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Mikrodalga kurutucu için bulanık modelleme: Pamuklu dokuma kumaş kurutma işlemi

Year 2023, Volume: 15 Issue: 1, 19 - 26, 11.05.2023
https://doi.org/10.55974/utbd.1226485

Abstract

Mikrodalga kurutma, geleneksel kurutma yöntemlerine göre daha çabuk olması, ürün içinde kurumanın daha düzgün olması ve enerji verimliliği sebebiyle öne çıkmaktadır. Bu çalışmada, bir mikrodalga kurutucunun bulanık modellemesi geliştirilmiştir. Mikrodalga kurutucu doğrusal olmayan bir kurutucu olarak kabul edilmiştir. Önerilen bulanık model, farklı elektriksel güçlerde ve farklı kuruma süreleri için kurutma hızının tahmin edilmesi için kullanılmıştır. Farklı deneysel ölçümler bu modelin güvenilirliğini değerlendirmek için kullanılmıştır. Diğer modelleme teknikleri ile karşılaştırıldığında simülasyon sayesinde, kurutucunun bulanık modeli, kurutma hızının anında tahmin edilmesini sağlar. Bu çalışma, belirli bir ürün için zaman ve enerji tasarrufu sağlayan makine parametrelerinin belirlenmesine yardımcı olacaktır.Bulanık model ile tahmin edilen davranış, tanımlanan modelin uygunluğunu doğrular niteliktedir.

