhancing their performance and energy efficiency. In order to maintain the temperature at the desired level, it is necessary to implement a good control system. To be able to facilitate the process of finding and setting parameters of the controller, for many control algorithms it is essential to make the reliable model of the object. The aim is to develop both reliable and accurate predictive model that can assist in optimizing the design, structures, and inspection processes of chamber dryers, which will lead to enhanced energy efficiency, harvesting and improved drying performance. In this paper, the authors propose a novel approach for modeling heat flow transfer in chamber dryers using an Adaptive Neuro-Fuzzy Inference System (ANFIS). The Quanser chamber was selected as the object of the research because of how closely its geometry, material choice, and air flow resemble the structural properties of a dryer. To obtain the most realistic model possible, parameters of ANFIS were found using Particle Swarm Optimization algorithm. By incorporating historical operational data of experimental measurements, the ANFIS model can learn and adapt to the dynamic behavior of the dryer system.", journal = "ISAE 2023 - Proceedings ; The 6th International Symposium on Agricultural Engineering - ISAE 2023 19th - 21st October 2023, Belgrade, Serbia", title = "Modelling heat-flow prototype dryer using ANFIS optimized by PSO", pages = "228-219", url = "https://hdl.handle.net/21.15107/rcub_machinery_7297" }
Vesović, M., Jovanović, R., Perišić, N.,& Sretenović, A.. (2023). Modelling heat-flow prototype dryer using ANFIS optimized by PSO. in ISAE 2023 - Proceedings ; The 6th International Symposium on Agricultural Engineering - ISAE 2023 19th - 21st October 2023, Belgrade, Serbia, 219-228. https://hdl.handle.net/21.15107/rcub_machinery_7297
Vesović M, Jovanović R, Perišić N, Sretenović A. Modelling heat-flow prototype dryer using ANFIS optimized by PSO. in ISAE 2023 - Proceedings ; The 6th International Symposium on Agricultural Engineering - ISAE 2023 19th - 21st October 2023, Belgrade, Serbia. 2023;:219-228. https://hdl.handle.net/21.15107/rcub_machinery_7297 .
Vesović, Mitra, Jovanović, Radiša, Perišić, Natalija, Sretenović, Aleksandra, "Modelling heat-flow prototype dryer using ANFIS optimized by PSO" in ISAE 2023 - Proceedings ; The 6th International Symposium on Agricultural Engineering - ISAE 2023 19th - 21st October 2023, Belgrade, Serbia (2023):219-228, https://hdl.handle.net/21.15107/rcub_machinery_7297 .