Modeling of a hazelnut dryer assisted heat pump by using artificial neural networks

被引：43

作者：

Ceylan, Ilhan ^{[1
]}

Aktas, Mustafa ^{[2
]}

机构：

[1] Karabuk Univ, Mech Educ Dept, Tech Educ Fac, Karabuk, Turkey

[2] Gazi Univ, Mech Educ Dept, Tech Educ Fac, TR-06503 Ankara, Turkey

来源：

APPLIED ENERGY | 2008年 / 85卷 / 09期

关键词：

heat pump dryer; hazelnut; artificial neural networks;

D O I：

10.1016/j.apenergy.2007.10.013

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

The artificial neural network (ANN) approach is generic technique for mapping non-linear relationships between inputs and outputs without knowing the details of these relationships. In this paper, an application of the ANN has been presented for a PID controlled heat pump dryer. In PID controlled heat pump dryer, air velocity changed according to the temperature value which is set in process control device. Heat pump dryer was tested drying of hazelnut at 40 degrees C, 45 degrees C and 50 degrees C drying air temperatures. By training the experiment results with ANN, drying air velocities, moisture content of hazelnuts and total drying time were predicted for 42 degrees C,44 degrees C, 46 degrees C and 48 degrees C drying air temperatures. (c) 2008 Elsevier Ltd. All rights reserved.

引用

页码：841 / 854

页数：14

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