References

  • Haghi AK, Amanifard N. Analysis of Heat and Mass Transfer During Microwave Drying of Food Products. Brazilian Journal of Chemical Engineering, 25 (3), 491-501, 2008.
  • Uysal B, Özkal, SG. Limon Kabuklarının Sıcak Hava, Mikrodalga ve Sıcak Hava-Mikrodalga Kombinasyonu ile Kurutulması, Journal of the Institute of Science and Technology, 12 (4) , 2223-2236, 2022.
  • Coruk KS, Baltacıoğlu H. Determination of the Effect of Different Drying Methods on the Physicochemical Properties of Potato Powder Using Multivariate Analysis. Turkish Journal of Agriculture-Food Science and Technology, 10(7), 1300-1307, 2022.
  • Motevali A, Minaei S, Khoshtagaza MH. Evaluation of Energy Consumption in Different Drying Methods, Energy Conversion and Management, 1192 – 1199, 2011.
  • Zoukit A, El Ferouali H, Salhi I, Doubabi S, Abdenouri N. Fuzzy modeling of a hybrid solar dryer: experimental validation. Journal of Energy Systems, 3(1), 1-12, 2019.
  • Zoukit A, El Ferouali H, Salhi I, Doubabi S, Abdenouri N. Takagi Sugeno fuzzy modeling applied to an indirect solar dryer operated in both natural and forced convection. Renewable Energy, 133, 849-860, 2019.
  • Azhari Asyauqi MF, Apriaskar E, Djuniadi D. Simulasi Sistem Pencuci Bahan Tekstil Berbasis Logika Fuzzy, JTE UNIBA (Jurnal Teknik Elektro Uniba), 5 (2), 109-113, 2021.
  • Hosseinpou S, Martynenko A. Application of fuzzy logic in drying: A review. Drying Technology, 40(5), 797-826, 2022.
  • Altınten A, Demirci Y, Pekel LC, Alpbaz M. Elektrokoagülasyon Reaktöründe Bulanık Kontrol Metodu ile Ph, İletkenlik ve Sıcaklığın Eş Zamanlı Kontrolü. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 31 (4), 987-996, 2016.
  • Özerdem A, Tarakçıoğlu I, Özgüney A. Mikrodalga Enerjisinin Reaktif Baskılı Pamuklu Kumaşların Fiksajında Kullanılabilirliği, Tekstil ve Konfeksiyon, 4, 289-296, 2008.
  • Chen L, Wang L, Wu X, et al. A process-level water conservation and pollution control performance evaluation tool of cleaner production technology in textile industry. J Cleaner Prod., 143, 1137–1143, 2017. Oktav Bulut M, and Sana NH. Modification of woolen fabric with plasma for a sustainable production. Fibers Polym., 19, 1887–1897, 2018.
  • Rattanadecho P and Makul N. Microwave-assisted drying: a review of the state-of-the-art. Drying Technol., 34, 1–38. 2016.
  • Katovic D, Vukusic SB, Grgac SF, et al. The effect of microwave drying on warp sizing. Text. Res. Journal, 78, 353–360, 2008.
  • Hosseinpour, S, & Martynenko, A. Application of fuzzy logic in drying: A review. Drying Technology, 40(5), 797-826, 2022.
  • Arief M, Nugroho F, et al. Analysis of Maizena Drying System Using Temperature Control Based Fuzzy Logic Method. AIP Conference Proceedings; AIP Publishing, 1941(1), 020005, March 2018.
  • Heriansyah H, Istiqphara I, Adliani N. Optimization of Herbal Dryer System Based on Smart Fuzzy and Internet of Thing (IOT). Int. J. Eng. Sci. Appl., 6, 104–110, 2019.
  • Nadian H, Abbaspour-Fard H, Martynenko A, Golzarian R. An Intelligent Integrated Control of Hybrid Hot Air-Infrared Dryer Based on Fuzzy Logic and Computer Vision System. Comput. Electron. Agric.,137, 138–149, 2017.
  • Sourveloudis C, Kiralakis L. Rotary Drying of Olive Stones: Fuzzy Modeling and Control. WSEASTrans. Syst.,4, 2361–2368, 2005.
  • Dayık M, Kodaloğlu M. Kondisyonlama Şartlarının İplik Rutubetine Etkisinin Yapay Zekâ Yardımıyla Tespiti. Tekstil Teknolojileri Elektronik Dergisi, 2, 25-32, 2007.
  • Kodaloğlu M, & Kodaloğlu, F. A. Evaluation of Thermal Comfort in Terms of Occupational Safety in Weavıng Facilities By Fuzzy Logic. International Journal of 3D Printing Technologies and Digital Industry, 6(2), 273-279, 2022.
  • Atthajariyakul S, Leephakpreeda, T. Fluidized Bed Paddy Drying in Optimal Conditions via Adaptive Fuzzy Logic Control. J. Food Eng., 75, 104–114, 2006.
  • Khodabakhsh Aghdam, H, et al. Modeling for Drying Kinetics of Papaya Fruit Using Fuzzy Logic Table Look-up Scheme. Int. Food Res. J., 22, 1234–1239, 2015.
  • Bagheri N, Nazilla T, Javadikia, H. Developmentand Evaluation of an Adaptive Neuro FuzzyInterface Models to Predict Performance of a Solar Dryer. Agric. Eng. Int. CIGR J., 17, 112–121, 2015.
  • Jafari M, Ganje M, Dehnad D. Ghanbari, V.Mathematical, Fuzzy Logic and Artificial Neural Network Modeling Techniques to Predict Drying Kinetics of Onion. J. Food Process, 40, 329–339. 2016.
  • Abdenouri N, Zoukit A, Salhi I, Doubabi S. Model identification and fuzzy control of the temperature inside an active hybrid solar indirect dryer. Solar Energy, 231, 328-342, 2022.
  • Kayacan C, Dayık M, Çolak O, Kodaloglu M. Velocity Control of Weft Insertion on Air Jet Looms by Fuzzy Logic, Fibres & Textiles in Eastern Europe, Vol.12, No. 3(47), 29-33, 2004.
  • Bayhan M, Kodaloğlu M, Cengiz Y, Kaplan S. Drum ve Loop Sistemlerinde Atkı Hareketinin Dinamik Modellenmesi ve Hızın Bulanık Mantıkla Kontrolü, Tekstil Maraton Dergisi, 63-69, Mart / Nisan 2002.
  • Kodaloğlu M, Dayık M, Çolak O, Kaplan S. Hava Jetli Dokumada İplik Tipinin Atkı Hızına Etkisinin Bulanık Mantıkla Tespiti, Tekstil Maraton Dergisi, 56-61, Mayıs / Haziran 2002.
  • Júnior MP, et al. Energy savings in a rotary dryer due to a fuzzy multivariable control application. Drying Technology, 40(6), 1196-1209, 2022.

