بررسی تجربی و مدل‌سازی خشک‌کردن گیاه جعفری با استفاده از شبکۀ عصبی مصنوعی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشگاه آزاد اسلامی، دانشکده فنی، قزوین، ایران

2 رشت،دانشگاه گیلان،دانشکده فنی، گروه مهندسی شیمی

3 دانشگاه گیلان- دانشکده فنی- گروه مهدسی شیمی

4 گروه مهندسی شیمی دانشکده فنی دانشگاه گیلان

چکیده

در این تحقیق،گیاه جعفری به‌صورت منفرد و توده‌ای، در دماهای 46، 58 و 68 درجۀ سلسیوس و در ضخامت‌های13/0 تا 17/0 میلی‌متر و بازه زمانی 0 تا 140 دقیقه در یک خشک‌کن سینی‌دار آزمایشگاهی خشک شد. نیز، ﺗﺄثیر عواملی مانند دما و زمان بر نرخ خشک‌شدن بررسی شد. زمان و رطوبت تعادلی به‌ترتیب 140 دقیقه و 0003/0 مشاهده شد. هم‌چنین، منحنی جنبش‌شناسی فرایند نشان می‌دهد که خشک‌شدن بیشتر در مرحلۀ نزولی اتفاق می‌افتد که به‌دلیل پایین‌بودن مقاومت خارجی در مقابل انتقال جرم و حرارت است. در مطالعۀ اثر دما، مشاهده شد که با افزایش دما از 46 به 68 درجۀ سلسیوس، گیاه جعفری با شیب بیشتر به رطوبت تعادلی می‌رسد. سپس، فرایند خشک‌شدن تک‌برگ و تودۀ جعفری با استفاده از شبکه‌های عصبی مصنوعی پیش‌خور و پیش‌رو مدل‌سازی شد و داده‌های مدل با داده‌های تجربی مقایسه شدند، که مناسب‌ترین نتیجه به‌وسیلۀ شبکۀ عصبی مصنوعی پیش‌خور برای تک‌برگ جعفری، با الگوریتم لونبرگ- مارکوارت و 13 نرون و ضریب تبیین 9987/0 و برای تودۀ جعفری با 9 نرون بهینه و ضریب تبیین 9993/0 به‌دست‌آمد که نشان‌دهندۀ دقت بالای شبکۀ عصبی مصنوعی است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Investigation the Experimental Method and Modeling for Drying of Parsley Bulk by Using Artificial Neural Network

چکیده [English]

In this study, the single-leaf of parsley and also bulk of particles at temperatures of 46, 58, and 68°C and the thickness of 0.13 to 0.17 mm and the period from 0 to 140 minutes in a laboratory fixed bed dryer dried. Also, the single leaf of parsley and the mass dried in the sun. To dry the parsley in the dryer, five samples were considered for each temperature and the weight of samples during the drying process is continuously recorded until changes in the volume of samples to zero. Then the influence of parameters such as the temperature of the drying rate is examined. Equilibrium time and humidity were observed to be 140 minutes and 0.0003, respectively. Also, the process kinetics curve shows that more drying occurs in the descending phase due to the low external resistance to mass and heat transfer. In studying the effect of temperature, it was observed that with increasing temperature from 46 to 68℃, parsley reaches equilibrium humidity with a greater slope. Then drying process of a single leaf, and parsley mass, using feed-forward neural networks and leading, was modeled and the results of the neural network with the results obtained from experimental data were compared. The best result by a feed-forward neural network for single-leaf parsley with Levenberg - Marquardt algorithm, and 13 neurons and the coefficient of determination 0.9987 and parsley mass with nine neurons optimized and coefficient 0.9993obtainedwhich demonstrates the high accuracy of the artificial neural network.

کلیدواژه‌ها [English]

  • Tray Dryers
  • Drying Parsley
  • Back Propagation
  • Neural Network
  • Levenberg–Marquardt Algorithm
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