Fuzzy modeling applied to a microwave dryer: Cotton weaving fabric drying process

Year 2023, Volume: 15 Issue: 1, 19 - 26, 11.05.2023
https://doi.org/10.55974/utbd.1226485

Abstract

Microwave drying stands out because it is faster than traditional drying methods, drying in the product is more uniform and energy efficiency. In this study, fuzzy modeling of a microwave dryer was developed. Microwave dryer is considered as a non-linear dryer. The proposed fuzzy model is used to estimate the drying rate for different electrical powers and different drying times. Different experimental measurements were used to evaluate the reliability of this model. Compared to other modeling techniques, thanks to simulation, the fuzzy model of the dryer provides an immediate estimation of the drying rate. This study will provide drying rates under demanded conditions and help determining machine parameters for a given product providing time and energy saving.The behavior predicted by the fuzzy model confirms the suitability of the defined model.

References

  • Haghi AK, Amanifard N. Analysis of Heat and Mass Transfer During Microwave Drying of Food Products. Brazilian Journal of Chemical Engineering, 25 (3), 491-501, 2008.
  • Uysal B, Özkal, SG. Limon Kabuklarının Sıcak Hava, Mikrodalga ve Sıcak Hava-Mikrodalga Kombinasyonu ile Kurutulması, Journal of the Institute of Science and Technology, 12 (4) , 2223-2236, 2022.
  • Coruk KS, Baltacıoğlu H. Determination of the Effect of Different Drying Methods on the Physicochemical Properties of Potato Powder Using Multivariate Analysis. Turkish Journal of Agriculture-Food Science and Technology, 10(7), 1300-1307, 2022.
  • Motevali A, Minaei S, Khoshtagaza MH. Evaluation of Energy Consumption in Different Drying Methods, Energy Conversion and Management, 1192 – 1199, 2011.
  • Zoukit A, El Ferouali H, Salhi I, Doubabi S, Abdenouri N. Fuzzy modeling of a hybrid solar dryer: experimental validation. Journal of Energy Systems, 3(1), 1-12, 2019.
  • Zoukit A, El Ferouali H, Salhi I, Doubabi S, Abdenouri N. Takagi Sugeno fuzzy modeling applied to an indirect solar dryer operated in both natural and forced convection. Renewable Energy, 133, 849-860, 2019.
  • Azhari Asyauqi MF, Apriaskar E, Djuniadi D. Simulasi Sistem Pencuci Bahan Tekstil Berbasis Logika Fuzzy, JTE UNIBA (Jurnal Teknik Elektro Uniba), 5 (2), 109-113, 2021.
  • Hosseinpou S, Martynenko A. Application of fuzzy logic in drying: A review. Drying Technology, 40(5), 797-826, 2022.
  • Altınten A, Demirci Y, Pekel LC, Alpbaz M. Elektrokoagülasyon Reaktöründe Bulanık Kontrol Metodu ile Ph, İletkenlik ve Sıcaklığın Eş Zamanlı Kontrolü. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 31 (4), 987-996, 2016.
  • Özerdem A, Tarakçıoğlu I, Özgüney A. Mikrodalga Enerjisinin Reaktif Baskılı Pamuklu Kumaşların Fiksajında Kullanılabilirliği, Tekstil ve Konfeksiyon, 4, 289-296, 2008.
  • Chen L, Wang L, Wu X, et al. A process-level water conservation and pollution control performance evaluation tool of cleaner production technology in textile industry. J Cleaner Prod., 143, 1137–1143, 2017. Oktav Bulut M, and Sana NH. Modification of woolen fabric with plasma for a sustainable production. Fibers Polym., 19, 1887–1897, 2018.
  • Rattanadecho P and Makul N. Microwave-assisted drying: a review of the state-of-the-art. Drying Technol., 34, 1–38. 2016.
  • Katovic D, Vukusic SB, Grgac SF, et al. The effect of microwave drying on warp sizing. Text. Res. Journal, 78, 353–360, 2008.
  • Hosseinpour, S, & Martynenko, A. Application of fuzzy logic in drying: A review. Drying Technology, 40(5), 797-826, 2022.
  • Arief M, Nugroho F, et al. Analysis of Maizena Drying System Using Temperature Control Based Fuzzy Logic Method. AIP Conference Proceedings; AIP Publishing, 1941(1), 020005, March 2018.
  • Heriansyah H, Istiqphara I, Adliani N. Optimization of Herbal Dryer System Based on Smart Fuzzy and Internet of Thing (IOT). Int. J. Eng. Sci. Appl., 6, 104–110, 2019.
  • Nadian H, Abbaspour-Fard H, Martynenko A, Golzarian R. An Intelligent Integrated Control of Hybrid Hot Air-Infrared Dryer Based on Fuzzy Logic and Computer Vision System. Comput. Electron. Agric.,137, 138–149, 2017.
  • Sourveloudis C, Kiralakis L. Rotary Drying of Olive Stones: Fuzzy Modeling and Control. WSEASTrans. Syst.,4, 2361–2368, 2005.
  • Dayık M, Kodaloğlu M. Kondisyonlama Şartlarının İplik Rutubetine Etkisinin Yapay Zekâ Yardımıyla Tespiti. Tekstil Teknolojileri Elektronik Dergisi, 2, 25-32, 2007.
  • Kodaloğlu M, & Kodaloğlu, F. A. Evaluation of Thermal Comfort in Terms of Occupational Safety in Weavıng Facilities By Fuzzy Logic. International Journal of 3D Printing Technologies and Digital Industry, 6(2), 273-279, 2022.
  • Atthajariyakul S, Leephakpreeda, T. Fluidized Bed Paddy Drying in Optimal Conditions via Adaptive Fuzzy Logic Control. J. Food Eng., 75, 104–114, 2006.
  • Khodabakhsh Aghdam, H, et al. Modeling for Drying Kinetics of Papaya Fruit Using Fuzzy Logic Table Look-up Scheme. Int. Food Res. J., 22, 1234–1239, 2015.
  • Bagheri N, Nazilla T, Javadikia, H. Developmentand Evaluation of an Adaptive Neuro FuzzyInterface Models to Predict Performance of a Solar Dryer. Agric. Eng. Int. CIGR J., 17, 112–121, 2015.
  • Jafari M, Ganje M, Dehnad D. Ghanbari, V.Mathematical, Fuzzy Logic and Artificial Neural Network Modeling Techniques to Predict Drying Kinetics of Onion. J. Food Process, 40, 329–339. 2016.
  • Abdenouri N, Zoukit A, Salhi I, Doubabi S. Model identification and fuzzy control of the temperature inside an active hybrid solar indirect dryer. Solar Energy, 231, 328-342, 2022.
  • Kayacan C, Dayık M, Çolak O, Kodaloglu M. Velocity Control of Weft Insertion on Air Jet Looms by Fuzzy Logic, Fibres & Textiles in Eastern Europe, Vol.12, No. 3(47), 29-33, 2004.
  • Bayhan M, Kodaloğlu M, Cengiz Y, Kaplan S. Drum ve Loop Sistemlerinde Atkı Hareketinin Dinamik Modellenmesi ve Hızın Bulanık Mantıkla Kontrolü, Tekstil Maraton Dergisi, 63-69, Mart / Nisan 2002.
  • Kodaloğlu M, Dayık M, Çolak O, Kaplan S. Hava Jetli Dokumada İplik Tipinin Atkı Hızına Etkisinin Bulanık Mantıkla Tespiti, Tekstil Maraton Dergisi, 56-61, Mayıs / Haziran 2002.
  • Júnior MP, et al. Energy savings in a rotary dryer due to a fuzzy multivariable control application. Drying Technology, 40(6), 1196-1209, 2022.
There are 29 citations in total.

Details

Primary Language English
Subjects Mechanical Engineering
Journal Section Articles
Authors

Feyza Akarslan Kodaloğlu 0000-0002-7855-8616

Publication Date May 11, 2023
Published in Issue Year 2023 Volume: 15 Issue: 1

Cite

IEEE F. Akarslan Kodaloğlu, “Fuzzy modeling applied to a microwave dryer: Cotton weaving fabric drying process”, IJTS, vol. 15, no. 1, pp. 19–26, 2023, doi: 10.55974/utbd.1226485.

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